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YpsR, a pivotal regulatory protein in the quorum-sensing (QS) of Yersinia pseudotuberculosis(Y. pstb), is essential for molecular signaling, yet its molecular mechanisms remain poorly understood. Herein, this study systematically investigates the interactions between YpsR and acyl-homoserine lactones (AHLs), shedding light on the selective mechanism of YpsR to various AHL molecules. Using molecular docking and surface plasmon resonance (SPR) analysis, we confirmed YpsR's binding affinities, with the strongest observed for 3OC6-HSL, which notably inhibited Y. pstb growth. Additionally, we engineered a whole-cell biosensor based on YpsR-AHL interaction, which exhibited sensitivity to the signal molecule 3OC6-HSL produced by Y. pstb. Furthermore, key YpsR residues (S32, Y50, W54, D67) involved in AHL binding were identified and validated. Overall, this research elucidates the mechanisms of QS signal recognition in Y. pstb, providing valuable insights that support the development of diagnostic tools for detecting Y. pstb infections.

Genetic circuits can endow microbial cell factories with the ability for self-learning and decision-making. Many standardized formats or automated software are developed to design genetic circuits. Many methods are developed to select and construct genetic parts. Recent advances in synthetic biology have provided a toolbox for constructing high-performance genetic circuits. Genetic circuits are widely employed for the dynamic regulation of metabolic networks and high-throughput screening of overproducers. In recent years, genetic circuit-based regulation of metabolic flux in microbial cell factories has received significant attention. In this review, we describe a pipeline for the design and construction of genetic circuits for metabolic flux optimization. In particular, we summarize the recent advances in computationally assisted prediction of critical metabolic nodes and genetic circuit design automation. Further, we introduce strategies for constructing high-performance genetic circuits. We also summarize the latest applications of genetic circuits in the dynamic regulation of metabolism and high-throughput screening. Finally, we discuss the challenges and prospects associated with the design and construction of sophisticated genetic circuits. Through this review, we aim to provide a theoretical basis for designing and constructing high-performance genetic circuits to optimize metabolic flux. [ABSTRACT FROM AUTHOR]

Decoupling cell formation from recombinant protein synthesis is a potent strategy to intensify bioprocesses. Escherichia coli strains with mutations in the glucose uptake components lack catabolite repression, display low growth rate, no overflow metabolism, and high recombinant protein yields. Fast growth rates were promoted by the simultaneous consumption of glucose and glycerol, and this was followed by a phase of slow growth, when only glucose remained in the medium. A glycerol‐repressible genetic circuit was designed to autonomously induce recombinant protein expression. The engineered strain bearing the genetic circuit was cultured in 3.9 g L−1 glycerol + 18 g L−1 glucose in microbioreactors with online oxygen transfer rate monitoring. The growth was fast during the simultaneous consumption of both carbon sources (C‐sources), while expression of the recombinant protein was low. When glycerol was depleted, the growth rate decreased, and the specific fluorescence reached values 17% higher than those obtained with a strong constitutive promoter. Despite the relatively high amount of C‐source used, no oxygen limitation was observed. The proposed approach eliminates the need for the substrate feeding or inducers addition and is set as a simple batch culture while mimicking fed‐batch performance. [ABSTRACT FROM AUTHOR]

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and classical systems typically studied in non-equilibrium statistical and quantum mechanics.

Synthetic genetic circuits have revolutionised our capacity to control cell viability by conferring microorganisms with programmable functionalities to limit survival to specific environmental conditions. Here, we present the GenoMine safeguard, a CRISPR-Cas9-based kill switch for the biotechnological workhorse Pseudomonas putida that employs repetitive genomic elements as cleavage targets to unleash a highly genotoxic response. To regulate the system’s activation, we tested various circuit-based mechanisms including the digitalised version of an inducible expression system that operates at the transcriptional level and different options of post-transcriptional riboregulators. All of them were applied not only to directly control Cas9 and its lethal effects, but also to modulate the expression of two of its inhibitors: the AcrIIA4 anti-CRISPR protein and the transcriptional repressor TetR. Either upon direct induction of the endonuclease or under non-induced conditions of its inhibitors, the presence of Cas9 suppressed cell survival which could be exploited beyond biocontainment in situations where further CRISPR genome editing is undesirable.

Although a major grain crop, maize is a deficit in Lysine (Lys), which is one of the essential amino acids (EAAs). Several attempts of molecular biology, conventional breeding, marker-assisted breeding, and single/multiple transgenesis have significantly increased Lys content in maize seed. However, till now, no commercial high-Lys maize for human consumption is available in the global market. Therefore, alternative strategies are needed that be adopted over the above-mentioned techniques to develop high-Lys maize. In addition to microbes, circuit-enabled programming-based synthetic biology has significantly improved the desired characteristics of crops including maize as synthetic mini chromosomes have already been built and transferred into maize. The above technology is advantageous as it is a precisely guided artificially controlled system that acts better in addition to the natural system or over the natural system. During the designing and programming of the synthetic genetic circuit for high-Lys maize, a deep understanding of natural Lys biosynthesis pathways, Lys metabolism, metabolic flux, metabolic interconnections, transporters, and transcription factor, post-translational protein regulation are needed. Hence, major genes in aspartate (Asp) pathway, like dihydrodipicolinate synthase (DHPS), aspartate kinase (AK), Lys-ketoglutarate reductase/saccharopine dehydrogenase (LKR/SDH) should be critically analyzed in maize before incorporating these into high-Lys synthetic genetic circuit. Indeed, a prototype of the synthetic high-Lys genetic circuits must have a synthetic switch for precise regulation of multiplex gene expression, memory circuits, synthetic boolean logic gates, and synthetic intercellular communication systems. For proper transformation of the synthetic high-Lys genetic circuit, the landing pad should be specific. Then, precise monitoring and remote regulation of the circuit over several generations might be done to obtain stable programmed high-Lys synthetic maize. Therefore, considering the current advancement of single/multiple transgenesis, conventional breeding, marker-assisted breeding that successfully increased maize Lys, precise programming-based synthetic genetic circuits should be designed for getting high-Lys maize following the mechanism of how the synthetic genetic circuits would work in the maize genome and its remote control. These need deep understanding in maize biology, integration of previously published transgenesis for high-Lys maize, in silico, in vitro and in vivo experiments for successful development of programming-based synthetic genetic circuit enabled high-Lys maize.

