Amplification of small molecule-inducible gene expression via tuning of intracellular receptor densities

Expanding the Toolbox of Broad Host-Range Transcriptional Terminators for Proteobacteria through Metagenomics

As the field of synthetic biology moves toward the utilization of novel bacterial chassis, there is a growing need for biological parts with enhanced performance in a wide number of hosts. Is not unusual that biological parts (such as promoters and terminators), initially characterized in the model bacterium Escherichia coli, do not perform well when implemented in alternative hosts, such as Pseudomonas, therefore limiting the construction of synthetic circuits in industrially relevant bacteria, for instance Pseudomonas putida. In order to address this limitation, we present here the mining of transcriptional terminators through functional metagenomics to identify novel parts with broad host-range activity. Using a GFP-based terminator trap strategy and a broad host-range plasmid, we identified 20 clones with potential terminator activity in P. putida. Further characterization allowed the identification of 4 unique sequences ranging from 58 to 181 bp long that efficiently terminate transcription in P. putida, E. coli, Burkholderia phymatum, and two Pseudomonas strains isolated from Antarctica. Therefore, this work presents a new set of biological parts useful for the engineering of synthetic circuits in Proteobacteria.

Engineered Orthogonal Quorum Sensing Systems for Synthetic Gene Regulation in Escherichia coli

Gene regulators that are controlled by membrane-permeable compounds called homoserine lactones (HSLs) have become popular tools for building synthetic gene networks that coordinate behaviors across populations of engineered bacteria. Synthetic HSL-signaling systems are derived from natural DNA and protein elements from microbial quorum signaling pathways. Crosstalk, where a single HSL can activate multiple regulators, can lead to faults in networks composed of parallel signaling pathways. Here, we report an investigation of quorum sensing components to identify synthetic pathways that exhibit little to no crosstalk in liquid and solid cultures. In previous work, we characterized the response of a single regulator (LuxR) to 10 distinct HSL-synthase enzymes. Our current study determined the responses of five different regulators (LuxR, LasR, TraR, BjaR, and AubR) to the same set of synthases. We identified two sets of orthogonal synthase-regulator pairs (BjaI/BjaR + EsaI/TraR and LasI/LasR + EsaI/TraR) that show little to no crosstalk when they are expressed in Escherichia coli BL21. These results expand the toolbox of characterized components for engineering microbial communities.

Cascaded amplifying circuits enable ultrasensitive cellular sensors for toxic metals

Cell-based biosensors have great potential to detect various toxic and pathogenic contaminants in aqueous environments. However, frequently they cannot meet practical requirements due to insufficient sensing performance. To address this issue, we investigated a modular, cascaded signal amplifying methodology. We first tuned intracellular sensory receptor densities to increase sensitivity, and then engineered multi-layered transcriptional amplifiers to sequentially boost output expression level. We demonstrated these strategies by engineering ultrasensitive bacterial sensors for arsenic and mercury, and improved detection limit and output up to 5,000-fold and 750-fold, respectively. Coupled by leakage regulation approaches, we developed an encapsulated microbial sensor cell array for low-cost, portable and precise field monitoring, where the analyte can be readily quantified via displaying an easy-to-interpret volume bar-like pattern. The ultrasensitive signal amplifying methodology along with the background regulation and the sensing platform will be widely applicable to many other cell-based sensors, paving the way for their real-world applications.

Dynamic control of endogenous metabolism with combinatorial logic circuits

Controlling gene expression during a bioprocess enables real-time metabolic control, coordinated cellular responses, and staging order-of-operations. Achieving this with small molecule inducers is impractical at scale and dynamic circuits are difficult to design. Here, we show that the same set of sensors can be integrated by different combinatorial logic circuits to vary when genes are turned on and off during growth. Three Escherichia coli sensors that respond to the consumption of feedstock (glucose), dissolved oxygen, and by-product accumulation (acetate) are constructed and optimized. By integrating these sensors, logic circuits implement temporal control over an 18-h period. The circuit outputs are used to regulate endogenous enzymes at the transcriptional and post-translational level using CRISPRi and targeted proteolysis, respectively. As a demonstration, two circuits are designed to control acetate production by matching their dynamics to when endogenous genes are expressed (pta or poxB) and respond by turning off the corresponding gene. This work demonstrates how simple circuits can be implemented to enable customizable dynamic gene regulation.

Scaling up genetic circuit design for cellular computing: advances and prospects

Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.

