LactoSpanks: A Collection of IPTG Inducible Promoters for the Commensal Lactic Acid Bacteria Lactobacillus gasseri.

Lactic acid bacteria (LAB) are important for many biotechnological applications such as bioproduction and engineered probiotics for therapy. Inducible promoters are key gene expression control elements, yet those available in LAB are mainly based on bacteriocin systems and have many drawbacks, including large gene clusters, costly inducer peptides, and little portability to in vivo settings. Using Lactobacillus gasseri, a model commensal bacteria from the human gut, we report the engineering of synthetic LactoSpanks promoters (Pls), a collection of variable strength inducible promoters controlled by the LacI repressor from E. coli and induced by isopropyl ß-d-1-thiogalactopyranoside (IPTG). We first show that the Phyper-spank promoter from Bacillus subtilis is functional in L. gasseri, albeit with substantial leakage. We then construct and screen a semirational library of Phyper-spank variants to select a set of four IPTG-inducible promoters that span a range of expression levels and exhibit reduced leakages and operational dynamic ranges (from ca. 9 to 28 fold-change). With their low genetic footprint and simplicity of use, LactoSpanks will support many applications in L. gasseri, and potentially other lactic acid and Gram-positive bacteria.

An optimized electrotransformation protocol for Lactobacillus jensenii.

Engineered bacteria are promising candidates for in situ detection and treatment of diseases. The female uro-genital tract presents several pathologies, such as sexually transmitted diseases or genital cancer, that could benefit from such technology. While bacteria from the gut microbiome are increasingly engineered, the use of chassis isolated from the female uro-genital resident flora has been limited. A major hurdle to implement the experimental throughput required for efficient engineering in these non-model bacteria is their low transformability. Here we report an optimized electrotransformation protocol for Lactobacillus jensenii, one the most widespread species across vaginal microflora. Starting from classical conditions, we optimized buffers, electric field parameters, cuvette type and DNA quantity to achieve an 80-fold improvement in transformation efficiency, with up to 3.5·103 CFUs/µg of DNA in L. jensenii ATCC 25258. We also identify several plasmids that are maintained and support reporter gene expression in L. jensenii. Finally, we demonstrate that our protocol provides increased transformability in three independent clinical isolates of L. jensenii. This work will facilitate the genetic engineering of L. jensenii and enable its use for addressing challenges in gynecological healthcare.

Computational Methods for the Design of Recombinase Logic Circuits with Adaptable Circuit Specifications.

Synthetic biology aims at engineering new biological systems and functions that can be used to provide new technological solutions to worldwide challenges. Detection and processing of multiple signals are crucial for many synthetic biology applications. A variety of logic circuits operating in living cells have been implemented. One particular class of logic circuits uses site-specific recombinases mediating specific DNA inversion or excision. Recombinase logic offers many interesting features, including single-layer architectures, memory, low metabolic footprint, and portability in many species. Here, we present two automated design strategies for both Boolean and history-dependent recombinase-based logic circuits. One approach is based on the distribution of computation within multicellular consortia, and the other is a single-cell design. Both are complementary and adapted for non-expert users via a web design interface, called CALIN and RECOMBINATOR, for multicellular and single-cell design strategies, respectively. In this book chapter, we are guiding the reader step by step through recombinase logic circuit design, from selecting the design strategy fitting to their final system of interest to obtaining the final design using one of our design web interfaces.

A rapid and standardized workflow for functional assessment of bacterial biosensors in fecal samples.

