Advances in genetic circuit design: novel biochemistries, deep part mining, and precision gene expression

Development of transcriptional factor-based whole-cell biosensors to monitor and degrade antibiotics using mutant cells obtained via adaptive laboratory evolution

With the widespread use of antibiotics and increasing environmental concerns regarding antibiotic abuse, the detection and degradation of antibiotic residues in various samples has become a pressing issue. Transcriptional factor (TF)-based whole-cell biosensors are low-cost, easy-to-use, and flexible tools for detecting chemicals and controlling bioprocesses. However, because of cytotoxicity caused by antibiotics, the application of such biosensors is limited in the presence of antibiotics. In this study, we used antibiotic-tolerant mutants obtained via adaptive laboratory evolution (ALE) to develop TF-based whole-cell biosensors for antibiotic monitoring and degradation. The biosensors had high performance and stability in detecting relatively high concentrations of tetracycline (Tc) and nisin. The ALE mutant-based Tc biosensor exhibited a 10-fold larger linear detection range than the wild-type strain-based biosensor. Then, the Tc biosensor was employed to detect residual amounts of Tc in mouse stool, serum, and urine samples and facilitate Tc biodegradation in mouse stool, demonstrating its high utility. Considering that ALE has been demonstrated to enhance cell tolerance to various toxic chemicals, our strategy might facilitate the development of whole-cell biosensors for most antibiotics and other toxic ligands.

A robust genetic toolbox for fine-tuning gene expression in the CO2-Fixing methanogenic archaeon Methanococcus maripaludis

Libraries of well-characterized genetic elements for fine-tuning gene expression are essential for biological and biotechnological research and applications. The fast-growing and genetically tractable methanogen, Methanococcus maripaludis, is a promising host organism for biotechnological conversion of carbon dioxide and renewable hydrogen into fuels and value-added products, as well as fundamental biological studies of archaea. However, the lack of molecular tools for gene expression has hindered its application as a workhorse to fine-tune gene and metabolic pathway expressions. In this study, we developed a genetic toolbox, including libraries of promoters, ribosome binding sites (RBS), and neutral sites for chromosomal integration, to facilitate precise gene expression in M. maripaludis. We generated a promoter library consisting of 81 constitutive promoters with expression strengths spanning a ∼104-fold dynamic range. Importantly, we identified a base composition rule for strong archaeal promoters and successfully remodeled weak promoters, enhancing their activities by up to 120-fold. We also established an RBS library containing 42 diverse RBS sequences with translation strengths covering a ∼100-fold dynamic range. Additionally, we identified eight neutral sites and developed a one-step, Cas9-based marker-less knock-in approach for chromosomal integration. We successfully applied the characterized promoter and RBS elements to significantly improve recombinant protein expression by 41-fold and modulate essential gene expression to generate corresponding physiological changes in M. maripaludis. Therefore, this work establishes a solid foundation for utilizing this autotrophic methanogen as an ideal workhorse for archaeal biology and biotechnological studies and applications.

The pGinger Family of Expression Plasmids

The pGinger suite of expression plasmids comprises 43 plasmids that will enable precise constitutive and inducible gene expression in a wide range of Gram-negative bacterial species. Constitutive vectors are composed of 16 synthetic constitutive promoters upstream of red fluorescent protein (RFP), with a broad-host-range BBR1 origin and a kanamycin resistance marker. The family also has seven inducible systems (Jungle Express, Psal/NahR, Pm/XylS, Prha/RhaS, LacO1/LacI, LacUV5/LacI, and Ptet/TetR) controlling RFP expression on BBR1/kanamycin plasmid backbones. For four of these inducible systems (Jungle Express, Psal/NahR, LacO1/LacI, and Ptet/TetR), we created variants that utilize the RK2 origin and spectinomycin or gentamicin selection. Relevant RFP expression and growth data have been collected in the model bacterium Escherichia coli as well as Pseudomonas putida. All pGinger vectors are available via the Joint BioEnergy Institute (JBEI) Public Registry. IMPORTANCE Metabolic engineering and synthetic biology are predicated on the precise control of gene expression. As synthetic biology expands beyond model organisms, more tools will be required that function robustly in a wide range of bacterial hosts. The pGinger family of plasmids constitutes 43 plasmids that will enable both constitutive and inducible gene expression in a wide range of nonmodel Proteobacteria.

Sourcing Phage-Encoded Terminators Using ONT-cappable-seq for SynBio Applications in Pseudomonas

Efficient transcriptional terminators are essential for the performance of genetic circuitry in microbial SynBio hosts. In recent years, several libraries of characterized strong terminators have become available for model organisms such as Escherichia coli. Conversely, terminator libraries for nonmodel species remain scarce, and individual terminators are often ported over from model systems, leading to unpredictable performance in their new hosts. In this work, we mined the genomes of Pseudomonas infecting phages LUZ7 and LUZ100 for transcriptional terminators utilizing the full-length RNA sequencing technique "ONT-cappable-seq" and validated these terminators in three Gram-negative hosts using a terminator trap assay. Based on these results, we present nine terminators for E. coli, Pseudomonas putida, and Pseudomonas aeruginosa, which outperform current reference terminators. Among these, terminator LUZ7 T50 displays potent bidirectional activity. These data further support that bacteriophages, as evolutionary-adapted natural predators of the targeted bacteria, provide a valuable source of microbial SynBio parts.

