Tracking, tuning, and terminating microbial physiology using synthetic riboregulators

Be a GEM: Biocontained, environmentally applied, genetically engineered microbes

Technological advances in engineering biology or synthetic biology have enabled practical applications of genetically engineered microbes (GEMs), including their use as living diagnostics and vehicles for therapeutics. However, technological and non-technological issues associated with biocontainment of GEMs have yet to be addressed before fully realizing their potential. In this short perspective, I briefly discuss the relevant technologies for GEM biocontainment as well as environmental impacts, regulatory issues, and public perception of GEMs.

Engineered orthogonal and obligate bacterial commensalism mediated by a non-standard amino acid

Microorganisms can be genetically engineered for intrinsic biological containment based on synthetic chemical provision. However, reliance on an exogenous chemical limits the contexts where a contained microorganism could survive. Here we design an orthogonal obligate commensalism in Escherichia coli that autonomously creates environments permissive for survival of a partner microbe. We engineer one E. coli strain (the producer) to biosynthesize a non-standard amino acid (nsAA) from simple carbon sources through heterologous expression. We engineer a second E. coli strain (the utilizer) to rely on the same nsAA for growth as a synthetic auxotroph, with a 14-day escape rate of 2.8 × 10-9 escapees per colony-forming unit. Co-culture experiments show utilizer dependence on the producer, with no escape detected during co-inoculation of ~107 colony-forming units of utilizer and a non-producer E. coli strain. Dependence is maintained within a simplified synthetic maize root-associated community. This work provides ecological insights and presents a potential biocontainment strategy independent of an exogenous chemical.

Tailoring microbial fitness through computational steering and CRISPRi-driven robustness regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

Synthetic translational coupling element for multiplexed signal processing and cellular control

Repurposing natural systems to develop customized functions in biological systems is one of the main thrusts of synthetic biology. Translational coupling is a common phenomenon in diverse polycistronic operons for efficient allocation of limited genetic space and cellular resources. These beneficial features of translation coupling can provide exciting opportunities for creating novel synthetic biological devices. Here, we introduce a modular synthetic translational coupling element (synTCE) and integrate this design with de novo designed riboregulators, toehold switches. A systematic exploration of sequence domain variants for synTCEs led to the identification of critical design considerations for improving the system performance. Next, this design approach was seamlessly integrated into logic computations and applied to construct multi-output transcripts with well-defined stoichiometric control. This module was further applied to signaling cascades for combined signal transduction and multi-input/multi-output synthetic devices. Further, the synTCEs can precisely manipulate the N-terminal ends of output proteins, facilitating effective protein localization and cellular population control. Therefore, the synTCEs could enhance computational capability and applicability of riboregulators for reprogramming biological systems, leading to future applications in synthetic biology, metabolic engineering and biotechnology.

Engineering of tnaC-Based Tryptophan Biosensors for Dynamic Control of Violacein Production

Tryptophan not only serves as a fundamental building block for protein synthesis but also acts as a metabolic precursor for a diverse array of high-value chemicals. Although a few tryptophan-responsive biosensors are currently available, there is a growing interest in developing high-performance biosensors. In this study, we create a miniature toolkit of tryptophan biosensors based upon the leader regulatory region of the tnaCAB operon, which is responsible for tryptophan catabolism in Escherichia coli. Four variants are generated by engineering the tnaC leader sequence, which encodes a leader peptide composed of 24 amino acid residues. Subsequently, the performance of both the natural tnaC sequence and its engineered variants is assessed in a reporter strain based on the MazEF toxin-antitoxin system. The results demonstrate that two engineered variants exhibit increased sensitivity to low levels of tryptophan. Moreover, the engineered biosensors are further optimized by replacing the native promoter of tnaC with a phage-derived constitutive promoter. Intriguingly, the engineered biosensors can be reconstructed for extended application in Pseudomonas putida, a robust microbial chassis for metabolic engineering. In summary, our study expands the toolkit of tryptophan biosensors that can be broadly used for the bioproduction of many other high-value tryptophan-derived products.

START: A Versatile Platform for Bacterial Ligand Sensing with Programmable Performances

Recognition of signaling molecules for coordinated regulation of target genes is a fundamental process for biological systems. Cells often rely on transcription factors to accomplish these intricate tasks, yet the subtle conformational changes of protein structures, coupled with the complexity of intertwined protein interaction networks, pose challenges for repurposing these for bioengineering applications. This study introduces a novel platform for ligand-responsive gene regulation, termed START (Synthetic Trans-Acting Riboswitch with Triggering RNA). Inspired by the bacterial ligand sensing system, riboswitch, and the synthetic gene regulator, toehold switch, the START platform enables the implementation of synthetic biosensors for various ligands. Rational sequence design with targeted domain optimization yields high-performance STARTs with a dynamic range up to 67.29-fold and a tunable ligand sensitivity, providing a simple and intuitive strategy for sensor engineering. The START platform also exhibits modularity and composability to allow flexible genetic circuit construction, enabling seamless implementation of OR, AND, and NOT Boolean logic gates for multiple ligand inputs. The START design principle is capable of broadening the suite of synthetic biosensors for diverse chemical and protein ligands, providing a novel riboregulator chassis for synthetic biology and bioengineering applications.

