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

Keratinocyte derived HMGB1 aggravates psoriasis dermatitis via facilitating inflammatory polarization of macrophages and hyperproliferation of keratinocyte

Psoriasis is one of the most common immune-mediated chronic inflammatory skin diseases, involving excessive proliferation of keratinocyte and infiltration of immune cells. There are many factors that cause the onset of psoriasis, so the exact pathogenesis of psoriasis still needs to be determined. High mobility group box-1 (HMGB1), a pro-inflammatory cytokine, is closely related to the pathogenesis of various inflammatory diseases. However, there are few studies investigating the effects of HMGB1 on inflammatory dermatoses. Here, we found that keratinocyte in the the IMQ-treated skin lesions of psoriasis model mice expressed more HMGB1. Notably, HMGB1 produced by keratinocyte could promote the activation of inflammatory type macrophages without affecting the polarization of anti-inflammatory type macrophages. Meanwhile, the proportion of M1 type macrophages in the skin lesions is significantly increased. Moreover, local clearance of macrophages in the skin could alleviate psoriasis like inflammation. Finally, keratinocyte-derived HMGB1 could also act on itself in turn, promoting the excessive proliferation and the mRNA expression of inflammatory cytokines of keratinocyte. Therefore, this study not only found the effect of HMGB1 on the hyperproliferation of keratinocyte, but also revealed that keratinocyte could communicate with macrophages through HMGB1, thereby facilitating macrophage inflammatory polarization. Collectively, these findings have clinical significance for the research and treatment of psoriasis, HMGB1 may become a potential target for the treatment of psoriasis.

Tailored Synthetic sRNAs Dynamically Tune Multilayer Genetic Circuits

Predictable and controllable tuning of genetic circuits to regulate gene expression, including modulation of existing circuits or constructs without the need for redesign or rebuilding, is a persistent challenge in synthetic biology. Here, we propose rationally designed new small RNAs (sRNAs) that dynamically modulate gene expression of genetic circuits with a broad range (high, medium, and low) of repression. We designed multiple multilayer genetic circuits in which the variable effector element is a transcription factor (TF) controlling downstream the production of a reporter protein. The sRNAs target TFs instead of a reporter gene, and harnessing the intrinsic RNA-interference pathway in E. coli allowed for a wide range of expression modulation of the reporter protein, including the most difficult to achieve dynamic switch to an OFF state. The synthetic sRNAs are expressed independently of the circuit(s), thus allowing for repression without modifying the circuit itself. Our work provides a frame for achieving independent modulation of gene expression and dynamic and modular control of the multilayer genetic circuits by only including an independent control circuit expressing synthetic sRNAs, without altering the structure of existing genetic circuits.

A Multi-Layer-Controlled Strategy for Cloning and Expression of Toxin Genes in Escherichia coli

Molecular cloning and controlled expression remain challenging when the target gene encodes a protein that is toxic to the host. We developed a set of multi-layer control systems to enable cloning of genes encoding proteins known to be highly toxic in Escherichia coli and other bacteria. The different multi-layer control systems combine a promoter-operator system on a transcriptional level with a riboswitch for translational control. Additionally, replicational control is ensured by using a strain that reduces the plasmid copy number. The use of weaker promoters (such as PBAD or PfdeA) in combination with the effective theophylline riboswitch is essential for cloning genes that encode notoriously toxic proteins that directly target translation and transcription. Controlled overexpression is possible, allowing the system to be used for evaluating in vivo effects of the toxin. Systems with a stronger promoter can be used for successful overexpression and purification of the desired protein but are limited to toxins that are more moderate and do not interfere with their own production.