Design of Four Small-Molecule-Inducible Systems in the Yeast Chromosome, Applied to Optimize Terpene Biosynthesis

The optimization of cellular functions often requires the balancing of gene expression, but the physical construction and screening of alternative designs are costly and time-consuming. Here, we construct a strain of Saccharomyces cerevisiae that contains a "sensor array" containing bacterial regulators that respond to four small-molecule inducers (vanillic acid, xylose, aTc, IPTG). Four promoters can be independently controlled with low background and a 40- to 5000-fold dynamic range. These systems can be used to study the impact of changing the level and timing of gene expression without requiring the construction of multiple strains. We apply this approach to the optimization of a four-gene heterologous pathway to the terpene linalool, which is a flavor and precursor to energetic materials. Using this approach, we identify bottlenecks in the metabolic pathway. This work can aid the rapid automated strain development of yeasts for the bio-manufacturing of diverse products, including chemicals, materials, fuels, and food ingredients.

Hardware, Software, and Wetware Codesign Environment for Synthetic Biology

Synthetic biology is the process of forward engineering living systems. These systems can be used to produce biobased materials, agriculture, medicine, and energy. One approach to designing these systems is to employ techniques from the design of embedded electronics. These techniques include abstraction, standards, modularity, automated design, and formal semantic models of computation. Together, these elements form the foundation of "biodesign automation," where software, robotics, and microfluidic devices combine to create exciting biological systems of the future. This paper describes a "hardware, software, wetware" codesign vision where software tools can be made to act as "genetic compilers" that transform high-level specifications into engineered "genetic circuits" (wetware). This is followed by a process where automation equipment, well-defined experimental workflows, and microfluidic devices are explicitly designed to house, execute, and test these circuits (hardware). These systems can be used as either massively parallel experimental platforms or distributed bioremediation and biosensing devices. Next, scheduling and control algorithms (software) manage these systems' actual execution and data analysis tasks. A distinguishing feature of this approach is how all three of these aspects (hardware, software, and wetware) may be derived from the same basic specification in parallel and generated to fulfill specific cost, performance, and structural requirements.

Novel High-Throughput DNA Part Characterization Technique for Synthetic Biology

This study presents a novel DNA part characterization technique that increases throughput by combinatorial DNA part assembly, solid plate-based quantitative fluorescence assay for phenotyping, and barcode tagging-based long-read sequencing for genotyping. We confirmed that the fluorescence intensities of colonies on plates were comparable to fluorescence at the single-cell level from a high-end, flow-cytometry device and developed a high-throughput image analysis pipeline. The barcode tagging-based long-read sequencing technique enabled rapid identification of all DNA parts and their combinations with a single sequencing experiment. Using our techniques, forty-four DNA parts (21 promoters and 23 RBSs) were successfully characterized in 72 h without any automated equipment. We anticipate that this high-throughput and easy-to-use part characterization technique will contribute to increasing part diversity and be useful for building genetic circuits and metabolic pathways in synthetic biology.

A modular RNA interference system for multiplexed gene regulation

The rational design and realisation of simple-to-use genetic control elements that are modular, orthogonal and robust is essential to the construction of predictable and reliable biological systems of increasing complexity. To this effect, we introduce modular Artificial RNA interference (mARi), a rational, modular and extensible design framework that enables robust, portable and multiplexed post-transcriptional regulation of gene expression in Escherichia coli. The regulatory function of mARi was characterised in a range of relevant genetic contexts, demonstrating its independence from other genetic control elements and the gene of interest, and providing new insight into the design rules of RNA based regulation in E. coli, while a range of cellular contexts also demonstrated it to be independent of growth-phase and strain type. Importantly, the extensibility and orthogonality of mARi enables the simultaneous post-transcriptional regulation of multi-gene systems as both single-gene cassettes and poly-cistronic operons. To facilitate adoption, mARi was designed to be directly integrated into the modular BASIC DNA assembly framework. We anticipate that mARi-based genetic control within an extensible DNA assembly framework will facilitate metabolic engineering, layered genetic control, and advanced genetic circuit applications.

Systems biology–the transformative approach to integrate sciences across disciplines

Life science is the study of living organisms, including bacteria, plants, and animals. Given the importance of biology, chemistry, and bioinformatics, we anticipate that this chapter may contribute to a better understanding of the interdisciplinary connections in life science. Research in applied biological sciences has changed the paradigm of basic and applied research. Biology is the study of life and living organisms, whereas science is a dynamic subject that as a result of constant research, new fields are constantly emerging. Some fields come and go, whereas others develop into new, well-recognized entities. Chemistry is the study of composition of matter and its properties, how the substances merge or separate and also how substances interact with energy. Advances in biology and chemistry provide another means to understand the biological system using many interdisciplinary approaches. Bioinformatics is a multidisciplinary or rather transdisciplinary field that encourages the use of computer tools and methodologies for qualitative and quantitative analysis. There are many instances where two fields, biology and chemistry have intersection. In this chapter, we explain how current knowledge in biology, chemistry, and bioinformatics, as well as its various interdisciplinary domains are merged into life sciences and its applications in biological research.