Building RNA-Mediated Artificial Signaling Pathways between Endogenous Genes

Sophisticated genetic networks play a pivotal role in orchestrating cellular responses through intricate signaling pathways across diverse environmental conditions. Beyond the inherent complexity of natural cellular signaling networks, the construction of artificial signaling pathways (ASPs) introduces a vast array of possibilities for reshaping cellular responses, enabling programmable control of living organisms. ASPs can be integrated with existing cellular networks and redirect output responses as desired, allowing seamless communication and coordination with other cellular processes, thereby achieving designable transduction within cells. Among diversified ASPs, establishing connections between originally independent endogenous genes is of particular significance in modifying the genetic networks, so that cells can be endowed with new capabilities to sense and deal with abnormal factors related to differentiated gene expression (i.e., solve the issues of the aberrant gene expression induced by either external or internal stimuli). In a typical scenario, the two genes X and Y in the cell are originally expressed independently. After the introduction of an ASP, changes in the expression of gene X may exert a designed impact on gene Y, subsequently inducing the cellular response related to gene Y. If X represents a disease signal and Y serves as a therapeutic module, the introduction of the ASP empowers cells with a new spontaneous defense system to handle potential risks, which holds great potential for both fundamental and translational studies.In this Account, we primarily review our endeavors in the construction of RNA-mediated ASPs between endogenous genes that can respond to differentiated RNA expression. In contrast to other molecules that may be restricted to specific pathways, synthetic RNA circuits can be easily utilized and expanded as a general platform for constructing ASPs with a high degree of programmability and tunability for diversified functionalities through predictable Watson-Crick base pairing. We first provide an overview of recent advancements in RNA-based genetic circuits, encompassing but not limited to utilization of RNA toehold switches, siRNA and CRISPR systems. Despite notable progress, most reported RNA circuits have to contain at least one exogenous RNA X as input or one engineered RNA Y as a target, which is not suitable for establishing endogenous gene connections. While exogenous RNAs can be engineered and controlled as desired, constructing a general and efficient platform for manipulation of naturally occurring RNAs poses a formidable challenge, especially for the mammalian system. With a focus on this goal, we are devoted to developing efficient strategies to manipulate cell responses by establishing RNA-mediated ASPs between endogenous genes, particularly in mammalian cells. Our step-by-step progress in engineering customized cell signaling circuits, from bacterial cells to mammalian cells, from gene expression regulation to phenotype control, and from small RNA to long mRNA of low abundance and more complex secondary structures, is systematically described. Finally, future perspectives and potential applications of these RNA-mediated ASPs between endogenous genes are also discussed.

Antigen identification strategies and preclinical evaluation models for advancing tuberculosis vaccine development

In its myriad devastating forms, Tuberculosis (TB) has existed for centuries, and humanity is still affected by it. Mycobacterium tuberculosis (M. tuberculosis), the causative agent of TB, was the foremost killer among infectious agents until the COVID-19 pandemic. One of the key healthcare strategies available to reduce the risk of TB is immunization with bacilli Calmette-Guerin (BCG). Although BCG has been widely used to protect against TB, reports show that BCG confers highly variable efficacy (0-80%) against adult pulmonary TB. Unwavering efforts have been made over the past 20 years to develop and evaluate new TB vaccine candidates. The failure of conventional preclinical animal models to fully recapitulate human response to TB, as also seen for the failure of MVA85A in clinical trials, signifies the need to develop better preclinical models for TB vaccine evaluation. In the present review article, we outline various approaches used to identify protective mycobacterial antigens and recent advancements in preclinical models for assessing the efficacy of candidate TB vaccines.

Genetically Engineered Microorganisms and Their Impact on Human Health

The emergence of antibiotic-resistant strains, the decreased effectiveness of conventional therapies, and the side effects have led researchers to seek a safer, more cost-effective, patient-friendly, and effective method that does not develop antibiotic resistance. With progress in synthetic biology and genetic engineering, genetically engineered microorganisms effective in treatment, prophylaxis, drug delivery, and diagnosis have been developed. The present study reviews the types of genetically engineered bacteria and phages, their impacts on diseases, cancer, and metabolic and inflammatory disorders, the biosynthesis of these modified strains, the route of administration, and their effects on the environment. We conclude that genetically engineered microorganisms can be considered promising candidates for adjunctive treatment of diseases and cancers.

