Programming the Dynamic Control of Bacterial Gene Expression with a Chimeric Ligand- and Light-Based Promoter System

Dissecting the Determinants of Domain Insertion Tolerance and Allostery in Proteins

Domain insertion engineering is a promising approach to recombine the functions of evolutionarily unrelated proteins. Insertion of light-switchable receptor domains into a selected effector protein, for instance, can yield allosteric effectors with light-dependent activity. However, the parameters that determine domain insertion tolerance and allostery are poorly understood. Here, an unbiased screen is used to systematically assess the domain insertion permissibility of several evolutionary unrelated proteins. Training machine learning models on the resulting data allow to dissect features informative for domain insertion tolerance and revealed sequence conservation statistics as the strongest indicators of suitable insertion sites. Finally, extending the experimental pipeline toward the identification of switchable hybrids results in opto-chemogenetic derivatives of the transcription factor AraC that function as single-protein Boolean logic gates. The study reveals determinants of domain insertion tolerance and yielded multimodally switchable proteins with unique functional properties.

Implementing re-configurable biological computation with distributed multicellular consortia

The use of synthetic biological circuits to deal with numerous biological challenges has been proposed in several studies, but its implementation is still remote. A major problem encountered is the complexity of the cellular engineering needed to achieve complex biological circuits and the lack of general-purpose biological systems. The generation of re-programmable circuits can increase circuit flexibility and the scalability of complex cell-based computing devices. Here we present a new architecture to produce reprogrammable biological circuits that allow the development of a variety of different functions with minimal cell engineering. We demonstrate the feasibility of creating several circuits using only a small set of engineered cells, which can be externally reprogrammed to implement simple logics in response to specific inputs. In this regard, depending on the computation needs, a device composed of a number of defined cells can generate a variety of circuits without the need of further cell engineering or rearrangements. In addition, the inclusion of a memory module in the circuits strongly improved the digital response of the devices. The reprogrammability of biological circuits is an intrinsic capacity that is not provided in electronics and it may be used as a tool to solve complex biological problems.

Light-regulated gene expression in Bacteria: Fundamentals, advances, and perspectives

Numerous photoreceptors and genetic circuits emerged over the past two decades and now enable the light-dependent i.e., optogenetic, regulation of gene expression in bacteria. Prompted by light cues in the near-ultraviolet to near-infrared region of the electromagnetic spectrum, gene expression can be up- or downregulated stringently, reversibly, non-invasively, and with precision in space and time. Here, we survey the underlying principles, available options, and prominent examples of optogenetically regulated gene expression in bacteria. While transcription initiation and elongation remain most important for optogenetic intervention, other processes e.g., translation and downstream events, were also rendered light-dependent. The optogenetic control of bacterial expression predominantly employs but three fundamental strategies: light-sensitive two-component systems, oligomerization reactions, and second-messenger signaling. Certain optogenetic circuits moved beyond the proof-of-principle and stood the test of practice. They enable unprecedented applications in three major areas. First, light-dependent expression underpins novel concepts and strategies for enhanced yields in microbial production processes. Second, light-responsive bacteria can be optogenetically stimulated while residing within the bodies of animals, thus prompting the secretion of compounds that grant health benefits to the animal host. Third, optogenetics allows the generation of precisely structured, novel biomaterials. These applications jointly testify to the maturity of the optogenetic approach and serve as blueprints bound to inspire and template innovative use cases of light-regulated gene expression in bacteria. Researchers pursuing these lines can choose from an ever-growing, versatile, and efficient toolkit of optogenetic circuits.

BMSS2: A Unified Database-Driven Modeling Tool for Systematic Biomodel Selection

Modeling in synthetic biology constitutes a powerful means in our continuous search for improved performance with a rational Design-Build-Test-Learn approach. Particularly, kinetic models unravel system dynamics and enable system analysis for guiding experimental design. However, a systematic yet modular pipeline that allows one to identify the appropriate model and guide the experimental designs while tracing the entire model development and analysis is still lacking. Here, we develop BMSS2, a unified tool that streamlines and automates model selection by combining information criterion ranking with upstream and parallel analysis algorithms. These include Bayesian parameter inference, a priori and a posteriori identifiability analysis, and global sensitivity analysis. In addition, the database-driven design supports interactive model storage/retrieval to encourage reusability and facilitate automated model selection. This allows ease of model manipulation and deposition for the selection and analysis, thus enabling better utilization of models in guiding experimental design.