Computational Design of Small Transcription Activating RNAs (STARs)

A major goal of synthetic biology has been to develop libraries of versatile genetic regulators that enable the precise control of gene expression. In recent years, the creation of novel RNA design motifs has allowed for the bottom-up, computational design of large libraries of high-performing and orthogonal RNA regulator systems. One example of this is Small Transcription Activating RNAs (STARs), which function through the conditional formation of terminator hairpins to activate the transcription of targeted genes. STARs have found broad utility for creating synthetic gene circuits, engineering metabolic pathways, and creating new types of diagnostics. Here we describe the method to computationally design, build, and characterize STAR regulators.

ProD: A Tool for Predictive Design of Tailored Promoters in Escherichia coli

A major goal in synthetic biology is the engineering of synthetic gene circuits with a predictable, controlled and designed outcome. This creates a need for building blocks that can modulate gene expression without interference with the native cell system. A tool allowing forward engineering of promoters with predictable transcription initiation frequency is still lacking. Promoter libraries specific for σ⁷⁰ to ensure the orthogonality of gene expression were built in Escherichia coli and labeled using fluorescence-activated cell sorting to obtain high-throughput DNA sequencing data to train a convolutional neural network. We were able to confirm in vivo that the model is able to predict the promoter transcription initiation frequency (TIF) of new promoter sequences. Here, we provide an online tool for promoter design (ProD) in E. coli, which can be used to tailor output sequences of desired promoter TIF or predict the TIF of a custom sequence.

Biological signal processing filters via engineering allosteric transcription factors

As the size and complexity of genetic circuits increases, scientists and engineers need to find solutions to rapidly optimize flux and reduce the metabolic burden imposed on chassis cells. In this study, we report synthetic biology tools that imbue chassis cells with advanced signal processing functions akin to electrical devices commonly used in wireless transmitters and receivers (i.e., biological BANDPASS and BANDSTOP devices) that can simultaneously reduce metabolic burden. Moreover, this study presents a set of granular and more complete design rules for engineering allosteric transcription factors in the broader LacI/GalR topology. In addition, this study has improved our fundamental understanding of the plasticity and continuum of allosteric communication from the binding pocket to the protein–DNA interaction.

Signal processing is critical to a myriad of biological phenomena (natural and engineered) that involve gene regulation. Biological signal processing can be achieved by way of allosteric transcription factors. In canonical regulatory systems (e.g., the lactose repressor), an INPUT signal results in the induction of a given transcription factor and objectively switches gene expression from an OFF state to an ON state. In such biological systems, to revert the gene expression back to the OFF state requires the aggressive dilution of the input signal, which can take 1 or more d to achieve in a typical biotic system. In this study, we present a class of engineered allosteric transcription factors capable of processing two-signal INPUTS, such that a sequence of INPUTS can rapidly transition gene expression between alternating OFF and ON states. Here, we present two fundamental biological signal processing filters, BANDPASS and BANDSTOP, that are regulated by D-fucose and isopropyl-β-D-1-thiogalactopyranoside. BANDPASS signal processing filters facilitate OFF–ON–OFF gene regulation. Whereas, BANDSTOP filters facilitate the antithetical gene regulation, ON–OFF–ON. Engineered signal processing filters can be directed to seven orthogonal promoters via adaptive modular DNA binding design. This collection of signal processing filters can be used in collaboration with our established transcriptional programming structure. Kinetic studies show that our collection of signal processing filters can switch between states of gene expression within a few minutes with minimal metabolic burden—representing a paradigm shift in general gene regulation.

Characterizing methanol metabolism-related promoters for metabolic engineering of Ogataea polymorpha

Promoters play an important role in regulating gene expression, and construction of microbial cell factories requires multiple promoters for balancing the metabolic pathways. However, there are only a limited number of characterized promoters for gene expression in the methylotrophic yeast Ogataea polymorpha, which hampers the extensive harnessing of this important yeast toward a cell factory. Here we characterized the promoters of methanol utilization pathway, precursor supply pathway, and reactive oxygen species (ROS) defense system, by using a green fluorescence protein variant (GFP_UV) as a quantification signal. Finally, the characterized promoters were used for tuning a fatty alcohol biosynthetic pathway in O. polymorpha and realized fatty alcohol production from methanol. This promoter box should be helpful for gene expression and pathway optimization in the methylotrophic yeast O. polymorpha. KEY POINTS : • 22 promoters related to methanol metabolism were characterized in O. polymorpha. • Promoter truncation resulted shorter and compact promoters. • Promoters with various strengths were used for regulating a fatty alcohol biosynthesis from methanol.

