PeroxiHUB: A Modular Cell-Free Biosensing Platform Using H2O2 as Signal Integrator.

Cell-free systems have great potential for delivering robust, inexpensive, and field-deployable biosensors. Many cell-free biosensors rely on transcription factors responding to small molecules, but their discovery and implementation still remain challenging. Here we report the engineering of PeroxiHUB, an optimized H2O2-centered sensing platform supporting cell-free detection of different metabolites. H2O2 is a central metabolite and a byproduct of numerous enzymatic reactions. PeroxiHUB uses enzymatic transducers to convert metabolites of interest into H2O2, enabling rapid reprogramming of sensor specificity using alternative transducers. We first screen several transcription factors and optimize OxyR for the transcriptional response to H2O2 in a cell-free system, highlighting the need for preincubation steps to obtain suitable signal-to-noise ratios. We then demonstrate modular detection of metabolites of clinical interest─lactate, sarcosine, and choline─using different transducers mined via a custom retrosynthesis workflow publicly available on the SynBioCAD Galaxy portal. We find that expressing the transducer during the preincubation step is crucial for optimal sensor operation. We then show that different reporters can be connected to PeroxiHUB, providing high adaptability for various applications. Finally, we demonstrate that a peroxiHUB lactate biosensor can detect endogenous levels of this metabolite in clinical samples. Given the wide range of enzymatic reactions producing H2O2, the PeroxiHUB platform will support cell-free detection of a large number of metabolites in a modular and scalable fashion.

Toehold switch based biosensors for sensing the highly trafficked rosewood Dalbergia maritima.

Nucleic acid sensing is a 3 decades old but still challenging area of application for different biological sub-domains, from pathogen detection to single cell transcriptomics analysis. The many applications of nucleic acid detection and identification are mostly carried out by PCR techniques, sequencing, and their derivatives used at large scale. However, these methods' limitations on speed, cost, complexity and specificity have motivated the development of innovative detection methods among which nucleic acid biosensing technologies seem promising. Toehold switches are a particular class of RNA sensing devices relying on a conformational switch of secondary structure induced by the pairing of the detected trigger RNA with a de novo designed synthetic sensing mRNA molecule. Here we describe a streamlined methodology enabling the development of such a sensor for the RNA-mediated detection of an endangered plant species in a cell-free reaction system. We applied this methodology to help identify the rosewood Dalbergia maritima, a highly trafficked wood, whose protection is limited by the capacity of the authorities to distinguish protected logs from other unprotected but related species. The streamlined pipeline presented in this work is a versatile framework enabling cheap and rapid development of new sensors for custom RNA detection.

Differentially Optimized Cell-Free Buffer Enables Robust Expression from Unprotected Linear DNA in Exonuclease-Deficient Extracts.

The use of linear DNA templates in cell-free systems promises to accelerate the prototyping and engineering of synthetic gene circuits. A key challenge is that linear templates are rapidly degraded by exonucleases present in cell extracts. Current approaches tackle the problem by adding exonuclease inhibitors and DNA-binding proteins to protect the linear DNA, requiring additional time- and resource-intensive steps. Here, we delete the recBCD exonuclease gene cluster from the Escherichia coli BL21 genome. We show that the resulting cell-free systems, with buffers optimized specifically for linear DNA, enable near-plasmid levels of expression from σ70 promoters in linear DNA templates without employing additional protection strategies. When using linear or plasmid DNA templates at the buffer calibration step, the optimal potassium glutamate concentrations obtained when using linear DNA were consistently lower than those obtained when using plasmid DNA for the same extract. We demonstrate the robustness of the exonuclease deficient extracts across seven different batches and a wide range of experimental conditions across two different laboratories. Finally, we illustrate the use of the ΔrecBCD extracts for two applications: toehold switch characterization and enzyme screening. Our work provides a simple, efficient, and cost-effective solution for using linear DNA templates in cell-free systems and highlights the importance of specifically tailoring buffer composition for the final experimental setup. Our data also suggest that similar exonuclease deletion strategies can be applied to other species suitable for cell-free synthetic biology.

Cell-Free Biosensors and AI Integration.

Cell-free biosensors hold a great potential as alternatives for traditional analytical chemistry methods providing low-cost low-resource measurement of specific chemicals. However, their large-scale use is limited by the complexity of their development.In this chapter, we present a standard methodology based on computer-aided design (CAD ) tools that enables fast development of new cell-free biosensors based on target molecule information transduction and reporting through metabolic and genetic layers, respectively. Such systems can then be repurposed to represent complex computational problems, allowing defined multiplex sensing of various inputs and integration of artificial intelligence in synthetic biological systems.

Optimising protein synthesis in cell-free systems, a review.

Over the last decades, cell-free systems have been extensively used for in vitro protein expression. A vast range of protocols and cellular sources varying from prokaryotes and eukaryotes are now available for cell-free technology. However, exploiting the maximum capacity of cell free systems is not achieved by using traditional protocols. Here, what are the strategies and choices one can apply to optimise cell-free protein synthesis have been reviewed. These strategies provide robust and informative improvements regarding transcription, translation and protein folding which can later be used for the establishment of individual best cell-free reactions per lysate batch.

Large scale active-learning-guided exploration for in vitro protein production optimization.