Identifying Antisense Oligonucleotides to Disrupt Small RNA Regulated Antibiotic Resistance via a Cell-Free Transcription-Translation Platform

Bacterial small RNAs (sRNAs) regulate many important physiological processes in cells, including antibiotic resistance and virulence genes, through base-pairing interactions with mRNAs. Antisense oligonucleotides (ASOs) have great potential as therapeutics against bacterial pathogens by targeting sRNAs such as MicF, which regulates outer membrane protein OmpF expression and limits the permeability of antibiotics. Here we devised a cell-free transcription-translation (TX-TL) assay to identify ASO designs that sufficiently sequester MicF. ASOs were then ordered as peptide nucleic acids conjugated to cell-penetrating peptides (CPP-PNA) to allow for effective delivery into bacteria. Subsequent minimum inhibitory concentration (MIC) assays demonstrated that simultaneously targeting the regions of MicF responsible for sequestering the start codon and the Shine-Dalgarno sequence of ompF with two different CPP-PNAs synergistically reduced the MIC for a set of antibiotics. This investigation offers a TX-TL-based approach to identify novel therapeutic candidates to combat intrinsic sRNA-mediated antibiotic resistance mechanisms.

Base editing enables duplex point mutagenesis in Clostridium autoethanogenum at the price of numerous off-target mutations

Base editors are recent multiplex gene editing tools derived from the Cas9 nuclease of Streptomyces pyogenes. They can target and modify a single nucleotide in the genome without inducing double-strand breaks (DSB) of the DNA helix. As such, they hold great potential for the engineering of microbes that lack effective DSB repair pathways such as homologous recombination (HR) or non-homologous end-joining (NHEJ). However, few applications of base editors have been reported in prokaryotes to date, and their advantages and drawbacks have not been systematically reported. Here, we used the base editors Target-AID and Target-AID-NG to introduce nonsense mutations into four different coding sequences of the industrially relevant Gram-positive bacterium Clostridium autoethanogenum. While up to two loci could be edited simultaneously using a variety of multiplexing strategies, most colonies exhibited mixed genotypes and most available protospacers led to undesired mutations within the targeted editing window. Additionally, fifteen off-target mutations were detected by sequencing the genome of the resulting strain, among them seven single-nucleotide polymorphisms (SNP) in or near loci bearing some similarity with the targeted protospacers, one 15 nt duplication, and one 12 kb deletion which removed uracil DNA glycosylase (UDG), a key DNA repair enzyme thought to be an obstacle to base editing mutagenesis. A strategy to process prokaryotic single-guide RNA arrays by exploiting tRNA maturation mechanisms is also illustrated.

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.

Model-Based Design of Synthetic Antisense RNA for Predictable Gene Repression

Our enhanced understanding of RNA folding and function has increased the use of small RNA regulators. Among these RNA regulators, synthetic antisense RNA (asRNA) is designed to contain an RNA sequence complementary to the target mRNA sequence, and the formation of double-stranded RNA (dsRNA) facilitates gene repression due to dsRNA degradation or prevention of ribosome access to the mRNA. Despite the simple complementarity rule, however, predictably tunable repression has been challenging when synthetic asRNAs are used. Here, the protocol for model-based asRNA design is described. This model can predict synthetic asRNA-mediated repression efficiency using two parameters: the change in free energy of complex formation (ΔG_CF) and percent mismatch of the target binding region (TBR). The model has been experimentally validated in both Gram-positive and Gram-negative bacteria as well as for target genes in both plasmids and chromosomes. These asRNAs can be created by simply replacing the TBR sequence with one that is complementary to the target mRNA sequence of interest. In principle, this protocol can be applied to design and build asRNAs for predictable gene repression in various contexts, including multiple target genes and organisms, making asRNAs predictably tunable regulators for broad applications.

RNA Compensation: A Positive Feedback Insulation Strategy for RNA-Based Transcription Networks

The lack of signaling modularity of biomolecular systems poses major challenges toward engineering complex networks. Directional signaling between an upstream and a downstream circuit requires the presence of binding events, which result in the consumption of regulatory molecules and can compromise the operation of the upstream circuit. This issue has been previously addressed by introducing insulation strategies that include high-gain negative feedback and activation-deactivation reaction cycles. In this paper, we focus on RNA-based circuits and propose a new positive-feedback strategy to mitigate signal consumption that we propose occurs for each regulatory event due to irreversible binding of the RNA input to the RNA target. To mitigate this, an extra RNA input is added in tandem with transcription output to compensate the RNA consumption, leading to concentration robustness of the input RNA molecule regardless of the amount of downstream modules. We term this strategy RNA compensation, and it can be applied to systems that have a stringent input-output gain, such as Small Transcription Activating RNAs (STARs). Our theoretical analysis shows that RNA compensation not only eliminates the signaling consumption in individual STAR-based regulators, but also improves the composability of STAR cascades and the modularity of RNA bistable systems.