Importance of the 5' regulatory region to bacterial synthetic biology applications

The field of synthetic biology is evolving at a fast pace. It is advancing beyond single-gene alterations in single hosts to the logical design of complex circuits and the development of integrated synthetic genomes. Recent breakthroughs in deep learning, which is increasingly used in de novo assembly of DNA components with predictable effects, are also aiding the discipline. Despite advances in computing, the field is still reliant on the availability of pre-characterized DNA parts, whether natural or synthetic, to regulate gene expression in bacteria and make valuable compounds. In this review, we discuss the different bacterial synthetic biology methodologies employed in the creation of 5' regulatory regions - promoters, untranslated regions and 5'-end of coding sequences. We summarize methodologies and discuss their significance for each of the functional DNA components, and highlight the key advances made in bacterial engineering by concentrating on their flaws and strengths. We end the review by outlining the issues that the discipline may face in the near future.

Rapid prototyping and design of cybergenetic single-cell controllers

The design and implementation of synthetic circuits that operate robustly in the cellular context is fundamental for the advancement of synthetic biology. However, their practical implementation presents challenges due to low predictability of synthetic circuit design and time-intensive troubleshooting. Here, we present the Cyberloop, a testing framework to accelerate the design process and implementation of biomolecular controllers. Cellular fluorescence measurements are sent in real-time to a computer simulating candidate stochastic controllers, which in turn compute the control inputs and feed them back to the controlled cells via light stimulation. Applying this framework to yeast cells engineered with optogenetic tools, we examine and characterize different biomolecular controllers, test the impact of non-ideal circuit behaviors such as dilution on their operation, and qualitatively demonstrate improvements in controller function with certain network modifications. From this analysis, we derive conditions for desirable biomolecular controller performance, thereby avoiding pitfalls during its biological implementation.

Multilayer Genetic Circuits for Dynamic Regulation of Metabolic Pathways

The dynamic regulation of metabolic pathways is based on changes in external signals and endogenous changes in gene expression levels and has extensive applications in the field of synthetic biology and metabolic engineering. However, achieving dynamic control is not trivial, and dynamic control is difficult to obtain using simple, single-level, control strategies because they are often affected by native regulatory networks. Therefore, synthetic biologists usually apply the concept of logic gates to build more complex and multilayer genetic circuits that can process various signals and direct the metabolic flux toward the synthesis of the molecules of interest. In this review, we first summarize the applications of dynamic regulatory systems and genetic circuits and then discuss how to design multilayer genetic circuits to achieve the optimal control of metabolic fluxes in living cells.

Future trends in synthetic biology in Asia

Synthetic biology research and technology translation has garnered increasing interest from the governments and private investors in Asia, where the technology has great potential in driving a sustainable bio-based economy. This Perspective reviews the latest developments in the key enabling technologies of synthetic biology and its application in bio-manufacturing, medicine, food and agriculture in Asia. Asia-centric strengths in synthetic biology to grow the bio-based economy, such as advances in genome editing and the presence of biofoundries combined with the availability of natural resources and vast markets, are also highlighted. The potential barriers to the sustainable development of the field, including inadequate infrastructure and policies, with suggestions to overcome these by building public-private partnerships, more effective multi-lateral collaborations and well-developed governance framework, are presented. Finally, the roles of technology, education and regulation in mitigating potential biosecurity risks are examined. Through these discussions, stakeholders from different groups, including academia, industry and government, are expectantly better positioned to contribute towards the establishment of innovation and bio-economy hubs in Asia.

Direct control of CAR T cells through small molecule-regulated antibodies

Antibody-based therapeutics have experienced a rapid growth in recent years and are now utilized in various modalities spanning from conventional antibodies, antibody-drug conjugates, bispecific antibodies to chimeric antigen receptor (CAR) T cells. Many next generation antibody therapeutics achieve enhanced potency but often increase the risk of adverse events. Antibody scaffolds capable of exhibiting inducible affinities could reduce the risk of adverse events by enabling a transient suspension of antibody activity. To demonstrate this, we develop conditionally activated, single-module CARs, in which tumor antigen recognition is directly modulated by an FDA-approved small molecule drug. The resulting CAR T cells demonstrate specific cytotoxicity of tumor cells comparable to that of traditional CARs, but the cytotoxicity is reversibly attenuated by the addition of the small molecule. The exogenous control of conditional CAR T cell activity allows continual modulation of therapeutic activity to improve the safety profile of CAR T cells across all disease indications.

Predictive design of sigma factor-specific promoters

To engineer synthetic gene circuits, molecular building blocks are developed which can modulate gene expression without interference, mutually or with the host's cell machinery. As the complexity of gene circuits increases, automated design tools and tailored building blocks to ensure perfect tuning of all components in the network are required. Despite the efforts to develop prediction tools that allow forward engineering of promoter transcription initiation frequency (TIF), such a tool is still lacking. Here, we use promoter libraries of E. coli sigma factor 70 (σ70)- and B. subtilis σB-, σF- and σW-dependent promoters to construct prediction models, capable of both predicting promoter TIF and orthogonality of the σ-specific promoters. This is achieved by training a convolutional neural network with high-throughput DNA sequencing data from fluorescence-activated cell sorted promoter libraries. This model functions as the base of the online promoter design tool (ProD), providing tailored promoters for tailored genetic systems.