Gut metabolites are pivotal mediators of host-microbiome interactions and provide an important window on human physiology and disease. However, current methods to monitor gut metabolites rely on heavy and expensive technologies such as liquid chromatography-mass spectrometry (LC-MS). In that context, robust, fast, field-deployable, and cost-effective strategies for monitoring fecal metabolites would support large-scale functional studies and routine monitoring of metabolites biomarkers associated with pathological conditions. Living cells are an attractive option to engineer biosensors due to their ability to detect and process many environmental signals and their self-replicating nature. Here we optimized a workflow for feces processing that supports metabolite detection using bacterial biosensors. We show that simple centrifugation and filtration steps remove host microbes and support reproducible preparation of a physiological-derived media retaining important characteristics of human feces, such as matrix effects and endogenous metabolites. We measure the performance of bacterial biosensors for benzoate, lactate, anhydrotetracycline, and bile acids, and find that they are highly sensitive to fecal matrices. However, encapsulating the bacteria in hydrogel helps reduce this inhibitory effect. Sensitivity to matrix effects is biosensor-dependent but also varies between individuals, highlighting the need for case-by-case optimization for biosensors' operation in feces. Finally, by detecting endogenous bile acids, we demonstrate that bacterial biosensors could be used for future metabolite monitoring in feces. This work lays the foundation for the optimization and use of bacterial biosensors for fecal metabolites monitoring. In the future, our method could also allow rapid pre-prototyping of engineered bacteria designed to operate in the gut, with applications to in situ diagnostics and therapeutics.

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.

Cell-Free Protein Synthesis from Exonuclease-Deficient Cellular Extracts Utilizing Linear DNA Templates.

Cell-free protein synthesis (CFPS) has recently become very popular in the field of synthetic biology due to its numerous advantages. Using linear DNA templates for CFPS will further enable the technology to reach its full potential, decreasing the experimental time by eliminating the steps of cloning, transformation, and plasmid extraction. Linear DNA can be rapidly and easily amplified by PCR to obtain high concentrations of the template, avoiding potential in vivo expression toxicity. However, linear DNA templates are rapidly degraded by exonucleases that are naturally present in the cell extracts. There are several strategies that have been proposed to tackle this problem, such as adding nuclease inhibitors or chemical modification of linear DNA ends for protection. All these strategies cost extra time and resources and are yet to obtain near-plasmid levels of protein expression. A detailed protocol for an alternative strategy is presented here for using linear DNA templates for CFPS. By using cell extracts from exonuclease-deficient knockout cells, linear DNA templates remain intact without requiring any end-modifications. We present the preparation steps of cell lysate from Escherichia coli BL21 Rosetta2 ΔrecBCD strain by sonication lysis and buffer calibration for Mg-glutamate (Mg-glu) and K-glutamate (K-glu) specifically for linear DNA. This method is able to achieve protein expression levels comparable to that from plasmid DNA in E. coli CFPS.

Evaluating and mitigating clinical samples matrix effects on TX-TL cell-free performance.

Cell-free biosensors are promising tools for medical diagnostics, yet their performance can be affected by matrix effects arising from the sample itself or from external components. Here we systematically evaluate the performance and robustness of cell-free systems in serum, plasma, urine, and saliva using two reporter systems, sfGFP and luciferase. In all cases, clinical samples have a strong inhibitory effect. Of the different inhibitors, only RNase inhibitor mitigated matrix effects. However, we found that the recovery potential of RNase inhibitor was partially muted by interference from glycerol contained in the commercial buffer. We solved this issue by designing a strain producing an RNase inhibitor protein requiring no additional step in extract preparation. Furthermore, our new extract yielded higher reporter levels than previous conditions and tempered interpatient variability associated with matrix effects. This systematic evaluation and improvements of cell-free system robustness unified across many types of clinical samples is a significant step towards developing cell-free diagnostics for a wide range of conditions.

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.

Engineered l-Lactate Responding Promoter System Operating in Glucose-Rich and Anoxic Environments.

Bacteria equipped with genetically encoded lactate biosensors are promising tools for biopharmaceutical production, diagnostics, and cellular therapies. However, many applications involve glucose-rich and anoxic environments, in which current whole-cell lactate biosensors show low performance. Here we engineer an optimized, synthetic lactate biosensor system by repurposing the natural LldPRD promoter regulated by the LldR transcriptional regulator. We removed glucose catabolite and anoxic repression by designing a hybrid promoter, containing LldR operators and tuned both regulator and reporter gene expressions to optimize biosensor signal-to-noise ratio. The resulting lactate biosensor, termed ALPaGA (A Lactate Promoter Operating in Glucose and Anoxia), can operate in glucose-rich, aerobic and anoxic conditions. We show that ALPaGA works reliably in the probiotic chassisEscherichia coliNissle 1917 and can detect endogenous l-lactate produced by 3D tumor spheroids with an improved dynamic range. In the future, the ALPaGA system could be used to monitor bioproduction processes and improve the specificity of engineered bacterial cancer therapies by restricting their activity to the lactate-rich microenvironment of solid tumors.