An operator-based expression toolkit for Bacillus subtilis enables fine-tuning of gene expression and biosynthetic pathway regulation

A gene regulatory system is an important tool for the engineering of biosynthetic pathways of organisms. Here, we report the development of an inducible-ON/OFF regulatory system using a malO operator as a key element. We identified and modulated sequence, position, numbers, and spacing distance of malO operators, generating a series of activating or repressive promoters with tunable strength. The stringency and robustness are both guaranteed in this system, a maximal induction factor of 790-fold was achieved, and nine proteins from different organisms were expressed with high yields. This system can be utilized as a gene switch, promoter enhancer, or metabolic valve in synthetic biology applications. This operator-based engineering strategy can be employed for developing similar regulatory systems in different microorganisms.

Genetic elements are key components of metabolic engineering and synthetic biological applications, allowing the development of organisms as biosensors and for manufacturing valuable chemicals and protein products. In contrast to the gram-negative model bacterium Escherichia coli, the gram-positive model bacterium Bacillus subtilis lacks such elements with precise and flexible characteristics, which is a great barrier to employing B. subtilis for laboratory studies and industrial applications. Here, we report the development of a malO-based genetic toolbox that is derived from the operator box in the malA promoter, enabling gene regulation via compatible “ON” and “OFF” switches. This engineered toolbox combines promoter-based mutagenesis and host-specific metabolic engineering of transactivation components upon maltose induction to achieve stringent, robust, and homogeneous gene regulation in B. subtilis. We further demonstrate the synthetic biological applications of the toolbox by utilizing these genetic elements as a gene switch, a promoter enhancer, and an ON-OFF dual-control device in biosynthetic pathway optimization. Collectively, this regulatory system provides a comprehensive genetic toolbox for controlling the expression of genes in biosynthetic pathways and regulatory networks to optimize the production of valuable chemicals and proteins in B. subtilis.

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.

A dynamic and multilocus metabolic regulation strategy using quorum-sensing-controlled bacterial small RNA

Metabolic regulation strategies have been developed to redirect metabolic fluxes to production pathways. However, it is difficult to screen out target genes that, when repressed, improve yield without affecting cell growth. Here, we report a strategy using a quorum-sensing system to control small RNA transcription, allowing cell-density-dependent repression of target genes. This strategy is shown with convenient operation, dynamic repression, and availability for simultaneous regulation of multiple genes. The parameters A_i, A_m, and R_A (3-oxohexanoyl-homoserine lactone [AHL] concentrations at which half of the maximum repression and the maximum repression were reached and value of the maximum repression when AHL was added manually, respectively) are defined and introduced to characterize repression curves, and the variant LuxR_I58N is identified as the most suitable tuning factor for shake flask culture. Moreover, it is shown that dynamic overexpression of the Hfq chaperone is the key to combinatorial repression without disruptions on cell growth. To show a broad applicability, the production titers of pinene, pentalenene, and psilocybin are improved by 365.3%, 79.5%, and 302.9%, respectively, by applying combinatorial dynamic repression.

Recent advances in tuning the expression and regulation of genes for constructing microbial cell factories

To overcome environmental problems caused by the use of fossil resources, microbial cell factories have become a promising technique for the sustainable and eco-friendly development of valuable products from renewable resources. Constructing microbial cell factories with high titers, yields, and productivity requires a balance between growth and production; to this end, tuning gene expression and regulation is necessary to optimise and precisely control complicated metabolic fluxes. In this article, we review the current trends and advances in tuning gene expression and regulation and consider their engineering at each of the three stages of gene regulation: genomic, mRNA, and protein. In particular, the technological approaches utilised in a diverse range of genetic-engineering-based tools for the construction of microbial cell factories are reviewed and representative applications of these strategies are presented. Finally, the prospects for strategies and systems for tuning gene expression and regulation are discussed.