Cas9-assisted biological containment of a genetically engineered human commensal bacterium and genetic elements

Sophisticated gene circuits built by synthetic biology can enable bacteria to sense their environment and respond predictably. Engineered biosensing bacteria outfitted with such circuits can potentially probe the human gut microbiome to prevent, diagnose, or treat disease. To provide robust biocontainment for engineered bacteria, we devised a Cas9-assisted auxotrophic biocontainment system combining thymidine auxotrophy, an Engineered Riboregulator (ER) for controlled gene expression, and a CRISPR Device (CD). The CD prevents the engineered bacteria from acquiring thyA via horizontal gene transfer, which would disrupt the biocontainment system, and inhibits the spread of genetic elements by killing bacteria harboring the gene cassette. This system tunably controlled gene expression in the human gut commensal bacterium Bacteroides thetaiotaomicron, prevented escape from thymidine auxotrophy, and blocked transgene dissemination. These capabilities were validated in vitro and in vivo. This biocontainment system exemplifies a powerful strategy for bringing genetically engineered microorganisms safely into biomedicine.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

Genetic Engineering of Resident Bacteria in the Gut Microbiome

Techniques by which to genetically manipulate members of the microbiota enable both the evaluation of host-microbe interactions and an avenue by which to monitor and modulate human physiology. Genetic engineering applications have traditionally focused on model gut residents, such as Escherichia coli and lactic acid bacteria. However, emerging efforts by which to develop synthetic biology toolsets for "nonmodel" resident gut microbes could provide an improved foundation for microbiome engineering. As genome engineering tools come online, so too have novel applications for engineered gut microbes. Engineered resident gut bacteria facilitate investigations of the roles of microbes and their metabolites on host health and allow for potential live microbial biotherapeutics. Due to the rapid pace of discovery in this burgeoning field, this minireview highlights advancements in the genetic engineering of all resident gut microbes.

A novel synthetic sRNA promoting protein overexpression in cell-free systems

Bacterial small RNAs (sRNAs) that regulate gene expression have been engineered for uses in synthetic biology and metabolic engineering. Here, we designed a novel non-Hfq-dependent sRNA scaffold that uses a modifiable 20 nucleotide antisense binding region to target mRNAs selectively and influence protein expression. The system was developed for regulation of a fluorescent reporter in vivo using Escherichia coli, but the system was found to be more responsive and produced statistically significant results when applied to protein synthesis using in vitro cell-free systems (CFS). Antisense binding sequences were designed to target not only translation initiation regions but various secondary structures in the reporter mRNA. Targeting a high-energy stem loop structure and the 3' end of mRNA yielded protein expression knock-downs that approached 70%. Notably, targeting a low-energy stem structure near a potential RNase E binding site led to a statistically significant 65% increase in protein expression (p < 0.05). These results were not obtainable in vivo, and the underlying mechanism was translated from the reporter system to achieve better than 75% increase in recombinant diaphorase expression in a CFS. It is possible the designs developed here can be applied to improve/regulate expression of other proteins in a CFS.

Stability, robustness, and containment: preparing synthetic biology for real-world deployment

As engineered microbes are used in increasingly diverse applications across human health and bioproduction, the field of synthetic biology will need to focus on strategies that stabilize and contain the function of these populations within target environments. To this end, recent advancements have created layered sensing circuits that can compute cell survival, genetic contexts that are less susceptible to mutation, burden, and resource control circuits, and methods for population variability reduction. These tools expand the potential for real-world deployment of complex microbial systems by enhancing their environmental robustness and functional stability in the face of unpredictable host response and evolutionary pressure.

Comparison of Kill Switch Toxins in Plant-Beneficial Pseudomonas fluorescens Reveals Drivers of Lethality, Stability, and Escape

Kill switches provide a biocontainment strategy in which unwanted growth of an engineered microorganism is prevented by expression of a toxin gene. A major challenge in kill switch engineering is balancing evolutionary stability with robust cell killing activity in application relevant host strains. Understanding host-specific containment dynamics and modes of failure helps to develop potent yet stable kill switches. To guide the design of robust kill switches in the agriculturally relevant strain Pseudomonas fluorescens SBW25, we present a comparison of lethality, stability, and genetic escape of eight different toxic effectors in the presence of their cognate inactivators (i.e., toxin-antitoxin modules, polymorphic exotoxin-immunity systems, restriction endonuclease-methyltransferase pair). We find that cell killing capacity and evolutionary stability are inversely correlated and dependent on the level of protection provided by the inactivator gene. Decreasing the proteolytic stability of the inactivator protein can increase cell killing capacity, but at the cost of long-term circuit stability. By comparing toxins within the same genetic context, we determine that modes of genetic escape increase with circuit complexity and are driven by toxin activity, the protective capacity of the inactivator, and the presence of mutation-prone sequences within the circuit. Collectively, the results of our study reveal that circuit complexity, toxin choice, inactivator stability, and DNA sequence design are powerful drivers of kill switch stability and valuable targets for optimization of biocontainment systems.

A Framework for the Systematic Selection of Biosensor Chassis for Environmental Synthetic Biology

Microbial biosensors sense and report exposures to stimuli, thereby facilitating our understanding of environmental processes. Successful design and deployment of biosensors hinge on the persistence of the microbial host of the genetic circuit, termed the chassis. However, model chassis organisms may persist poorly in environmental conditions. In contrast, non-model organisms persist better in environmental conditions but are limited by other challenges, such as genetic intractability and part unavailability. Here we identify ecological, metabolic, and genetic constraints for chassis development and propose a conceptual framework for the systematic selection of environmental biosensor chassis. We identify key challenges with using current model chassis and delineate major points of conflict in choosing the most suitable organisms as chassis for environmental biosensing. This framework provides a way forward in the selection of biosensor chassis for environmental synthetic biology.