Programmable cross-ribosome-binding sites to fine-tune the dynamic range of transcription factor-based biosensor

Currently, predictive translation tuning of regulatory elements to the desired output of transcription factor (TF)-based biosensors remains a challenge. The gene expression of a biosensor system must exhibit appropriate translation intensity, which is controlled by the ribosome-binding site (RBS), to achieve fine-tuning of its dynamic range (i.e. fold change in gene expression between the presence and absence of inducer) by adjusting the translation level of the TF and reporter. However, existing TF-based biosensors generally suffer from unpredictable dynamic range. Here, we elucidated the connections and partial mechanisms between RBS, translation level, protein folding and dynamic range, and presented a design platform that predictably tuned the dynamic range of biosensors based on deep learning of large datasets cross-RBSs (cRBSs). In doing so, a library containing 7053 designed cRBSs was divided into five sub-libraries through fluorescence-activated cell sorting to establish a classification model based on convolutional neural network in deep learning. Finally, the present work exhibited a powerful platform to enable predictable translation tuning of RBS to the dynamic range of biosensors.

New Insight into Plasmid-Driven T7 RNA Polymerase in Escherichia coli and Use as a Genetic Amplifier for a Biosensor

T7 RNA polymerase (T7RNAP) and T7 promoter are powerful genetic components, thus a plasmid-driven T7 (PDT7) genetic circuit could be broadly applied for synthetic biology. However, the limited knowledge of the toxicity and instability of such a system still restricts its application. Herein, we constructed 16 constitutive genetic circuts of PDT7 and investigated the orthogonal effects in toxicity and instability. The T7 toxicity was elucidated from the construction processes and cell growth characterization, showing the importance of optimal orthogonality for PDT7. Besides, a protein analysis was performed to validate how the T7 system affected cell metabolism and led to the instability. The application of constitutive PDT7 in functional protein expressions, including carbonic anhydrase, lysine decarboxylase, and 5-ALA synthetase was demonstrated. Furthermore, PDT7 working as a genetic amplifier had been designed for E. coli cell-based biosensors, which illustrated the opportunities in the future of PDT7 used in synthetic biology.

The COMET toolkit for composing customizable genetic programs in mammalian cells

Engineering mammalian cells to carry out sophisticated and customizable genetic programs requires a toolkit of multiple orthogonal and well-characterized transcription factors (TFs). To address this need, we develop the COmposable Mammalian Elements of Transcription (COMET)-an ensemble of TFs and promoters that enable the design and tuning of gene expression to an extent not, to the best of our knowledge, previously possible. COMET currently comprises 44 activating and 12 inhibitory zinc-finger TFs and 83 cognate promoters, combined in a framework that readily accommodates new parts. This system can tune gene expression over three orders of magnitude, provides chemically inducible control of TF activity, and enables single-layer Boolean logic. We also develop a mathematical model that provides mechanistic insights into COMET performance characteristics. Altogether, COMET enables the design and construction of customizable genetic programs in mammalian cells.

Pseudomonas mRNA 2.0: Boosting Gene Expression Through Enhanced mRNA Stability and Translational Efficiency

High gene expression of enzymes partaking in recombinant production pathways is a desirable trait among cell factories belonging to all different kingdoms of life. High enzyme abundance is generally aimed for by utilizing strong promoters, which ramp up gene transcription and mRNA levels. Increased protein abundance can alternatively be achieved by optimizing the expression on the post-transcriptional level. Here, we evaluated protein synthesis with a previously proposed optimized gene expression architecture, in which mRNA stability and translation initiation are modulated by genetic parts such as self-cleaving ribozymes and a bicistronic design, which have initially been described to support the standardization of gene expression. The optimized gene expression architecture was tested in Pseudomonas taiwanensis VLB120, a promising, novel microbial cell factory. The expression cassette was employed on a plasmid basis and after single genomic integration. We used three constitutive and two inducible promoters to drive the expression of two fluorescent reporter proteins and a short acetoin biosynthesis pathway. The performance was confronted with that of a traditional expression cassette harboring the same promoter and gene of interest but lacking the genetic parts for increased expression efficiency. The optimized expression cassette granted higher protein abundance independently of the expression basis or promoter used proving its value for applications requiring high protein abundance.

Engineering DNA recognition and allosteric response properties of TetR family proteins by using a module-swapping strategy

The development of synthetic biological systems requires modular biomolecular components to flexibly alter response pathways. In previous studies, we have established a module-swapping design principle to engineer allosteric response and DNA recognition properties among regulators in the LacI family, in which the engineered regulators served as effective components for implementing new cellular behavior. Here we introduced this protein engineering strategy to two regulators in the TetR family: TetR (UniProt Accession ID: P04483) and MphR (Q9EVJ6). The TetR DNA-binding module and the MphR ligand-binding module were used to create the TetR-MphR. This resulting hybrid regulator possesses DNA-binding properties of TetR and ligand response properties of MphR, which is able to control gene expression in response to a molecular signal in cells. Furthermore, we studied molecular interactions between the TetR DNA-binding module and MphR ligand-binding module by using mutant analysis. Together, we demonstrated that TetR family regulators contain discrete and functional modules that can be used to build biological components with novel properties. This work highlights the utility of rational design as a means of creating modular parts for cell engineering and introduces new possibilities in rewiring cellular response pathways.

Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset

Engineering allosteric transcriptional repressors containing an environmental sensing module (ESM) and a DNA recognition module (DRM) has the potential to unlock a combinatorial set of rationally designed biological responses. We demonstrated that constructing hybrid repressors by fusing distinct ESMs and DRMs provides a means to flexibly rewire genetic networks for complex signal processing. We have used coevolutionary traits among LacI homologs to develop a model for predicting compatibility between ESMs and DRMs. Our predictions accurately agree with the performance of 40 engineered repressors. We have harnessed this framework to develop a system of multiple toggle switches with a master OFF signal that produces a unique behavior: each engineered biological activity is switched to a stable ON state by different chemicals and returned to OFF in response to a common signal. One promising application of this design is to develop living diagnostics for monitoring multiple parameters in complex physiological environments and it represents one of many circuit topologies that can be explored with modular repressors designed with coevolutionary information.

Enhanced growth-driven stepwise inducible expression system development in haloalkaliphilic desulfurizing Thioalkalivibrio versutus

Highly toxic and flammable H₂S gas has become an environmental threat. Because of its ability to efficiently remove H₂S by oxidation, Thioalkalivibrio versutus is gaining more attention. Haloalkaliphilic autotrophs, like the bio-desulfurizing T. versutus, grow weakly. Weak growth makes any trial for developing potent genetic tools required for genetic engineering far from achieved. In this study, the fed-batch strategy improved T. versutus growth by 1.6 fold in maximal growth rate, 9-fold in O.D₆₀₀ values and about 3-fold in biomass and protein productions. The strategy also increased the favorable desulfurization product, sulfur, by 2.7 fold in percent yield and 1.5-fold in diameter. A tight iron-inducible expression system for T. versutus was successfully developed. The system was derived from fed-batch cultivation coupled with new design, build, test and validate (DPTV) approach. The inducible system was validated by toxin expression. Fed-batch cultivation coupled with DPTV approach could be applied to other autotrophs.

Synthetic genetic circuits for programmable biological functionalities

Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.

Advances in engineered trans-acting regulatory RNAs and their application in bacterial genome engineering

Small noncoding RNAs, a large class of ancient posttranscriptional regulators, are increasingly recognized and utilized as key modulators of gene expression in a broad range of microorganisms. Owing to their small molecular size and the central role of Watson-Crick base pairing in defining their interactions, structure and function, numerous diverse types of trans-acting RNA regulators that are functional at the DNA, mRNA and protein levels have been experimentally characterized. It has become increasingly clear that most small RNAs play critical regulatory roles in many processes and are, therefore, considered to be powerful tools for genetic engineering and synthetic biology. The trans-acting regulatory RNAs accelerate this ability to establish potential framework for genetic engineering and genome-scale engineering, which allows RNA structure characterization, easier to design and model compared to DNA or protein-based systems. In this review, we summarize recent advances in engineered trans-acting regulatory RNAs that are used in bacterial genome-scale engineering and in novel cellular capabilities as well as their implementation in wide range of biotechnological, biological and medical applications.

Engineering a New Class of Anti-LacI Transcription Factors with Alternate DNA Recognition

The lactose repressor, LacI (I⁺_YQR), is an archetypal transcription factor that has been a workhorse in many synthetic genetic networks. LacI represses gene expression (apo ligand) and is induced upon binding of the ligand isopropyl β-d-1-thiogalactopyranoside (IPTG). Recently, laboratory evolution was used to confer inverted function in the native LacI topology resulting in anti-LacI (antilac) function (I^A_YQR), where IPTG binding results in gene suppression. Here we engineered 46 antilacs with alternate DNA binding function (I^A_ADR). Phenotypically, I^A_ADR transcription factors are the inverse of wild-type I⁺_YQR function and possess alternate DNA recognition (ADR). This collection of bespoke I^A_ADR bind orthogonally to disparate non-natural operator DNA sequences and suppress gene expression in the presence of IPTG. This new class of I^A_ADR gene regulators were designed modularly via the systematic pairing of nine alternate allosteric regulatory cores with six alternate DNA binding domains that interact with complementary synthetic operator DNA sequences. The 46 I^A_ADR identified in this study are also orthogonal to the naturally occurring operator O¹. Finally, a demonstration of full orthogonality was achieved via the construction of synthetic genetic toggle switches composed of two nonsynonymous unit pair operations that control two distinct fluorescent outputs. This new class of I^A_ADR transcription factors will facilitate the expansion of the computational capacity of engineered gene circuits, via the scalable increase in the control over the number of gene outputs by way of the expansion of the number of unique transcription factors (or systems of transcription factors) that can simultaneously regulate one or more promoter(s).

Application of mRNA Arrays for the Production of mCherry Reporter-Protein Arrays for Quantitative Gene Expression Analysis

The development of programmable regulators that precisely and predictably control gene expression is a major goal of synthetic biology. Consequently, rapid high-throughput biochemical methods capable of quantitatively analyzing all components of gene expression would be of value in the characterization and optimization of regulator performance. In this study we demonstrate a novel application of RNA arrays, involving the production of reporter-protein arrays, to gene expression analysis. This method enables simultaneous quantification of both the transcription and post-transcription/translation components of gene expression, and it also allows the assessment of the orthogonality of multiple regulators. We use our method to directly compare the performance of a series of previously characterized synthetic post-transcriptional riboregulators, thus demonstrating its utility in the development of synthetic regulatory modules and evaluation of gene expression regulation in general.