Reducing metabolic burden in the PACEmid evolver system by remastering high-copy phagemid vectors

Orthogonal or non-cross-reacting transcription factors are used in synthetic biology as components of genetic circuits. Brödel et al. (2016) engineered 12 such cIλ transcription factor variants using a directed evolution 'PACEmid' system. The variants operate as dual activator/repressors and expand gene circuit construction possibilities. However, the high-copy phagemid vectors carrying the cIλ variants imposed high metabolic burden upon cells. Here, the authors 'remaster' the phagemid backbones to relieve their burden substantially, exhibited by a recovery in Escherichia coli growth. The remastered phagemids' ability to function within the PACEmid evolver system is maintained, as is the cIλ transcription factors' activity within these vectors. The low-burden phagemid versions are more suitable for use in PACEmid experiments and synthetic gene circuits; the authors have, therefore, replaced the original high-burden phagemids on the Addgene repository. The authors' work emphasises the importance of understanding metabolic burden and incorporating it into design steps in future synthetic biology ventures.

Restoring circadian gene profiles in clock networks using synthetic feedback control

The circadian system—an organism’s built-in biological clock—is responsible for orchestrating biological processes to adapt to diurnal and seasonal variations. Perturbations to the circadian system (e.g., pathogen attack, sudden environmental change) often result in pathophysiological responses (e.g., jetlag in humans, stunted growth in plants, etc.) In view of this, synthetic biologists are progressively adapting the idea of employing synthetic feedback control circuits to alleviate the effects of perturbations on circadian systems. To facilitate the design of such controllers, suitable models are required. Here, we extend our recently developed model for the plant circadian clock—termed the extended S-System model—to model circadian systems across different kingdoms of life. We then use this modeling strategy to develop a design framework, based on an antithetic integral feedback (AIF) controller, to restore a gene’s circadian profile when it is subject to loss-of-function due to external perturbations. The use of the AIF controller is motivated by its recent successful experimental implementation. Our findings provide circadian biologists with a systematic and general modeling and design approach for implementing synthetic feedback control of circadian systems.

Thermogenetics: Applications come of age

Temperature is a ubiquitous physical cue that is non-invasive, penetrative and easy to apply. In the growing field of thermogenetics, through beneficial repurposing of natural thermosensing mechanisms, synthetic biology is bringing new opportunities to design and build robust temperature-sensitive (TS) sensors which forms a thermogenetic toolbox of well characterised biological parts. Recent advancements in technological platforms available have expedited the discovery of novel or de novo thermosensors which are increasingly deployed in many practical temperature-dependent biomedical, industrial and biosafety applications. In all, the review aims to convey both the exhilarating recent technological developments underlying the advancement of thermosensors and the exciting opportunities the nascent thermogenetic field holds for biomedical and biotechnology applications.

Translation complex stabilization on messenger RNA and footprint profiling to study the RNA responses and dynamics of protein biosynthesis in the cells

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5' and 3' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

Engineering Escherichia coli biofilm to increase contact surface for shikimate and L-malate production

Microbial organelles are a promising model to promote cellular functions for the production of high-value chemicals. However, the concentrations of enzymes and nanoparticles are limited by the contact surface in single Escherichia coli cells. Herein, the definition of contact surface is to improve the amylase and CdS nanoparticles concentration for enhancing the substrate starch and cofactor NADH utilization. In this study, two biofilm-based strategies were developed to improve the contact surface for the production of shikimate and L-malate. First, the contact surface of E. coli was improved by amylase self-assembly with a blue light-inducible biofilm-based SpyTag/SpyCatcher system. This system increased the glucose concentration by 20.7% and the starch-based shikimate titer to 50.96 g L-1, which showed the highest titer with starch as substrate. Then, the contact surface of E. coli was improved using a biofilm-based CdS-biohybrid system by light-driven system, which improved the NADH concentration by 83.3% and increased the NADH-dependent L-malate titer to 45.93 g L-1. Thus, the biofilm-based strategies can regulate cellular functions to increase the efficiency of microbial cell factories based on the optogenetics, light-driven, and metabolic engineering.