Engineering Toehold-Mediated Switches for Native RNA Detection and Regulation in Bacteria

RNA switches are versatile tools in synthetic biology for sensing and regulation applications. The discoveries of RNA-mediated translational and transcriptional control have facilitated the development of complexde novodesigns of RNA switches. Specifically, RNA toehold-mediated switches, in which binding to the toehold sensing domain controls the transition between switch states via strand displacement, have been extensively adapted for coupling systems responses to specifictrans-RNA inputs. This review highlights some of the challenges associated with applying these switches for native RNA detectionin vivo, including transferability between organisms. The applicability and design considerations of toehold-mediated switches are discussed by highlighting twelve recently developed switch designs. This review finishes with future perspectives to address current gaps in the field, particularly regarding the power of structural prediction algorithms for improved in vivo functionality of RNA switches.

Cellular Computational Logic Using Toehold Switches

The development of computational logic that carries programmable and predictable features is one of the key requirements for next-generation synthetic biological devices. Despite considerable progress, the construction of synthetic biological arithmetic logic units presents numerous challenges. In this paper, utilizing the unique advantages of RNA molecules in building complex logic circuits in the cellular environment, we demonstrate the RNA-only bitwise logical operation of XOR gates and basic arithmetic operations, including a half adder, a half subtractor, and a Feynman gate, in Escherichia coli. Specifically, de-novo-designed riboregulators, known as toehold switches, were concatenated to enhance the functionality of an OR gate, and a previously utilized antisense RNA strategy was further optimized to construct orthogonal NIMPLY gates. These optimized synthetic logic gates were able to be seamlessly integrated to achieve final arithmetic operations on small molecule inputs in cells. Toehold-switch-based ribocomputing devices may provide a fundamental basis for synthetic RNA-based arithmetic logic units or higher-order systems in cells.

Genetically stable CRISPR-based kill switches for engineered microbes

Microbial biocontainment is an essential goal for engineering safe, next-generation living therapeutics. However, the genetic stability of biocontainment circuits, including kill switches, is a challenge that must be addressed. Kill switches are among the most difficult circuits to maintain due to the strong selection pressure they impart, leading to high potential for evolution of escape mutant populations. Here we engineer two CRISPR-based kill switches in the probiotic Escherichia coli Nissle 1917, a single-input chemical-responsive switch and a 2-input chemical- and temperature-responsive switch. We employ parallel strategies to address kill switch stability, including functional redundancy within the circuit, modulation of the SOS response, antibiotic-independent plasmid maintenance, and provision of intra-niche competition by a closely related strain. We demonstrate that strains harboring either kill switch can be selectively and efficiently killed inside the murine gut, while strains harboring the 2-input switch are additionally killed upon excretion. Leveraging redundant strategies, we demonstrate robust biocontainment of our kill switch strains and provide a template for future kill switch development.

Computational Design of RNA Toehold-Mediated Translation Activators

Translation activators are an important class of riboregulators that respond to nucleic acid signals by activating gene expression. Toehold switches and single-nucleotide-specific programmable riboregulators (SNIPRs) are two types of translation activators that can detect nearly any nucleic acid sequence using interactions initiated by single-stranded domains known as toeholds. Toehold switches operate with high dynamic range, orthogonality, and programmability, making them capable of detecting a variety of pathogens in paper-based cell-free diagnostic assays. SNIPRs are designed to enable the accurate detection of single-nucleotide mutations, making them valuable tools for mutation and drug-resistance assays. Here we describe the computational design process for generating toehold switches and SNIPRs active against different pathogens and mutations of interest. Such riboregulators can be deployed in paper-based diagnostic assays to enable rapid and low-cost disease detection.

Implementation of novel boolean logic gates for IMPLICATION and XOR functions using riboregulators

To date, several different types of synthetic genetic switches, including riboregulators, riboswitches, and toehold switches, have been developed to construct AND, OR, NOT, NAND, NOR, and NOT IMPLICATION (NIMP) gates. The logic gate can integrate multiple input signals following a set of algorithms and generate a response only if strictly defined conditions are met. However, there are still some logic gates that have not been implemented but are necessary to build complex genetic circuits. Here, based on the toehold switches and three-way-junction (3WJ) repressors, we designed two novel biological Boolean logic gates of IMPLICATION (IMP) and XOR. Subsequently, the outputs of these two logic gates were characterized by fluorescence analysis, indicating that they can achieve the truth tables of logical gates. Furthermore, the fluorescence intensity under the logical TRUE condition was significantly higher than under the logical FALSE condition, suggesting the high dynamic range of the ON/OFF ratios. Because of the programmability of synthetic RNA switches, the constructed RNA logic gates could serve as elementary units to build a versatile and powerful platform for translational regulation and RNA-based biological computation.