Mitochondria-Targeting Polydopamine Nanocomposites as Chemophotothermal Therapeutics for Cancer

Mitochondria play a key role in a variety of physiological processes, and mitochondria-targeting drug delivery is helpful and effective in cancer therapy. Rhodamine123 (Rhod123) and Doxorubicin (Dox) are not new chemical molecules, and they both can inhibit the growth of cancerous cells. Here, we combine these two "old" chemicals with polydopamine nanoparticles (PDA NPs) to strengthen the antitumor effect with the aid of near-infrared irradiation. PDA NPs carry these two chemicals tightly by hydrogen bonds and π-π stacking besides chemical bonds. The better antitumor profile of PDA-Rhod-Dox comes from the mitochondria-targeting delivery, which decreases ATP in living cells, causing apoptosis of cancerous cells effectively and inhibiting the growth of tumors in mice. The synergistic effect of PDA, Rhod123, and Dox improves the treatment effect of conventional chemotherapy drugs.

Rational engineering of synthetic microbial systems: from single cells to consortia

One promise of synthetic biology is to provide solutions for biomedical and industrial problems by rational design of added functionality in living systems. Microbes are at the forefront of this biological engineering endeavor due to their general ease of handling and their relevance in many potential applications from fermentation to therapeutics. In recent years, the field has witnessed an explosion of novel regulatory tools, from synthetic orthogonal transcription factors to posttranslational mechanisms for increased control over the behavior of synthetic circuits. Tool development has been paralleled by the discovery of principles that enable increased modularity and the management of host-circuit interactions. Engineered cell-to-cell communication bridges the scales from intracellular to population-level coordination. These developments facilitate the translation of more than a decade of circuit design into applications.

An Improved Whole-Cell Biosensor for the Discovery of Lignin-Transforming Enzymes in Functional Metagenomic Screens

The discovery and utilization of biocatalysts that selectively valorize lignocellulose is critical to the profitability of next-generation biorefineries. Here, we report the development of a refactored, whole-cell, GFP-based biosensor for high-throughput identification of biocatalysts that transform lignin into specialty chemicals from environmental DNA of uncultivable archaea and bacteria. The biosensor comprises the transcriptional regulator and promoter of the emrRAB operon of E. coli, and the configuration of the biosensor was tuned with the aid of mathematical model. The biosensor sensitively and selectively detects vanillin and syringaldehyde, and responds linearly over a wide detection range. We employed the biosensor to screen 42 520 fosmid clones comprising environmental DNA isolated from two coal beds and successfully identified 147 clones that transform hardwood kraft lignin to vanillin and syringaldehyde.

Orthogonality and Burdens of Heterologous AND Gate Gene Circuits in E. coli

Synthetic biology approaches commonly introduce heterologous gene networks into a host to predictably program cells, with the expectation of the synthetic network being orthogonal to the host background. However, introduced circuits may interfere with the host’s physiology, either indirectly by posing a metabolic burden and/or through unintended direct interactions between parts of the circuit with those of the host, affecting functionality. Here we used RNA-Seq transcriptome analysis to quantify the interactions between a representative heterologous AND gate circuit and the host Escherichia coli under various conditions including circuit designs and plasmid copy numbers. We show that the circuit plasmid copy number outweighs circuit composition for their effect on host gene expression with medium-copy number plasmid showing more prominent interference than its low-copy number counterpart. In contrast, the circuits have a stronger influence on the host growth with a metabolic load increasing with the copy number of the circuits. Notably, we show that variation of copy number, an increase from low to medium copy, caused different types of change observed in the behavior of components in the AND gate circuit leading to the unbalance of the two gate-inputs and thus counterintuitive output attenuation. The study demonstrates the circuit plasmid copy number is a key factor that can dramatically affect the orthogonality, burden and functionality of the heterologous circuits in the host chassis. The results provide important guidance for future efforts to design orthogonal and robust gene circuits with minimal unwanted interaction and burden to their host.

Cellular Biosensors with Engineered Genetic Circuits

An increasing interest in building novel biological devices with designed cellular functionalities has triggered the search of innovative tools for biocomputation. Utilizing the tools of synthetic biology, numerous genetic circuits have been implemented such as engineered logic operation in analog and digital circuits. Whole cell biosensors are widely used biological devices that employ several biocomputation tools to program cells for desired functions. Up to the present date, a wide range of whole-cell biosensors have been designed and implemented for disease theranostics, biomedical applications, and environmental monitoring. In this review, we investigated the recent developments in biocomputation tools such as analog, digital, and mix circuits, logic gates, switches, and state machines. Additionally, we stated the novel applications of biological devices with computing functionalities for diagnosis and therapy of various diseases such as infections, cancer, or metabolic diseases, as well as the detection of environmental pollutants such as heavy metals or organic toxic compounds. Current whole-cell biosensors are innovative alternatives to classical biosensors; however, there is still a need to advance decision making capabilities by developing novel biocomputing devices.