A Timed Off-Switch for Dynamic Control of Gene Expression in Corynebacterium Glutamicum

Dynamic control of gene expression mainly relies on inducible systems, which require supplementation of (costly) inducer molecules. In contrast, synthetic regulatory circuits, which allow the timed shutdown of gene expression, are rarely available and therefore represent highly attractive tools for metabolic engineering. To achieve this, we utilized the VanR/P vanABK * regulatory system of Corynebacterium glutamicum, which consists of the transcriptional repressor VanR and a modified promoter of the vanABK operon (P vanABK *). VanR activity is modulated by one of the phenolic compounds ferulic acid, vanillin or vanillic acid, which are co-metabolized with d-glucose. Thus, gene expression in the presence of d-glucose is turned off if one of the effector molecules is depleted from the medium. To dynamically control the expression of the aceE gene, encoding the E1 subunit of the pyruvate dehydrogenase complex that is essential for growth on d-glucose, we replaced the native promoter by vanR/P vanABK * yielding C. glutamicum ΔP aceE ::vanR-P vanABK *. The biomass yield of this strain increased linearly with the supplemented amount of effector. After consumption of the phenolic compounds growth ceased, however, C. glutamicumΔP aceE ::vanR-P vanABK * continued to utilize the residual d-glucose to produce significant amounts of pyruvate, l-alanine, and l-valine. Interestingly, equimolar concentrations of the three phenolic compounds resulted in different biomass yields; and with increasing effector concentration, the product spectrum shifted from pyruvate over l-alanine to l-valine. To further test the suitability of the VanR/P vanABK * system, we overexpressed the l-valine biosynthesis genes ilvBNCE in C. glutamicum ΔP aceE ::vanR-P vanABK *, which resulted in efficient l-valine production with a yield of about 0.36 mol l-valine per mol d-glucose. These results demonstrate that the VanR/P vanABK * system is a valuable tool to control gene expression in C. glutamicum in a timed manner by the cheap and abundant phenolic compounds ferulic acid, vanillin, and vanillic acid.

SynBiopython: an open-source software library for Synthetic Biology

Advances in hardware automation in synthetic biology laboratories are not yet fully matched by those of their software counterparts. Such automated laboratories, now commonly called biofoundries, require software solutions that would help with many specialized tasks such as batch DNA design, sample and data tracking, and data analysis, among others. Typically, many of the challenges facing biofoundries are shared, yet there is frequent wheel-reinvention where many labs develop similar software solutions in parallel. In this article, we present the first attempt at creating a standardized, open-source Python package. A number of tools will be integrated and developed that we envisage will become the obvious starting point for software development projects within biofoundries globally. Specifically, we describe the current state of available software, present usage scenarios and case studies for common problems, and finally describe plans for future development. SynBiopython is publicly available at the following address: http://synbiopython.org.

Engineering an Optogenetic CRISPRi Platform for Improved Chemical Production

Microbial synthesis of chemicals typically requires the redistribution of metabolic flux toward the synthesis of targeted products. Dynamic control is emerging as an effective approach for solving the hurdles mentioned above. As light could control the cell behavior in a spatial and temporal manner, the optogenetic-CRISPR interference (opto-CRISPRi) technique that allocates the metabolic resources according to different optical signal frequencies will enable bacteria to be controlled between the growth phase and the production stage. In this study, we applied a blue light-sensitive protein EL222 to regulate the expression of the dCpf1-mediated CRISPRi system that turns off the competitive pathways and redirects the metabolic flux toward the heterologous muconic acid synthesis in Escherichia coli. We found that the opto-CRISPRi system dynamically regulating the suppression of the central metabolism and competitive pathways could increase the muconic acid production by 130%. These results demonstrated that the opto-CRISPRi platform is an effective method for enhancing chemical synthesis with broad utilities.