Detection of pks Island mRNAs Using Toehold Sensors in Escherichia coli

Synthetic biologists have applied biomolecular engineering approaches toward the goal of novel biological devices and have shown progress in diverse areas of medicine and biotechnology. Especially promising is the application of synthetic biological devices towards a novel class of molecular diagnostics. As an example, a de-novo-designed riboregulator called toehold switch, with its programmability and compatibility with field-deployable devices showed promising in vitro applications for viral RNA detection such as Zika and Corona viruses. However, the in vivo application of high-performance RNA sensors remains challenging due to the secondary structure of long mRNA species. Here, we introduced ‘Helper RNAs’ that can enhance the functionality of toehold switch sensors by mitigating the effect of secondary structures around a target site. By employing the helper RNAs, previously reported mCherry mRNA sensor showed improved fold-changes in vivo. To further generalize the Helper RNA approaches, we employed automatic design pipeline for toehold sensors that target the essential genes within the pks island, an important target of biomedical research in connection with colorectal cancer. The toehold switch sensors showed fold-changes upon the expression of full-length mRNAs that apparently depended sensitively on the identity of the gene as well as the predicted local structure within the target region of the mRNA. Still, the helper RNAs could improve the performance of toehold switch sensors in many instances, with up to 10-fold improvement over no helper cases. These results suggest that the helper RNA approaches can further assist the design of functional RNA devices in vivo with the aid of the streamlined automatic design software developed here. Further, our solutions for screening and stabilizing single-stranded region of mRNA may find use in other in vivo mRNA-sensing applications such as cas13 crRNA design, transcriptome engineering, and trans-cleaving ribozymes.

Programming living sensors for environment, health and biomanufacturing

Synthetic biology offers new tools and capabilities of engineering cells with desired functions for example as new biosensing platforms leveraging engineered microbes. In the last two decades, bacterial cells have been programmed to sense and respond to various input cues for versatile purposes including environmental monitoring, disease diagnosis and adaptive biomanufacturing. Despite demonstrated proof-of-concept success in the laboratory, the real-world applications of microbial sensors have been restricted due to certain technical and societal limitations. Yet, most limitations can be addressed by new technological developments in synthetic biology such as circuit design, biocontainment and machine learning. Here, we summarize the latest advances in synthetic biology and discuss how they could accelerate the development, enhance the performance and address the present limitations of microbial sensors to facilitate their use in the field. We view that programmable living sensors are promising sensing platforms to achieve sustainable, affordable and easy-to-use on-site detection in diverse settings.

Attenuator LRR - a regulatory tool for modulating gene expression in Gram-positive bacteria

With the rapid development of synthetic biology in recent years, particular attention has been paid to RNA devices, especially riboswitches, because of their significant and diverse regulatory roles in prokaryotic and eukaryotic cells. Due to the limited performance and context-dependence of riboswitches, only a few of them (such as theophylline, tetracycline and ciprofloxacin riboswitches) have been utilized as regulatory tools in biotechnology. In the present study, we demonstrated that a ribosome-dependent ribo-regulator, LRR, discovered in our previous work, exhibits an attractive regulatory performance. Specifically, it offers a 60-fold change in expression in the presence of retapamulin and a low level of leaky expression of about 1-2% without antibiotics. Moreover, LRR can be combined with different promoters and performs well in Bacillus thuringiensis, B. cereus, B. amyloliquefaciens, and B. subtilis. Additionally, LRR also functions in the Gram-negative bacterium Escherichia coli. Furthermore, we demonstrate its ability to control melanin metabolism in B. thuringiensis BMB171. Our results show that LRR can be applied to regulate gene expression, construct genetic circuits and tune metabolic pathways, and has great potential for many applications in synthetic biology.

Drug delivery to the inflamed intestinal mucosa - targeting technologies and human cell culture models for better therapies of IBD

Current treatment strategies for inflammatory bowel disease (IBD) seek to alleviate the undesirable symptoms of the disorder. Despite the higher specificity of newer generation therapeutics, e.g. monoclonal antibodies, adverse effects still arise from their interference with non-specific systemic immune cascades. To circumvent such undesirable effects, both conventional and newer therapeutic options can benefit from various targeting strategies. Of course, both the development and the assessment of the efficiency of such targeted delivery systems necessitate the use of suitable in vivo and in vitro models representing relevant pathophysiological manifestations of the disorder. Accordingly, the current review seeks to provide a comprehensive discussion of the available preclinical models with emphasis on human in vitro models of IBD, along with their potentials and limitations. This is followed by an elaboration on the advancements in the field of biology- and nanotechnology-based targeted drug delivery systems and the potential rooms for improvement to facilitate their clinical translation.

Genetically encoded RNA nanodevices for cellular imaging and regulation

Nucleic acid-based nanodevices have been widely used in the fields of biosensing and nanomedicine. Traditionally, the majority of these nanodevices were first constructed in vitro using synthetic DNA or RNA oligonucleotides and then delivered into cells. Nowadays, the emergence of genetically encoded RNA nanodevices has provided a promising alternative approach for intracellular analysis and regulation. These genetically encoded RNA-based nanodevices can be directly transcribed and continuously produced inside living cells. A variety of highly precise and programmable nanodevices have been constructed in this way during the last decade. In this review, we will summarize the recent advances in the design and function of these artificial genetically encoded RNA nanodevices. In particular, we will focus on their applications in regulating cellular gene expression, imaging, logic operation, structural biology, and optogenetics. We believe these versatile RNA-based nanodevices will be broadly used in the near future to probe and program cells and other biological systems.