Autonomous control of metabolic state by a quorum sensing (QS)-mediated regulator for bisabolene production in engineered E. coli

Inducible gene expression systems are widely used in microbial host strains for protein and commodity chemical production because of their extensive characterization and ease of use. However, some of these systems have disadvantages such as leaky expression, lack of dynamic control, and the prohibitively high costs of inducers associated with large-scale production. Quorum sensing (QS) systems in bacteria control gene expression in response to population density, and the LuxI/R system from Vibrio fischeri is a well-studied example. A QS system could be ideal for biofuel production strains as it is self-regulated and does not require the addition of inducer compounds, which reduce operational costs for inducer. In this study, a QS system was developed for inducer-free production of the biofuel compound bisabolene from engineered E. coli. Seven variants of the Sensor plasmid, which carry the luxI-luxR genes, and four variants of the Response plasmid, which carry bisabolene producing pathway genes under the control of the P_luxI promoter, were designed for optimization of bisabolene production. Furthermore, a chromosome-integrated QS strain was engineered with the best combination of Sensor and Response plasmid and produced bisabolene at a titer of 1.1g/L without addition of external inducers. This is a 44% improvement from our previous inducible system. The QS strain also displayed higher homogeneity in gene expression and isoprenoid production compared to an inducible-system strain.

Synthetic Biology: Engineering Living Systems from Biophysical Principles

Synthetic biology was founded as a biophysical discipline that sought explanations for the origins of life from chemical and physical first principles. Modern synthetic biology has been reinvented as an engineering discipline to design new organisms as well as to better understand fundamental biological mechanisms. However, success is still largely limited to the laboratory and transformative applications of synthetic biology are still in their infancy. Here, we review six principles of living systems and how they compare and contrast with engineered systems. We cite specific examples from the synthetic biology literature that illustrate these principles and speculate on their implications for further study. To fully realize the promise of synthetic biology, we must be aware of life's unique properties.

Biosensor-Based Evolution and Elucidation of a Biosynthetic Pathway in Escherichia coli

The successful evolution of metabolite-producing microbes requires a high-throughput screening method to obtain the desired properties within a short time. In this study, we developed a transcription-factor-driven device that combines a metabolite-responsive element and a selection module. This device was able to specifically sense intracellular l-phenylalanine (l-Phe) and convert this signal into an observable phenotype. Applying this device, we successfully improved l-Phe production by screening hyperproducing phenotypes from a ribonucleotide binding site library and a random mutagenesis library. In addition, several site mutations introduced by random mutagenesis were identified and elucidated to facilitate the improvement of l-Phe production. Our results present a paradigm for screening of compounds that are not easily observable to raise the yield of targeted compounds from a large candidate library. This approach may guide further applications in rewiring metabolic circuits and facilitate the directed evolution of recombinant strains.

Autoinduced AND Gate Controls Metabolic Pathway Dynamically in Response to Microbial Communities and Cell Physiological State

Quorum sensing (QS) systems have been widely applied in biotechnology and synthetic biology that require coordinated, community-level behaviors. Meanwhile, the cell physiological state is another key parameter that affects metabolic pathway regulation. Here, we designed an autoinduced AND gate that responds to both microbial communities and the cell physiological state. A series of tunable QS systems in response to different cell densities were obtained through random mutagenesis of LuxR and optimization of the luxRI promoter; the corresponding suitable stationary phase sensing system was selected after monitoring the fluorescence process during cell growth. The application of the final synthetic device was demonstrated using the polyhydroxybutyrate (PHB) production system. The AND gate system increased PHB production by 1-2-fold in Escherichia coli. This synthetic logic gate is a tool for developing a general dynamic regulation system in metabolic engineering in response to complex signals, without using a specific sensor.