Optogenetic interrogation and control of cell signaling

Signaling networks control the flow of information through biological systems and coordinate the chemical processes that constitute cellular life. Optogenetic actuators - genetically encoded proteins that undergo light-induced changes in activity or conformation - are useful tools for probing signaling networks over time and space. They have permitted detailed dissections of cellular proliferation, differentiation, motility, and death, and enabled the assembly of synthetic systems with applications in areas as diverse as photography, chemical synthesis, and medicine. In this review, we provide a brief introduction to optogenetic systems and describe their application to molecular-level analyses of cell signaling. Our discussion highlights important research achievements and speculates on future opportunities to exploit optogenetic systems in the study and assembly of complex biochemical networks.

Light-Inducible Recombinases for Bacterial Optogenetics

Optogenetic tools can provide direct and programmable control of gene expression. Light-inducible recombinases, in particular, offer a powerful method for achieving precise spatiotemporal control of DNA modification. However, to-date this technology has been largely limited to eukaryotic systems. Here, we develop optogenetic recombinases for Escherichia coli that activate in response to blue light. Our approach uses a split recombinase coupled with photodimers, where blue light brings the split protein together to form a functional recombinase. We tested both Cre and Flp recombinases, Vivid and Magnet photodimers, and alternative protein split sites in our analysis. The optimal configuration, Opto-Cre-Vvd, exhibits strong blue light-responsive excision and low ambient light sensitivity. For this system we characterize the effect of light intensity and the temporal dynamics of light-induced recombination. These tools expand the microbial optogenetic toolbox, offering the potential for precise control of DNA excision with light-inducible recombinases in bacteria.

Optogenetic control of mesenchymal cell fate towards precise bone regeneration

Rationale: Spatial-temporal control of cell fate in vivo is of great importance for regenerative medicine. Currently, there remain no practical strategies to tune cell-fate spatial-temporally. Optogenetics is a biological technique that widely used to control cell activity in genetically defined neurons in a spatiotemporal-specific manner by light. In this study, optogenetics was repurposed for precise bone tissue regeneration.

Methods: Lhx8 and BMP2 genes, which are considered as the master genes for mesenchymal stem cell proliferation and differentiation respectively, were recombined into a customized optogenetic control system. In the system, Lhx8 was constitutively expressed, while BMP2 together with shLhx8 expression was driven by blue light.

Results: As expected, blue light induced BMP2 expression and inactivated Lhx8 expression in cells infected with the optogenetic control system. Optogenetic control of BMP2 and Lhx8 expression inversely regulates MSC fate in vitro. By animal study, we found that blue light could fine-tune the regeneration in vivo. Blue light illumination significantly promotes bone regeneration when the scaffold was loaded with MSCs infected with adeno-Lhx8, GI-Gal4DBD, LOV-VP16, and BMP2-shLhx8.

Conclusions: Together, our study revealed that optogenetic control of the master genes for mesenchymal stem cell proliferation and differentiation would be such a candidate strategy for precise regenerative medicine.

An Automated Biomodel Selection System (BMSS) for Gene Circuit Designs

Constructing a complex functional gene circuit composed of different modular biological parts to achieve the desired performance remains challenging without a proper understanding of how the individual module behaves. To address this, mathematical models serve as an important tool toward better interpretation by quantifying the performance of the overall gene circuit, providing insights, and guiding the experimental designs. As different gene circuits might require exclusively different mathematical representations in the form of ordinary differential equations to capture their transient dynamic behaviors, a recurring challenge in model development is the selection of the appropriate model. Here, we developed an automated biomodel selection system (BMSS) which includes a library of pre-established models with intuitive or unintuitive features derived from a vast array of expression profiles. Selection of models is built upon the Akaike information criteria (AIC). We tested the automated platform using characterization data of routinely used inducible systems, constitutive expression systems, and several different logic gate systems (NOT, AND, and OR gates). The BMSS achieved a good agreement for all the different characterization data sets and managed to select the most appropriate model accordingly. To enable exchange and reproducibility of gene circuit design models, the BMSS platform also generates Synthetic Biology Open Language (SBOL)-compliant gene circuit diagrams and Systems Biology Markup Language (SBML) output files. All aspects of the algorithm were programmed in a modular manner to ease the efforts on model extensions or customizations by users. Taken together, the BMSS which is implemented in Python supports users in deriving the best mathematical model candidate in a fast, efficient, and automated way using part/circuit characterization data.