Modular and Versatile Trans-Encoded Genetic Switches

Current bacterial RNA switches suffer from lack of versatile inputs and are difficult to engineer. We present versatile and modular RNA switches that are trans-encoded and based on tRNA-mimicking structures (TMSs). These switches provide a high degree of freedom for reengineering and can thus be designed to accept a wide range of inputs, including RNA, small molecules, and proteins. This powerful approach enables control of the translation of protein expression from plasmid and genome DNA.

Sequence-to-function deep learning frameworks for engineered riboregulators

While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of completely novel biological circuit components beyond naturally-derived templates remains challenging due to poorly understood design rules. Toehold switches, which are programmable nucleic acid sensors, face an analogous design bottleneck; our limited understanding of how sequence impacts functionality often necessitates expensive, time-consuming screens to identify effective switches. Here, we introduce Sequence-based Toehold Optimization and Redesign Model (STORM) and Nucleic-Acid Speech (NuSpeak), two orthogonal and synergistic deep learning architectures to characterize and optimize toeholds. Applying techniques from computer vision and natural language processing, we 'un-box' our models using convolutional filters, attention maps, and in silico mutagenesis. Through transfer-learning, we redesign sub-optimal toehold sensors, even with sparse training data, experimentally validating their improved performance. This work provides sequence-to-function deep learning frameworks for toehold selection and design, augmenting our ability to construct potent biological circuit components and precision diagnostics.

Biosensing in Smart Engineered Probiotics

Engineered microbes are exciting alternatives to current diagnostics and therapeutics. Researchers have developed a wide range of genetic tools and parts to engineer probiotic and commensal microbes. Among these tools and parts, biosensors allow the microbes to sense and record or to sense and respond to chemical and environmental signals in the body, enabling them to report on health conditions of the animal host and/or deliver therapeutics in a controlled manner. This review focuses on how biosensing is applied to engineer "smart" microbes for in vivo diagnostic, therapeutic, and biocontainment goals. Hurdles that need to be overcome when transitioning from high-throughput in vitro systems to low-throughput in vivo animal models, new technologies that can be implemented to alleviate this experimental gap, and areas where future advancements can be made to maximize the utility of biosensing for medical applications are also discussed. As technologies for engineering microbes continue to be developed, these engineered organisms will be used to address many medical challenges.

Enzyme-Assisted Nucleic Acid Detection for Infectious Disease Diagnostics: Moving toward the Point-of-Care

Driven by complex and interconnected factors, including population growth, climate change, and geopolitics, infectious diseases represent one of the greatest healthcare challenges of the 21st century. Diagnostic technologies are the first line of defense in the fight against infectious disease, providing critical information to inform epidemiological models, track diseases, decide treatment choices, and ultimately prevent epidemics. The diagnosis of infectious disease at the genomic level using nucleic acid disease biomarkers has proven to be the most effective approach to date. Such methods rely heavily on enzymes to specifically amplify or detect nucleic acids in complex samples, and significant effort has been exerted to harness the power of enzymes for in vitro nucleic acid diagnostics. Unfortunately, significant challenges limit the potential of enzyme-assisted nucleic acid diagnostics, particularly when translating diagnostic technologies from the lab toward the point-of-use or point-of-care. Herein, we discuss the current state of the field and highlight cross-disciplinary efforts to solve the challenges associated with the successful deployment of this important class of diagnostics at or near the point-of-care.

Controlling the Implementation of Transgenic Microbes: Are We Ready for What Synthetic Biology Has to Offer?

Synthetic biology has promised and delivered on an impressive array of applications based on genetically modified microorganisms. While novel biotechnology undoubtedly offers benefits, like all new technology, precautions should be considered during implementation to reduce the risk of both known and unknown adverse effects. To achieve containment of transgenic microorganisms, confidence to a near-scientific certainty that they cannot transfer their transgenic genes to other organisms, and that they cannot survive to propagate in unintended environments, is a priority. Here, we present an in-depth summary of biological containment systems for micro-organisms published to date, including the production of a genetic firewall through genome recoding and physical containment of microbes using auxotrophies, regulation of essential genes, and expression of toxic genes. The level of containment required to consider a transgenic organism suitable for deployment is discussed, as well as standards of practice for developing new containment systems.

Safety Aspects of Genetically Modified Lactic Acid Bacteria

Lactic acid bacteria (LAB) have a long history of use in the food industry. Some species are part of the normal human microbiota and have beneficial properties for human health. Their long-standing use and considerable biotechnological potential have led to the development of various systems for their engineering. Together with novel approaches such as CRISPR-Cas, the established systems for engineering now allow significant improvements to LAB strains. Nevertheless, genetically modified LAB (GM-LAB) still encounter disapproval and are under extensive regulatory requirements. This review presents data on the prospects for LAB to obtain 'generally recognized as safe' (GRAS) status. Genetic modification of LAB is discussed, together with problems that can arise from their engineering, including their dissemination into the environment and the spread of antibiotic resistance markers. Possible solutions that would allow the use of GM-LAB are described, such as biocontainment, alternative selection markers, and use of homologous DNA. The use of GM-LAB as cell factories in closed systems that prevent their environmental release is the least problematic aspect, and this is also discussed.