Programmable receptors enable bacterial biosensors to detect pathological biomarkers in clinical samples.

Bacterial biosensors, or bactosensors, are promising agents for medical and environmental diagnostics. However, the lack of scalable frameworks to systematically program ligand detection limits their applications. Here we show how novel, clinically relevant sensing modalities can be introduced into bactosensors in a modular fashion. To do so, we have leveraged a synthetic receptor platform, termed EMeRALD (Engineered Modularized Receptors Activated via Ligand-induced Dimerization) which supports the modular assembly of sensing modules onto a high-performance, generic signaling scaffold controlling gene expression in E. coli. We apply EMeRALD to detect bile salts, a biomarker of liver dysfunction, by repurposing sensing modules from enteropathogenic Vibrio species. We improve the sensitivity and lower the limit-of-detection of the sensing module by directed evolution. We then engineer a colorimetric bactosensor detecting pathological bile salt levels in serum from patients having undergone liver transplant, providing an output detectable by the naked-eye. The EMeRALD technology enables functional exploration of natural sensing modules and rapid engineering of synthetic receptors for diagnostics, environmental monitoring, and control of therapeutic microbes.

Computational Methods for the Design of Recombinase Logic Circuits.

Synthetic biology aims at engineering new biological systems and functions that can be used to provide new technological solutions to worldwide challenges. Detection and processing of multiple signals are crucial for many synthetic biology applications. A variety of logic circuits operating in living cells have been implemented. One particular class of logic circuits uses site-specific recombinases mediating specific DNA inversion or excision. Recombinase logic offers many interesting features, including single-layer architectures, memory, low metabolic footprint, and portability in many species. Here, we present two automated design strategies for recombinase-based logic circuits, one based on the distribution of computation within a multicellular consortia and the other one being a single-cell design. The two design strategies are complementary and are both adapted for none expert as a design web-interface exits for each strategy, the CALIN and RECOMBINATOR web-interface for respectively the multicellular and single-cell design strategy. In this book chapter, we are guiding the reader step by step through recombinase-logic circuit design from selecting the design strategy fitting to his/her final system of interest to obtaining the final design using one of our design web-interface.

Rational programming of history-dependent logic in cellular populations.

Genetic programs operating in a history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities. Here we implement robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on standardized recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular, do not require cell-cell communication channels, and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed automated workflows that researchers can use to streamline program design and optimization. We anticipate that the history-dependent programs presented here will support many applications using cellular populations for material engineering, biomanufacturing and healthcare.

Synthetic receptors to understand and control cellular functions.

Cellular functions are controlled by sophisticated signal transduction pathways triggered by receptors responding to myriad environmental stimuli. With the rise of synthetic biology, we can now engineer artificial receptors enabling real-time interrogation and manipulation of cellular signaling, and providing new clues about the design principles of natural sensing systems. In this review, we describe the main classes of synthetic receptors engineered to date, their applications, and highlight recent developments that might improve synthetic receptor design in the future.

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.

Plug-and-play metabolic transducers expand the chemical detection space of cell-free biosensors.

Cell-free transcription-translation systems have great potential for biosensing, yet the range of detectable chemicals is limited. Here we provide a workflow to expand the range of molecules detectable by cell-free biosensors through combining synthetic metabolic cascades with transcription factor-based networks. These hybrid cell-free biosensors have a fast response time, strong signal response, and a high dynamic range. In addition, they are capable of functioning in a variety of complex media, including commercial beverages and human urine, in which they can be used to detect clinically relevant concentrations of small molecules. This work provides a foundation to engineer modular cell-free biosensors tailored for many applications.