Recent Innovations in Bacterial Infection Detection and Treatment

Bacterial infections are a major threat to human health, exacerbated by increasing antibiotic resistance. These infections can result in tremendous morbidity and mortality, emphasizing the need to identify and treat pathogenic bacteria quickly and effectively. Recent developments in detection methods have focused on electrochemical, optical, and mass-based biosensors. Advances in these systems include implementing multifunctional materials, microfluidic sampling, and portable data-processing to improve sensitivity, specificity, and ease of operation. Concurrently, advances in antibacterial treatment have largely focused on targeted and responsive delivery for both antibiotics and antibiotic alternatives. Antibiotic alternatives described here include repurposed drugs, antimicrobial peptides and polymers, nucleic acids, small molecules, living systems, and bacteriophages. Finally, closed-loop therapies are combining advances in the fields of both detection and treatment. This review provides a comprehensive summary of the current trends in detection and treatment systems for bacterial infections.

Ultrasensitive molecular controllers for quasi-integral feedback

Feedback control has enabled the success of automated technologies by mitigating the effects of variability, unknown disturbances, and noise. While it is known that biological feedback loops reduce the impact of noise and help shape kinetic responses, many questions remain about how to design molecular integral controllers. Here, we propose a modular strategy to build molecular quasi-integral feedback controllers, which involves following two design principles. The first principle is to utilize an ultrasensitive response, which determines the gain of the controller and influences the steady-state error. The second is to use a tunable threshold of the ultrasensitive response, which determines the equilibrium point of the system. We describe a reaction network, named brink controller, that satisfies these conditions by combining molecular sequestration and an activation/deactivation cycle. With computational models, we examine potential biological implementations of brink controllers, and we illustrate different example applications.

Third Generation Whole-Cell Sensing Systems: Synthetic Biology Inside, Nanomaterial Outside

Whole-cell sensing systems (WCSSs) are highly anticipated in the field of on-site detection. However, due to their low specificity, poor stability, and potential environmental problems, their commercial application is unrealistic. Recently, synthetic biology and nanomaterials have provided potential solutions to these problems, propelling WCSSs into a new generation. Synthetic biology provides a complete solution for the intelligent design and assembly of elements, modules, and genetic circuits. Nanomaterials covering the exterior of the cells provide stable protection, remote control capability, and catalytic ability for the WCSSs, and they can limit the horizontal transfer of genetic elements. These advancements enable personalized customization, intelligent control, and self-destruction in the next generation of cell sensors, promoting their industrialization.

Keratinocyte: A trigger or an executor of psoriasis?

Psoriasis is a common chronic inflammatory skin disease characterized by abnormal proliferation/differentiation of keratinocytes and excessive immune cell infiltration in the dermis and epidermis. Over the past 2 decades, immune cells have been considered as the main driver of psoriasis because the neutralizing antibodies targeting the IL-23/IL-17 axis that regulates cross-talk between dendritic cells and T cells achieve tremendous success in the treatment of psoriasis. However, whether keratinocyte would be a driver of psoriasis or just an executor in response to immune cells is still under debate. In this review, we focus on the recent advances in the identification of keratinocyte as a trigger of psoriasis, summarize on the role of keratinocytes in self-perpetuating loop to maintain inflammation in psoriasis, and then discuss the possible roles of keratinocytes in the relapse of psoriasis.

Extremely Low Leakage Expression Systems Using Dual Transcriptional-Translational Control for Toxic Protein Production

Expression systems for highly toxic protein genes must be conditional and suppress leakage expression to almost zero because even faint leakage expression may kill host cells, inhibit host growth, and cause loss of plasmids containing the toxic protein genes. The most widely used conditional expression systems are controlled only at the transcriptional level, and complete suppression of leakage expression is challenging. Recent progress on translational control has enabled construction of dual transcriptional-translational control systems in which leakage expression is strongly suppressed. This review summarizes the principles, features, and practical examples of dual transcriptional-translational control systems in bacteria, and provides future perspectives on these systems.