Biomolecular Assemblies: Moving from Observation to Predictive Design

Biomolecular assembly is a key driving force in nearly all life processes, providing structure, information storage, and communication within cells and at the whole organism level. These assembly processes rely on precise interactions between functional groups on nucleic acids, proteins, carbohydrates, and small molecules, and can be fine-tuned to span a range of time, length, and complexity scales. Recognizing the power of these motifs, researchers have sought to emulate and engineer biomolecular assemblies in the laboratory, with goals ranging from modulating cellular function to the creation of new polymeric materials. In most cases, engineering efforts are inspired or informed by understanding the structure and properties of naturally occurring assemblies, which has in turn fueled the development of predictive models that enable computational design of novel assemblies. This Review will focus on selected examples of protein assemblies, highlighting the story arc from initial discovery of an assembly, through initial engineering attempts, toward the ultimate goal of predictive design. The aim of this Review is to highlight areas where significant progress has been made, as well as to outline remaining challenges, as solving these challenges will be the key that unlocks the full power of biomolecules for advances in technology and medicine.

Engineered dCas9 with reduced toxicity in bacteria: implications for genetic circuit design

Large synthetic genetic circuits require the simultaneous expression of many regulators. Deactivated Cas9 (dCas9) can serve as a repressor by having a small guide RNA (sgRNA) direct it to bind a promoter. The programmability and specificity of RNA:DNA basepairing simplifies the generation of many orthogonal sgRNAs that, in theory, could serve as a large set of regulators in a circuit. However, dCas9 is toxic in many bacteria, thus limiting how high it can be expressed, and low concentrations are quickly sequestered by multiple sgRNAs. Here, we construct a non-toxic version of dCas9 by eliminating PAM (protospacer adjacent motif) binding with a R1335K mutation (dCas9*) and recovering DNA binding by fusing it to the PhlF repressor (dCas9*_PhlF). Both the 30 bp PhlF operator and 20 bp sgRNA binding site are required to repress a promoter. The larger region required for recognition mitigates toxicity in Escherichia coli, allowing up to 9600 ± 800 molecules of dCas9*_PhlF per cell before growth or morphology are impacted, as compared to 530 ± 40 molecules of dCas9. Further, PhlF multimerization leads to an increase in average cooperativity from n = 0.9 (dCas9) to 1.6 (dCas9*_PhlF). A set of 30 orthogonal sgRNA-promoter pairs are characterized as NOT gates; however, the simultaneous use of multiple sgRNAs leads to a monotonic decline in repression and after 15 are co-expressed the dynamic range is <10-fold. This work introduces a non-toxic variant of dCas9, critical for its use in applications in metabolic engineering and synthetic biology, and exposes a limitation in the number of regulators that can be used in one cell when they rely on a shared resource.

Programming Bacteria With Light-Sensors and Applications in Synthetic Biology

Photo-receptors are widely present in both prokaryotic and eukaryotic cells, which serves as the foundation of tuning cell behaviors with light. While practices in eukaryotic cells have been relatively established, trials in bacterial cells have only been emerging in the past few years. A number of light sensors have been engineered in bacteria cells and most of them fall into the categories of two-component and one-component systems. Such a sensor toolbox has enabled practices in controlling synthetic circuits at the level of transcription and protein activity which is a major topic in synthetic biology, according to the central dogma. Additionally, engineered light sensors and practices of tuning synthetic circuits have served as a foundation for achieving light based real-time feedback control. Here, we review programming bacteria cells with light, introducing engineered light sensors in bacteria and their applications, including tuning synthetic circuits and achieving feedback controls over microbial cell culture.

Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology

Work on synthetic biology has largely used a component-based metaphor for system construction. While this paradigm has been successful for the construction of numerous systems, the incorporation of contextual design issues-either compositional, host or environmental-will be key to realising more complex applications. Here, we present a design framework that radically steps away from a purely parts-based paradigm by using aspect-oriented software engineering concepts. We believe that the notion of concerns is a powerful and biologically credible way of thinking about system synthesis. By adopting this approach, we can separate core concerns, which represent modular aims of the design, from cross-cutting concerns, which represent system-wide attributes. The explicit handling of cross-cutting concerns allows for contextual information to enter the design process in a modular way. As a proof-of-principle, we implemented the aspect-oriented approach in the Python tool, SynBioWeaver, which enables the combination, or weaving, of core and cross-cutting concerns. The power and flexibility of this framework is demonstrated through a number of examples covering the inclusion of part context, combining circuit designs in a context dependent manner, and the generation of rule, logic and reaction models from synthetic circuit designs.

Computing with biological switches and clocks

The complex dynamics of biological systems is primarily driven by molecular interactions that underpin the regulatory networks of cells. These networks typically contain positive and negative feedback loops, which are responsible for switch-like and oscillatory dynamics, respectively. Many computing systems rely on switches and clocks as computational modules. While the combination of such modules in biological systems leads to a variety of dynamical behaviours, it is also driving development of new computing algorithms. Here we present a historical perspective on computation by biological systems, with a focus on switches and clocks, and discuss parallels between biology and computing. We also outline our vision for the future of biological computing.