Structural basis for chemically-induced homodimerization of a single domain antibody.

Chemically-induced dimerization (CID) systems are essential tools to interrogate and control biological systems. AcVHH is a single domain antibody homo-dimerizing upon caffeine binding. AcVHH has a strong potential for clinical applications through caffeine-mediated in vivo control of therapeutic gene networks. Here we provide the structural basis for caffeine-induced homo-dimerization of acVHH.

Hierarchical composition of reliable recombinase logic devices.

A major goal of synthetic biology is to reprogram living organisms to solve pressing challenges in manufacturing, environmental remediation, and healthcare. Recombinase devices can efficiently encode complex logic in many species, yet current designs are performed on a case-by-case basis, limiting their scalability and requiring time-consuming optimization. Here we provide a systematic framework for engineering reliable recombinase logic devices by hierarchical composition of well-characterized, optimized recombinase switches. We apply this framework to build a recombinase logic device family supporting up to 4-input Boolean logic within a multicellular system. This work enables straightforward implementation of multicellular recombinase logic and will support the predictable engineering of several classes of recombinase devices to reliably control cellular behavior.

An Engineered Device for Indoleacetic Acid Production under Quorum Sensing Signals Enables Cupriavidus pinatubonensis JMP134 To Stimulate Plant Growth.

The environmental effects of chemical fertilizers and pesticides have encouraged the quest for new strategies to increase crop productivity with minimal impacts on the natural medium. Plant growth promoting rhizobacteria (PGPR) can contribute to this endeavor by improving fitness through better nutrition acquisition and stress tolerance. Using the neutral (non PGPR) rhizobacterium Cupriavidus pinatubonensis JMP134 as the host, we engineered a regulatory forward loop that triggered the synthesis of the phytohormone indole-3-acetic acid (IAA) in a manner dependent on quorum sensing (QS) signals. Implementation of the device in JMP134 yielded synthesis of IAA in an autoregulated manner, improving the growth of the roots of inoculated Arabidopsis thaliana. These results not only demonstrated the value of the designed genetic module, but also validated C. pinatubonensis JMP134 as a suitable vehicle for agricultural applications, as it is amenable to genetic manipulations.

An Automated Design Framework for Multicellular Recombinase Logic.

Tools to systematically reprogram cellular behavior are crucial to address pressing challenges in manufacturing, environment, or healthcare. Recombinases can very efficiently encode Boolean and history-dependent logic in many species, yet current designs are performed on a case-by-case basis, limiting their scalability and requiring time-consuming optimization. Here we present an automated workflow for designing recombinase logic devices executing Boolean functions. Our theoretical framework uses a reduced library of computational devices distributed into different cellular subpopulations, which are then composed in various manners to implement all desired logic functions at the multicellular level. Our design platform called CALIN (Composable Asynchronous Logic using Integrase Networks) is broadly accessible via a web server, taking truth tables as inputs and providing corresponding DNA designs and sequences as outputs (available at http://synbio.cbs.cnrs.fr/calin ). We anticipate that this automated design workflow will streamline the implementation of Boolean functions in many organisms and for various applications.

A Modular Receptor Platform To Expand the Sensing Repertoire of Bacteria.

Engineered bacteria promise to revolutionize diagnostics and therapeutics, yet many applications are precluded by the limited number of detectable signals. Here we present a general framework to engineer synthetic receptors enabling bacterial cells to respond to novel ligands. These receptors are activated via ligand-induced dimerization of a single-domain antibody fused to monomeric DNA-binding domains (split-DBDs). Using E. coli as a model system, we engineer both transmembrane and cytosolic receptors using a VHH for ligand detection and demonstrate the scalability of our platform by using the DBDs of two different transcriptional regulators. We provide a method to optimize receptor behavior by finely tuning protein expression levels and optimizing interdomain linker regions. Finally, we show that these receptors can be connected to downstream synthetic gene circuits for further signal processing. The general nature of the split-DBD principle and the versatility of antibody-based detection should support the deployment of these receptors into various hosts to detect ligands for which no receptor is found in nature.