Fail-safe genetic codes designed to intrinsically contain engineered organisms

One challenge in engineering organisms is taking responsibility for their behavior over many generations. Spontaneous mutations arising before or during use can impact heterologous genetic functions, disrupt system integration, or change organism phenotype. Here, we propose restructuring the genetic code itself such that point mutations in protein-coding sequences are selected against. Synthetic genetic systems so-encoded should fail more safely in response to most spontaneous mutations. We designed fail-safe codes and simulated their expected effects on the evolution of so-encoded proteins. We predict fail-safe codes supporting expression of 20 or 15 amino acids could slow protein evolution to ∼30% or 0% the rate of standard-encoded proteins, respectively. We also designed quadruplet-codon codes that should ensure all single point mutations in protein-coding sequences are selected against while maintaining expression of 20 or more amino acids. We demonstrate experimentally that a reduced set of 21 tRNAs is capable of expressing a protein encoded by only 20 sense codons, whereas a standard 64-codon encoding is not expressed. Our work suggests that biological systems using rationally depleted but otherwise natural translation systems should evolve more slowly and that such hypoevolvable organisms may be less likely to invade new niches or outcompete native populations.

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.

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.

Engineering metabolite-responsive transcriptional factors to sense small molecules in eukaryotes: current state and perspectives

Nature has evolved exquisite sensing mechanisms to detect cellular and environmental signals surrounding living organisms. These biosensors have been widely used to sense small molecules, detect environmental cues and diagnose disease markers. Metabolic engineers and synthetic biologists have been able to exploit metabolites-responsive transcriptional factors (MRTFs) as basic tools to rewire cell metabolism, reprogram cellular activity as well as boost cell’s productivity. This is commonly achieved by integrating sensor-actuator systems with biocatalytic functions and dynamically allocating cellular resources to drive carbon flux toward the target pathway. Up to date, most of identified MRTFs are derived from bacteria. As an endeavor to advance intelligent biomanufacturing in yeast cell factory, we will summarize the opportunities and challenges to transfer the bacteria-derived MRTFs to expand the small-molecule sensing capability in eukaryotic cells. We will discuss the design principles underlying MRTF-based biosensors in eukaryotic cells, including the choice of reliable reporters and the characterization tools to minimize background noise, strategies to tune the sensor dynamic range, sensitivity and specificity, as well as the criteria to engineer activator and repressor-based biosensors. Due to the physical separation of transcription and protein expression in eukaryotes, we argue that nuclear import/export mechanism of MRTFs across the nuclear membrane plays a critical role in regulating the MRTF sensor dynamics. Precisely-controlled MRTF response will allow us to repurpose the vast majority of transcriptional factors as molecular switches to achieve temporal or spatial gene expression in eukaryotes. Uncovering this knowledge will inform us fundamental design principles to deliver robust cell factories and enable the design of reprogrammable and predictable biological systems for intelligent biomanufacturing, smart therapeutics or precision medicine in the foreseeable future.

New Applications of Synthetic Biology Tools for Cyanobacterial Metabolic Engineering

Cyanobacteria are promising microorganisms for sustainable biotechnologies, yet unlocking their potential requires radical re-engineering and application of cutting-edge synthetic biology techniques. In recent years, the available devices and strategies for modifying cyanobacteria have been increasing, including advances in the design of genetic promoters, ribosome binding sites, riboswitches, reporter proteins, modular vector systems, and markerless selection systems. Because of these new toolkits, cyanobacteria have been successfully engineered to express heterologous pathways for the production of a wide variety of valuable compounds. Cyanobacterial strains with the potential to be used in real-world applications will require the refinement of genetic circuits used to express the heterologous pathways and development of accurate models that predict how these pathways can be best integrated into the larger cellular metabolic network. Herein, we review advances that have been made to translate synthetic biology tools into cyanobacterial model organisms and summarize experimental and in silico strategies that have been employed to increase their bioproduction potential. Despite the advances in synthetic biology and metabolic engineering during the last years, it is clear that still further improvements are required if cyanobacteria are to be competitive with heterotrophic microorganisms for the bioproduction of added-value compounds.

