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

2015 ◽  
Author(s):  
Sarai Meyer ◽  
James Chappell ◽  
Sitara Sankar ◽  
Rebecca Chew ◽  
Julius B Lucks
Keyword(s):  
Gene Expression ◽  
Synthetic Biology ◽  
Antisense Rna ◽  
Promoter Strength ◽  
Transcriptional Repressors ◽  
Transcriptional Terminator ◽  
Broad Array ◽  
Rna Stabilization ◽  
Fold Activation

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.

scholarly journals Engineered systems of inducible anti-repressors for the next generation of biological programming

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Thomas M. Groseclose ◽  
Ronald E. Rondon ◽  
Zachary D. Herde ◽  
Carlos A. Aldrete ◽  
Corey J. Wilson
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Synthetic Biology ◽  
Great Success ◽  
Engineering Systems ◽  
Transcriptional Repressors ◽  
Genetic Circuits ◽  
Naturally Occurring ◽  
Logical Control ◽  
Engineered Systems

Abstract Traditionally engineered genetic circuits have almost exclusively used naturally occurring transcriptional repressors. Recently, non-natural transcription factors (repressors) have been engineered and employed in synthetic biology with great success. However, transcriptional anti-repressors have largely been absent with regard to the regulation of genes in engineered genetic circuits. Here, we present a workflow for engineering systems of non-natural anti-repressors. In this study, we create 41 inducible anti-repressors. This collection of transcription factors respond to two distinct ligands, fructose (anti-FruR) or D-ribose (anti-RbsR); and were complemented by 14 additional engineered anti-repressors that respond to the ligand isopropyl β-d-1-thiogalactopyranoside (anti-LacI). In turn, we use this collection of anti-repressors and complementary genetic architectures to confer logical control over gene expression. Here, we achieved all NOT oriented logical controls (i.e., NOT, NOR, NAND, and XNOR). The engineered transcription factors and corresponding series, parallel, and series-parallel genetic architectures represent a nascent anti-repressor based transcriptional programming structure.

Synthetic biology approaches in regulation of targeted gene expression

2021 ◽  
Vol 63 ◽  
pp. 102036
Author(s):  
Debao Huang ◽  
Pawel Z. Kosentka ◽  
Wusheng Liu
Keyword(s):  
Gene Expression ◽  
Synthetic Biology ◽  
Targeted Gene Expression

scholarly journals Improving cell-free glycoprotein synthesis by characterizing and enriching native membrane vesicles

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jasmine M. Hershewe ◽  
Katherine F. Warfel ◽  
Shaelyn M. Iyer ◽  
Justin A. Peruzzi ◽  
Claretta J. Sullivan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Synthetic Biology ◽  
Membrane Protein ◽  
Membrane Vesicles ◽  
Processing Methods ◽  
Glycoprotein Synthesis ◽  
On Demand ◽  
Free Gene ◽  
Membrane Bound

AbstractCell-free gene expression (CFE) systems from crude cellular extracts have attracted much attention for biomanufacturing and synthetic biology. However, activating membrane-dependent functionality of cell-derived vesicles in bacterial CFE systems has been limited. Here, we address this limitation by characterizing native membrane vesicles in Escherichia coli-based CFE extracts and describing methods to enrich vesicles with heterologous, membrane-bound machinery. As a model, we focus on bacterial glycoengineering. We first use multiple, orthogonal techniques to characterize vesicles and show how extract processing methods can be used to increase concentrations of membrane vesicles in CFE systems. Then, we show that extracts enriched in vesicle number also display enhanced concentrations of heterologous membrane protein cargo. Finally, we apply our methods to enrich membrane-bound oligosaccharyltransferases and lipid-linked oligosaccharides for improving cell-free N-linked and O-linked glycoprotein synthesis. We anticipate that these methods will facilitate on-demand glycoprotein production and enable new CFE systems with membrane-associated activities.

scholarly journals Gene Expression Space Shapes the Bioprocess Trade-Offs among Titer, Yield and Productivity

2021 ◽  
Vol 11 (13) ◽  
pp. 5859
Author(s):  
Fernando N. Santos-Navarro ◽  
Yadira Boada ◽  
Alejandro Vignoni ◽  
Jesús Picó
Keyword(s):  
Gene Expression ◽  
Gene Transcription ◽  
Performance Metrics ◽  
Cell Mass ◽  
Gene Copy ◽  
Substrate Uptake ◽  
Promoter Strength ◽  
Expression Levels ◽  
Trade Offs ◽  
Wide Range

Optimal gene expression is central for the development of both bacterial expression systems for heterologous protein production, and microbial cell factories for industrial metabolite production. Our goal is to fulfill industry-level overproduction demands optimally, as measured by the following key performance metrics: titer, productivity rate, and yield (TRY). Here we use a multiscale model incorporating the dynamics of (i) the cell population in the bioreactor, (ii) the substrate uptake and (iii) the interaction between the cell host and expression of the protein of interest. Our model predicts cell growth rate and cell mass distribution between enzymes of interest and host enzymes as a function of substrate uptake and the following main lab-accessible gene expression-related characteristics: promoter strength, gene copy number and ribosome binding site strength. We evaluated the differential roles of gene transcription and translation in shaping TRY trade-offs for a wide range of expression levels and the sensitivity of the TRY space to variations in substrate availability. Our results show that, at low expression levels, gene transcription mainly defined TRY, and gene translation had a limited effect; whereas, at high expression levels, TRY depended on the product of both, in agreement with experiments in the literature.