Engineering Complexity in Bacterial Regulatory Circuits for Biotechnological Applications

Engineering microbial systems allows the generation of new technologies having significant impact in the biotechnological industry and on human health. In the past few years, several synthetic biology approaches have been implemented in bacteria to allow precise engineering of novel regulatory circuits for several applications.

Engineering microbial systems allows the generation of new technologies having significant impact in the biotechnological industry and on human health. In the past few years, several synthetic biology approaches have been implemented in bacteria to allow precise engineering of novel regulatory circuits for several applications. The advent of high-throughput technologies and clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9-based DNA editing techniques have been pivotal in this process. Yet, despite the tremendous advances experienced recently, there are still a number of bottlenecks that need to be overcome in order to generate high-performance redesigned living machines, and the use of novel computer-aided approaches would be essential for this task. In this perspective, we discuss some of the main advances in the field of microbial engineering and the new technologies and approaches that should allow the construction of on demand synthetic microbial factories through the redesign of regulatory complexity.

Engineered promoters enable constant gene expression at any copy number in bacteria

The internal environment of growing cells is variable and dynamic, making it difficult to introduce reliable parts, such as promoters, for genetic engineering. Here, we applied control-theoretic ideas to design promoters that maintained constant levels of expression at any copy number. Theory predicts that independence to copy number can be achieved by using an incoherent feedforward loop (iFFL) if the negative regulation is perfectly non-cooperative. We engineered iFFLs into Escherichia coli promoters using transcription-activator-like effectors (TALEs). These promoters had near-identical expression in different genome locations and plasmids, even when their copy number was perturbed by genomic mutations or changes in growth medium composition. We applied the stabilized promoters to show that a three-gene metabolic pathway to produce deoxychromoviridans could retain function without re-tuning when the stabilized-promoter-driven genes were moved from a plasmid into the genome.

Simulation Modeling to Compare High-Throughput, Low-Iteration Optimization Strategies for Metabolic Engineering

Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems.

Genetic engineering of host organisms for pharmaceutical synthesis

Pharmaceutical production hosts may be derived from almost any organism, from Chinese Hamster Ovary (CHO) cell lines to isolated actinomycetes. Each host can be improved, historically only through adaptive evolution. Recently, the maturation of organism engineering has expanded the available models, methods, and tools for altering host phenotypes. New tools like CRISPR-associated endonucleases promise to enable precise cellular reprogramming and to access previously intractable hosts. In this review, we discuss the most recent advances in engineering several types of pharmaceutical production hosts. These include model organisms, potential platform hosts with advantageous metabolism or physiology, specialized producers capable of unique biosynthesis, and CHO, the most widely used recombinant protein production host. To realize improved engineered hosts, an increasing number of approaches involving DNA sequencing and synthesis, host rewriting technologies, computational methods, and organism engineering strategies must be used. Integrative workflows that enable application of the right combination of methods to the right production host could enable economical production solutions for emerging human health treatments.

Part by Part: Synthetic Biology Parts Used in Solventogenic Clostridia

The solventogenic Clostridia are of interest to the chemical industry because of their natural ability to produce chemicals such as butanol, acetone and ethanol from diverse feedstocks. Their use as whole cell factories presents multiple metabolic engineering targets that could lead to improved sustainability and profitability of Clostridium industrial processes. However, engineering efforts have been held back by the scarcity of genetic and synthetic biology tools. Over the past decade, genetic tools to enable transformation and chromosomal modifications have been developed, but the lack of a broad palette of synthetic biology parts remains one of the last obstacles to the rapid engineered improvement of these species for bioproduction. We have systematically reviewed existing parts that have been used in the modification of solventogenic Clostridia, revealing a narrow range of empirically chosen and nonengineered parts that are in current use. The analysis uncovers elements, such as promoters, transcriptional terminators and ribosome binding sites where increased fundamental knowledge is needed for their reliable use in different applications. Together, the review provides the most comprehensive list of parts used and also presents areas where an improved toolbox is needed for full exploitation of these industrially important bacteria.

Developing a Genetically Encoded, Cross-Species Biosensor for Detecting Ammonium and Regulating Biosynthesis of Cyanophycin

Responding to nitrogen status is essential for all living organisms. Bacteria have evolved various complex and exquisite regulatory systems to control nitrogen metabolism. However, natural nitrogen regulatory systems, owing to their complexity, often function only in their original hosts and do not respond properly when transferred to another species. By harnessing the Lactococcus GlnRA system, we developed a genetically encoded, cross-species ammonium biosensor that displays a dynamic range up to 9-fold upon detection of ammonium ion. We demonstrated applications of this ammonium biosensor in three different species (Escherichia coli, Pseudomonas putida, and Synechocystis sp.) to detect different nitrogen sources. This ammonium sensor was further used to regulate the biosynthesis of a nitrogen-rich polymer, cyanophycin, based on ammonium concentration. Given the importance of nitrogen responses, the developed biosensor should be broadly applicable to synthetic biology and bioengineering.