bioRxiv Science⌕ Search

bioRxiv · 10.1101/285866

Marionette: E. coli containing 12 highly-optimized small molecule sensors

Abstract

Cellular processes are carried out by many interacting genes and their study and optimization requires multiple levers by which they can be independently controlled. The most common method is via a genetically-encoded sensor that responds to a small molecule (an \"inducible system\"). However, these sensors are often suboptimal, exhibiting high background expression and low dynamic range. Further, using multiple sensors in one cell is limited by cross-talk and the taxing of cellular resources. Here, we have developed a directed evolution strategy to simultaneously select for less background, high dynamic range, increased sensitivity, and low crosstalk. Libraries of the regulatory protein and output promoter are built based on random and rationally-guided mutations. This is applied to generate a set of 12 high-performance sensors, which exhibit >100-fold induction with low background and cross-reactivity. These are combined to build a single \"sensor array\" and inserted into the genomes of E. coli MG1655 (wild-type), DH10B (cloning), and BL21 (protein expression). These \"Marionette\" strains allow for the independent control of gene expression using 2,4-diacetylphophloroglucinol (DAPG), cuminic acid (Cuma), 3-oxohexanoyl-homoserine lactone (OC6), vanillic acid (Van), isopropyl {beta}-D-1-thiogalactopyranoside (IPTG), anhydrotetracycline (aTc), L-arabinose (Ara), choline chloride (Cho), naringenin (Nar), 3,4-dihydroxybenzoic acid (DHBA), sodium salicylate (Sal), and 3-hydroxytetradecanoyl-homoserine lactone (OHC14).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Meyer, A. J., Segall-Shapiro, T. H., Voigt, C. A.. 2018-03-20. Marionette: E. coli containing 12 highly-optimized small molecule sensors. https://doi.org/10.1101/285866

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Functional analysis of small-molecule and protein binding domains using monomeric streptavidin-based two-component biosensors

Protein biosensors are important analytical and diagnostic tools that convert molecular recognition into measurable activity. Most common two-component biosensors require two non-competing recognition domains, yet binding affinity and specificity alone do not reliably predict their compatibility with the rest of the biosensor. We report a modular platform that exploits monomeric streptavidin (mSA2) as a surrogate recognition domain, enabling rapid functional evaluation of candidate binders in the context of biosensor scaffold without requiring a second ligand-specific binding protein. We established a chromatography-free protocol for recovering functional mSA2-based biosensor components from Escherichia coli. Using biotinylated small molecules methotrexate and vitamin D3, as well as heart failure protein biomarkers galectin-3 and S100A7 we demonstrate ligand-dependent reporter biosensor activation. The developed platform provides a scalable approach for rapid binder evaluation and biosensor prototyping, streamlining biosensor development using binding domains generated by directed evolution or computational protein design.

synthetic biology↗

Developing synthetic auxin-based trans-kingdom signaling

Synthetic trans-kingdom signaling systems with tunable transduction properties provide a unique avenue to explore how communication between organisms coordinate behaviors without the confounding complexity of natural systems. However, existing trans-kingdom signaling systems suffer from either toxic signal molecules, a need for rare precursors for signal generation, or transduction machinery which is either species-specific or cannot be easily tuned. This limits their capacity to be broadly applied across kingdoms and their utility as a model system to study trans-kingdom interactions. In this work we elucidate the design principles for a trans-kingdom signaling system based on the plant phytohormone, Indole 3-Acetic Acid (auxin), that overcomes these challenges. We demonstrate how auxin biosynthesis can be engineered into a model sender organism, the cyanobacteria Synechococcus elongatus PCC 7942, and how this signal can be tuned with low leak and high dynamic range. We also show these signals can be connected to gene expression using tunable synthetic auxin-responsive signaling systems across multiple kingdoms. We demonstrate that S. elongatus generated auxin signals can tune gene expression in co-cultured Saccharomyces cerevisiae via auxin-induced degradation. Additionally, we show that when the S. elongatus are associated with the roots of the model plant, Arabidopsis thaliana, the auxin they generate can control gene expression via auxin-responsive synthetic transcription factors expressed from the plants genome. Taken together, our results demonstrate the design principles for a tunable auxin-based trans-kingdom signaling system that can be broadly applied across species.

synthetic biology↗

Biosensor-guided genome-wide CRISPR screens enable cis,cis-muconic acid overproduction in yeast

Classical pathway metabolic engineering relies on enhancing strain productivity through the introduction of rationally identified genetic perturbations, which while useful, are time-consuming and miss unintuitive targets. Genome-wide CRISPR screens offer an alternative by efficiently sampling genomes, enabling the engineering of novel phenotypes, and are further enhanced when combined with high-throughput strain interrogation methods. Here, using Saccharomyces cerevisiae, we engineered small molecule biosensors into population enrichment tools using zeocin resistance and fluorescence as signal outputs. We then introduced the multi-functional genome-wide CRISPR (MAGIC) library that targets every gene for activation, interference, or deletion, thus creating biosensor-aided MAGIC, or senMAGIC. As a case study, we utilized senMAGIC to identify single genetic determinants that improve productivity of the nylon precursors protocatechuic and cis,cis-muconic acids (PCA and ccM). These were then randomly assembled as triple gRNA-tRNA arrays for multiplexed gene perturbations to identify combinatorial effects. Top gRNA hits were then confirmed using direct genomic integrations in senMAGIC-free production strains, resulting in identifying known as well as novel targets that increase PCA and ccM titres. Our results demonstrate senMAGIC as a robust automation-friendly whole-genome evolution tool and highlight limitations of the method, providing a roadmap for future multifunctional CRISPR screens to optimize host metabolism for efficient bioprocesses.

synthetic biology↗