scholarly journals Refactoring of a synthetic raspberry ketone pathway with EcoFlex

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Simon J. Moore ◽  
Yonek B. Hleba ◽  
Sarah Bischoff ◽  
David Bell ◽  
Karen M. Polizzi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Synthetic Biology ◽  
Combinatorial Libraries ◽  
Value Added ◽  
Microtiter Plate ◽  
Fine Tuning ◽  
Golden Gate ◽  
E Coli ◽  
Fine Chemical ◽  
Raspberry Ketone

Abstract Background  A key focus of synthetic biology is to develop microbial or cell-free based biobased routes to value-added chemicals such as fragrances. Originally, we developed the EcoFlex system, a Golden Gate toolkit, to study genes/pathways flexibly using Escherichia coli heterologous expression. In this current work, we sought to use EcoFlex to optimise a synthetic raspberry ketone biosynthetic pathway. Raspberry ketone is a high-value (~ £20,000 kg−1) fine chemical farmed from raspberry (Rubeus rubrum) fruit. Results  By applying a synthetic biology led design-build-test-learn cycle approach, we refactor the raspberry ketone pathway from a low level of productivity (0.2 mg/L), to achieve a 65-fold (12.9 mg/L) improvement in production. We perform this optimisation at the prototype level (using microtiter plate cultures) with E. coli DH10β, as a routine cloning host. The use of E. coli DH10β facilitates the Golden Gate cloning process for the screening of combinatorial libraries. In addition, we also newly establish a novel colour-based phenotypic screen to identify productive clones quickly from solid/liquid culture. Conclusions  Our findings provide a stable raspberry ketone pathway that relies upon a natural feedstock (L-tyrosine) and uses only constitutive promoters to control gene expression. In conclusion we demonstrate the capability of EcoFlex for fine-tuning a model fine chemical pathway and provide a range of newly characterised promoter tools gene expression in E. coli.

scholarly journals Detection Method for Multiple Gene Expression in Single Early Bovine Embryo (Antisense RNA-RT-PCR).

1996 ◽  
Vol 13 (2) ◽  
pp. 125-129
Author(s):  
Hiroya Kadokawa ◽  
Seizo Hamano ◽  
Ryuji Itoh ◽  
Hitomi Takahashi ◽  
Yutaka Yamada ◽  
...  
Keyword(s):  
Gene Expression ◽  
Antisense Rna ◽  
Detection Method ◽  
Bovine Embryo ◽  
Rt Pcr ◽  
Multiple Gene

scholarly journals Cell-free genetic devices confer autonomic and adaptive properties to hydrogels

2019 ◽  
Author(s):  
Colette J. Whitfield ◽  
Alice M. Banks ◽  
Gema Dura ◽  
John Love ◽  
Jonathan E. Fieldsend ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Information Processing ◽  
Synthetic Biology ◽  
Smart Materials ◽  
Living Organism ◽  
Chemical Diversity ◽  
Biological Information ◽  
Self Healing ◽  
Wide Range

AbstractSmart materials are able to alter one or more of their properties in response to defined stimuli. Our ability to design and create such materials, however, does not match the diversity and specificity of responses seen within the biological domain. We propose that relocation of molecular phenomena from living cells into hydrogels can be used to confer smart functionality to materials. We establish that cell-free protein synthesis can be conducted in agarose hydrogels, that gene expression occurs throughout the material and that co-expression of genes is possible. We demonstrate that gene expression can be controlled transcriptionally (using in gel gene interactions) and translationally in response to small molecule and nucleic acid triggers. We use this system to design and build a genetic device that can alter the structural property of its chassis material in response to exogenous stimuli. Importantly, we establish that a wide range of hydrogels are appropriate chassis for cell-free synthetic biology, meaning a designer may alter both the genetic and hydrogel components according to the requirements of a given application. We probe the relationship between the physical structure of the gel and in gel protein synthesis and reveal that the material itself may act as a macromolecular crowder enhancing protein synthesis. Given the extensive range of genetically encoded information processing networks in the living kingdom and the structural and chemical diversity of hydrogels, this work establishes a model by which cell-free synthetic biology can be used to create autonomic and adaptive materials.Significance statementSmart materials have the ability to change one or more of their properties (e.g. structure, shape or function) in response to specific triggers. They have applications ranging from light-sensitive sunglasses and drug delivery systems to shape-memory alloys and self-healing coatings. The ability to programme such materials, however, is basic compared to the ability of a living organism to observe, understand and respond to its environment. Here we demonstrate the relocation of biological information processing systems from cells to materials. We achieved this by operating small, programmable genetic devices outside the confines of a living cell and inside hydrogel matrices. These results establish a method for developing materials functionally enhanced with molecular machinery from biological systems.

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