Exploring of the feature space of de novo developed post-transcriptional riboregulators

Metabolic engineering increasingly depends upon RNA technology to customly rewire the metabolism to maximize production. To this end, pure riboregulators allow dynamic gene repression without the need of a potentially burdensome coexpressed protein like typical Hfq binding small RNAs and clustered regularly interspaced short palindromic repeats technology. Despite this clear advantage, no clear general design principles are available to de novo develop repressing riboregulators, limiting the availability and the reliable development of these type of riboregulators. Here, to overcome this lack of knowledge on the functionality of repressing riboregulators, translation inhibiting RNAs are developed from scratch. These de novo developed riboregulators explore features related to thermodynamical and structural factors previously attributed to translation initiation modulation. In total, 12 structural and thermodynamic features were defined of which six features were retained after removing correlations from an in silico generated riboregulator library. From this translation inhibiting RNA library, 18 riboregulators were selected using a experimental design and subsequently constructed and co-expressed with two target untranslated regions to link the translation inhibiting RNA features to functionality. The pure riboregulators in the design of experiments showed repression down to 6% of the original protein expression levels, which could only be partially explained by a ordinary least squares regression model. To allow reliable forward engineering, a partial least squares regression model was constructed and validated to link the properties of translation inhibiting RNA riboregulators to gene repression. In this model both structural and thermodynamic features were important for efficient gene repression by pure riboregulators. This approach enables a more reliable de novo forward engineering of effective pure riboregulators, which further expands the RNA toolbox for gene expression modulation.

To allow reliable forward engineering of microbial cell factories, various metabolic engineering efforts rely on RNA-based technology. As such, programmable riboregulators allow dynamic control over gene expression. However, no clear design principles exist for de novo developed repressing riboregulators, which limits their applicability. Here, various engineering principles are identified and computationally explored. Subsequently, various design criteria are used in an experimental design, which were explored in an in vivo study. This resulted in a regression model that enables a more reliable computational design of repression small RNAs.

Binary addition in a living cell based on riboregulation

Synthetic biology aims at (re-)programming living cells like computers to perform new functions for a variety of applications. Initial work rested on transcription factors, but regulatory RNAs have recently gained much attention due to their high programmability. However, functional circuits mainly implemented with regulatory RNAs are quite limited. Here, we report the engineering of a fundamental arithmetic logic unit based on de novo riboregulation to sum two bits of information encoded in molecular concentrations. Our designer circuit robustly performs the intended computation in a living cell encoding the result as fluorescence amplitudes. The whole system exploits post-transcriptional control to switch on tightly silenced genes with small RNAs, together with allosteric transcription factors to sense the molecular signals. This important result demonstrates that regulatory RNAs can be key players in synthetic biology, and it paves the way for engineering more complex RNA-based biocomputers using this designer circuit as a building block.

Bottom-up approaches in synthetic biology and biomaterials for tissue engineering applications

Synthetic biologists use engineering principles to design and construct genetic circuits for programming cells with novel functions. A bottom-up approach is commonly used to design and construct genetic circuits by piecing together functional modules that are capable of reprogramming cells with novel behavior. While genetic circuits control cell operations through the tight regulation of gene expression, a diverse array of environmental factors within the extracellular space also has a significant impact on cell behavior. This extracellular space offers an addition route for synthetic biologists to apply their engineering principles to program cell-responsive modules within the extracellular space using biomaterials. In this review, we discuss how taking a bottom-up approach to build genetic circuits using DNA modules can be applied to biomaterials for controlling cell behavior from the extracellular milieu. We suggest that, by collectively controlling intrinsic and extrinsic signals in synthetic biology and biomaterials, tissue engineering outcomes can be improved.

Next-generation biocontainment systems for engineered organisms

The increasing use of engineered organisms for industrial, clinical, and environmental applications poses a growing risk of spreading hazardous biological entities into the environment. To address this biosafety issue, significant effort has been invested in creating ways to confine these organisms and transgenic materials. Emerging technologies in synthetic biology involving genetic circuit engineering, genome editing, and gene expression regulation have led to the development of novel biocontainment systems. In this perspective, we highlight recent advances in biocontainment and suggest a number of approaches for future development, which may be applied to overcome remaining challenges in safeguard implementation.

Understanding Biological Regulation Through Synthetic Biology

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry—biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Multilevel Regulation of Bacterial Gene Expression with the Combined STAR and Antisense RNA System

Synthetic small RNA regulators have emerged as a versatile tool to predictably control bacterial gene expression. Owing to their simple design principles, small size, and highly orthogonal behavior, these engineered genetic parts have been incorporated into genetic circuits. However, efforts to achieve more sophisticated cellular functions using RNA regulators have been hindered by our limited ability to integrate different RNA regulators into complex circuits. Here, we present a combined RNA regulatory system in Escherichia coli that uses small transcription activating RNA (STAR) and antisense RNA (asRNA) to activate or deactivate target gene expression in a programmable manner. Specifically, we demonstrated that the activated target output by the STAR system can be deactivated by expressing two different types of asRNAs: one binds to and sequesters the STAR regulator, affecting the transcription process, while the other binds to the target mRNA, affecting the translation process. We improved deactivation efficiencies (up to 96%) by optimizing each type of asRNA and then integrating the two optimized asRNAs into a single circuit. Furthermore, we demonstrated that the combined STAR and asRNA system can control gene expression in a reversible way and can regulate expression of a gene in the genome. Lastly, we constructed and simultaneously tested two A AND NOT B logic gates in the same cell to show sophisticated multigene regulation by the combined system. Our approach establishes a methodology for integrating multiple RNA regulators to rationally control multiple genes.