Cell-Free Prototyping of AND-Logic Gates Based on Heterogeneous RNA Activators

RNA-based devices controlling gene expression bear great promise for synthetic biology, as they offer many advantages such as short response times and light metabolic burden compared to protein-circuits. However, little work has been done regarding their integration to multilevel regulated circuits. In this work, we combined a variety of small transcriptional activator RNAs (STARs) and toehold switches to build highly effective AND-gates. To characterize the components and their dynamic range, we used an Escherichia coli (E. coli) cell-free transcription-translation (TX-TL) system dispensed via nanoliter droplets. We analyzed a prototype gate in vitro as well as in silico, employing parametrized ordinary differential equations (ODEs), for which parameters were inferred via parallel tempering, a Markov chain Monte Carlo (MCMC) method. On the basis of this analysis, we created nine additional AND-gates and tested them in vitro. The functionality of the gates was found to be highly dependent on the concentration of the activating RNA for either the STAR or the toehold switch. All gates were successfully implemented in vivo, offering a dynamic range comparable to the level of protein circuits. This study shows the potential of a rapid prototyping approach for RNA circuit design, using cell-free systems in combination with a model prediction.

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.

Modulating Responses of Toehold Switches by an Inhibitory Hairpin

The toehold switch consists of a cis-repressing switch RNA hairpin and a trans-acting trigger RNA. The binding of the trigger RNA to an unpaired toehold sequence of the switch hairpin allows for a branch migration process, exposing the start codon and ribosome binding site for translation initiation. In this work, we demonstrate that responses of toehold switches can be modulated by introducing an inhibitory hairpin that shortens the length of the unpaired toehold region. First, we investigated the effect of the toehold region length on output gene expression and showed that the second trigger RNA, which binds to the inhibitory hairpin, is necessary for output gene activation when the hairpin-to-hairpin spacing is short. Second, the apparent Hill coefficient was found generally to increase with decreasing hairpin-to-hairpin spacing or increasing hairpin number. This work expands the utility of toehold switches by providing a new way to modulate their response.

Designing Spatially Distributed Gene Regulatory Networks To Elicit Contrasting Patterns

Pattern formation and differential interactions are important for microbial consortia to divide labor and perform complex functions. To obtain further insight into such interactions, we present a computational method for simulating physically separated microbial colonies, each implementing different gene regulatory networks. We validate our theory by experimentally demonstrating control over gene expression patterns in a diffusion-mediated lateral inhibition circuit. We highlight the importance of spatial arrangement as a control knob for modulating system behavior. Our systematic approach provides a foundation for future applications that require understanding and engineering of multistrain microbial communities for sophisticated, synergistic functions.

Establishing a Multivariate Model for Predictable Antisense RNA-Mediated Repression

Recent advances in our understanding of RNA folding and functions have facilitated the use of regulatory RNAs such as synthetic antisense RNAs (asRNAs) to modulate gene expression. However, despite the simple and universal complementarity rule, predictable asRNA-mediated repression is still challenging due to the intrinsic complexity of native asRNA-mediated gene regulation. To address this issue, we present a multivariate model, based on the change in free energy of complex formation (Δ G_CF) and percent mismatch of the target binding region, which can predict synthetic asRNA-mediated repression efficiency in diverse contexts. First, 69 asRNAs that bind to multiple target mRNAs were designed and tested to create the predictive model. Second, we showed that the same model is effective predicting repression of target genes in both plasmids and chromosomes. Third, using our model, we designed asRNAs that simultaneously modulated expression of a toxin and its antitoxin to demonstrate tunable control of cell growth. Fourth, we tested and validated the same model in two different biotechnologically important organisms: Escherichia coli Nissle 1917 and Bacillus subtilis 168. Last, multiple parameters, including target locations, the presence of an Hfq binding site, GC contents, and gene expression levels, were revisited to define the conditions under which the multivariate model should be used for accurate prediction. Together, 434 different strain-asRNA combinations were tested, validating the predictive model in a variety of contexts, including multiple target genes and organisms. The result presented in this study is an important step toward achieving predictable tunability of asRNA-mediated repression.

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.