Lysate-based cell-free systems have become a major platform to study gene expression but batch-to-batch variation makes protein production difficult to predict. Here we describe an active learning approach to explore a combinatorial space of ~4,000,000 cell-free buffer compositions, maximizing protein production and identifying critical parameters involved in cell-free productivity. We also provide a one-step-method to achieve high quality predictions for protein production using minimal experimental effort regardless of the lysate quality.

Efficient expression vectors and host strain for the production of recombinant proteins by Yarrowia lipolytica in process conditions.

BACKGROUND: The oleaginous yeast Yarrowia lipolytica is increasingly used as an alternative cell factory for the production of recombinant proteins. Recently, regulated promoters from genes EYK1 and EYD1, encoding an erythrulose kinase and an erythritol dehydrogenase, respectively, have been identified and characterized in this yeast. Hybrid promoters up-regulated by polyols such as erythritol and erythrulose have been developed based on tandem copies of upstream activating sequences from EYK1 (UAS1EYK1) and XPR2 (encoding extracellular protease, UAS1XPR2) promoters. RESULTS: The strength of native (pEYD1) and engineered promoters (pEYK1-3AB and pHU8EYK) was compared using the extracellular lipase CalB from Candida antarctica as a model protein and a novel dedicated host strain. This latter is engineered in polyol metabolism and allows targeted chromosomal integration. In process conditions, engineered promoters pEYK1-3AB and pHU8EYK yielded 2.8 and 2.5-fold higher protein productivity, respectively, as compared to the reference pTEF promoter. We also demonstrated the possibility of multicopy integration in the newly developed host strain. In batch bioreactor, the CalB multi-copy strain RIY406 led to a 1.6 fold increased lipase productivity (45,125 U mL-1) within 24 h as compared to the mono-copy strain. CONCLUSIONS: The expression system described herein appears promising for recombinant extracellular protein production in Y. lipolytica.

Metabolic perceptrons for neural computing in biological systems.

Synthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a different approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model fitted on experimental data, we finally implement two four-input perceptrons for desired binary classification of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.

A modular Golden Gate toolkit for Yarrowia lipolytica synthetic biology.

The oleaginous yeast Yarrowia lipolytica is an established host for the bio-based production of valuable compounds and an organism for which many genetic tools have been developed. However, to properly engineer Y. lipolytica and take full advantage of its potential, we need efficient, versatile, standardized and modular cloning tools. Here, we present a new modular Golden Gate toolkit for the one-step assembly of three transcription units that includes a selective marker and sequences for genome integration. Perfectly suited to a combinatorial approach, it contains nine different validated promoters, including inducible promoters, which allows expression to be fine-tuned. Moreover, this toolbox incorporates six different markers (three auxotrophic markers, two antibiotic-resistance markers and one metabolic marker), which allows the fast sequential construction and transformation of multiple elements. In total, the toolbox contains 64 bricks, and it has been validated and characterized using three different fluorescent reporter proteins. Additionally, it was successfully used to assemble and integrate a three-gene pathway allowing xylose utilization by Y. lipolytica. This toolbox provides a powerful new tool for rapidly engineering Y. lipolytica strains and is available to the community through Addgene.

Selection of Heterologous Protein-Producing Strains in Yarrowia lipolytica.

Yarrowia lipolytica has emerged as an alternative expression system for heterologous protein production and enzyme evolution. Several different expression systems dedicated for this species have been developed, ranging from the simple cloning of expression vectors to recently developed high-throughput methodologies using efficient cloning and assembly such as Gateway and Golden Gate strategies. The latter strategies, due to their modular character, enable multiple vector construction and the construction of expression cassettes containing different genes or a gene under different promoters of various strengths.Here, we present the Golden Gate cloning strategy for the construction of multiple expression cassettes, the transformation into Y. lipolytica, and the selection of efficient enzyme-producing strains using an insect alpha-amylase as a reporter detected via a thermal cycler-based microassay.

Engineering the architecture of erythritol-inducible promoters for regulated and enhanced gene expression in Yarrowia lipolytica.

The non-conventional model yeast Yarrowia lipolytica is of increasing interest as a cell factory for producing recombinant proteins or biomolecules with biotechnological or pharmaceutical applications. To further develop the yeast's efficiency and construct inducible promoters, it is crucial to better understand and engineer promoter architecture. Four conserved cis-regulatory modules (CRMs) were identified via phylogenetic footprinting within the promoter regions of EYD1 and EYK1, two genes that have recently been shown to be involved in erythritol catabolism. Using CRM mutagenesis and hybrid promoter construction, we identified four upstream activation sequences (UASs) that are involved in promoter induction by erythritol. Using RedStarII fluorescence as a reporter, the strength of the promoters and the degree of erythritol-based inducibility were determined in two genetic backgrounds: the EYK1 wild type and the eyk1Δ mutant. We successfully developed inducible promoters with variable strengths, which ranged from 0.1 SFU/h to 457.5 SFU/h. Erythritol-based induction increased 2.2 to 32.3 fold in the EYK1 + wild type and 2.9 to 896.1 fold in the eyk1Δ mutant. This set of erythritol-inducible hybrid promoters could allow the modulation and fine-tuning of gene expression levels. These promoters have direct applications in protein production, metabolic engineering and synthetic biology.