Synthetic Cell-Based Sensors with Programmed Selectivity and Sensitivity

Bacteria live in an ever changing environment and, to adapt their physiology, they have to sense the changes. Our current understanding of the mechanisms and elements involved in the detection and processing of these environmental signals grant us access to an array of genetic components able to process such information. As engineers can use different electronic components to build a circuit, we can rewire the cellular components to create digital logic and analogue gene circuits that will program cell behaviour in a designed manner in response to a specific stimulus. Here we present the methods and protocols for designing and implementing synthetic cell-based biosensors that use engineered genetic logic and analogue amplifying circuits to significantly increase selectivity and sensitivity, for example, for heavy metal ions in an aqueous environment. The approach is modular and can be readily applied to improving the sensing limit and performance of a range of microbial cell-based sensors to meet their real world detection requirement.

The Chromobacterium violaceum ArsR Arsenite Repressor Exerts Tighter Control on Its Cognate Promoter Than the Escherichia coli System

Environmental bacteria are endowed with several regulatory systems that have potential applications in biotechnology. In this report, we characterize the arsenic biosensing features of the ars response system from Chromobacterium violaceum in the heterologous host Escherichia coli. We show that the native Pars/arsR system of C. violaceum outperforms the chromosomal ars copy of E. coli when exposed to micromolar concentrations of arsenite. To understand the molecular basis of this phenomenon, we analyzed the interaction between ArsR regulators and their promoter target sites as well as induction of the system at saturating concentrations of the regulators. In vivo titration experiments indicate that ArsR from C. violaceum has stronger binding affinity for its target promoter than the regulator from E. coli does. Additionally, arsenite induction experiments at saturating regulator concentration demonstrates that although the Pars/arsR system from E. coli displays a gradual response to increasing concentration of the inducer, the system from C. violaceum has a steeper response with a stronger promoter induction after a given arsenite threshold. Taken together, these data demonstrate the characterization of a novel arsenic response element from an environmental bacterium with potentially enhanced performance that could be further explored for the construction of an arsenic biosensor.

Tailor-made transcriptional biosensors for optimizing microbial cell factories

Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today's metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature's richness. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

Rationally rewiring the connectivity of the XylR/Pu regulatory node of the m-xylene degradation pathway in Pseudomonas putida

The XylR/Pu regulatory node of the m-xylene biodegradation pathway of Pseudomonas putida mt-2 is one of the most intricate cases of processing internal and external cues into a single controlling element. Despite this complexity, the performance of the regulatory system is determined in vivo only by the occupation of Pu by m-xylene-activated XylR and σ(54)-RNAP. The stoichiometry between these three elements defines natural system boundaries that outline a specific functional space. This space can be expanded artificially following different strategies that involve either the increase of XylR or σ(54) or both elements at the same time (each using a different inducer). In this work we have designed a new regulatory architecture that drives the system to reach a maximum performance in response to one single input. To this end, we first explored using a simple mathematical model whether the output of the XylR/Pu node could be amended by simultaneously increasing σ(54) and XylR in response to only natural inducers. The exacerbation of Pu activity in vivo was tested in strains bearing synthetic transposons encoding xylR and rpoN (the σ(54) coding gene) controlled also by Pu, thereby generating a P. putida strain with the XylR/Pu output controlled by two intertwined feed forward loops (FFLs). The lack of a negative feedback loop in the expression node enables Pu activity to reach its physiological maximum in response to a single input. Only competition for cell resources might ultimately check the upper activity limit of such a rewired m-xylene sensing device.

Phenotypic Variability in Synthetic Biology Applications: Dealing with Noise in Microbial Gene Expression

The stochasticity due to the infrequent collisions among low copy-number molecules within the crowded cellular compartment is a feature of living systems. Single cell variability in gene expression within an isogenic population (i.e., biological noise) is usually described as the sum of two independent components: intrinsic and extrinsic stochasticity. Intrinsic stochasticity arises from the random occurrence of events inherent to the gene expression process (e.g., the burst-like synthesis of mRNA and protein molecules). Extrinsic fluctuations reflect the state of the biological system and its interaction with the intra and extracellular environments (e.g., concentration of available polymerases, ribosomes, metabolites, and micro-environmental conditions). A better understanding of cellular noise would help synthetic biologists design gene circuits with well-defined functional properties. In silico modeling has already revealed several aspects of the network topology’s impact on noise properties; this information could drive the selection of biological parts and the design of reliably engineered pathways. Importantly, while optimizing artificial gene circuitry for industrial applications, synthetic biology could also elucidate the natural mechanisms underlying natural phenotypic variability. In this review, we briefly summarize the functional roles of noise in unicellular organisms and address their relevance to synthetic network design. We will also consider how noise might influence the selection of network topologies supporting reliable functions, and how the variability of cellular events might be exploited when designing innovative biotechnology applications.

Designer cell signal processing circuits for biotechnology

Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field.