Endogenous metabolic pathways in microbial cells are usually precisely controlled by sophisticated regulation networks. However, the lack of such regulations when introducing heterologous pathways in microbial hosts often causes unbalanced enzyme expression and carbon flux distribution, hindering the construction of highly efficient microbial biosynthesis systems. Here, using naringenin as the target compound, we developed an Autonomous Cascaded Artificial Dynamic (AutoCAD) regulation system to automatically coordinate the pathway expression and redirect carbon fluxes for enhanced naringenin production. The AutoCAD regulation system, consisting of both intermediate-based feedforward and product-based feedback control genetic circuits, resulted in a 16.5-fold increase in naringenin titer compared with the static control. Fed-batch fermentation using the strain with AutoCAD regulation further enhanced the naringenin titer to 277.2 mg/L. The AutoCAD regulation system, with intermediate-based feedforward control and product-triggered feedback control, provides a new paradigm of developing complicated cascade dynamic control to engineer heterologous pathways.

Biomaterials have evolved from inert materials to responsive entities, playing a crucial role in disease diagnosis, treatment, and modeling. However, their advancement is hindered by limitations in chemical and mechanical approaches. Synthetic biology enabling the genetically reprograming of biological systems offers a new paradigm. It has achieved remarkable progresses in cell reprogramming, engineering designer cells for diverse applications. Synthetic biology also encompasses cell-free systems and rational design of biological molecules. This review focuses on the application of synthetic biology in theranostics, which boost rapid development of advanced biomaterials. We introduce key fundamental concepts of synthetic biology and highlight frontier applications thereof, aiming to explore the intersection of synthetic biology and biomaterials. This integration holds tremendous promise for advancing biomaterial engineering with programable complex functions.

Advances in synthetic biology have led to the design of biological parts that can be assembled in different ways to perform specific functions. For example, genetic circuits can be designed to execute specific therapeutic functions, including gene therapy or targeted detection and the destruction of invading viruses. Viral infections are difficult to manage through drug treatment. Due to their high mutation rates and their ability to hijack the host's ribosomes to make viral proteins, very few therapeutic options are available. One approach to addressing this problem is to disrupt the process of converting viral RNA into proteins, thereby disrupting the mechanism for assembling new viral particles that could infect other cells. This can be done by ensuring precise control over the abundance of viral RNA (vRNA) inside host cells by designing biological circuits to target vRNA for degradation. RNA-binding proteins (RBPs) have become important biological devices in regulating RNA processing. Incorporating naturally upregulated RBPs into a gene circuit could be advantageous because such a circuit could mimic the natural pathway for RNA degradation. This review highlights the process of viral RNA degradation and different approaches to designing genetic circuits. We also provide a customizable template for designing genetic circuits that utilize RBPs as transcription activators for viral RNA degradation, with the overall goal of taking advantage of the natural functions of RBPs in host cells to activate targeted viral RNA degradation. [ABSTRACT FROM AUTHOR]

The recent development of synthetic biology has expanded the capability to design and construct protein networks outside of living cells from the bottom-up. The new capability has enabled us to assemble protein networks for the basic study of cellular pathways, expression of proteins outside cells, and building tissue materials. Furthermore, the integration of natural and synthetic protein networks has enabled new functions of synthetic or artificial cells. Here, we review the underlying technologies for assembling protein networks in liposomes, water-in-oil droplets, and biomaterials from the bottom-up. We cover the recent applications of protein networks in biological transduction pathways, energy self-supplying systems, cellular environmental sensors, and cell-free protein scaffolds. We also review new technologies for assembling protein networks, including multiprotein purification methods, high-throughput assay screen platforms, and controllable fusion of liposomes. Finally, we present existing challenges towards building protein networks that rival the complexity and dynamic response akin to natural systems. This review addresses the gap in our understanding of synthetic and natural protein networks. It presents a vision towards developing smart and resilient protein networks for various biomedical applications.

The study of synthetic biology focusing on biosensor systems has resulted from a growing interest in developing customized biological devices with desired cellular functions. Recently, biosensors have been used for a variety of medical applications such as disease diagnosis, prevention, rehabilitation, patient health monitoring, and human health management. Meanwhile, the ability to track biomarkers based on biosensors allows researchers and medical practitioners to provide patients with individualized treatment regimens and health management. Biosensors that respond to electrochemical, optical, thermal, piezoelectric and magnetic signals have been developed and utilized for various disease therapies and biomedical applications. This study reviews recent developments in biosensor-based therapeutic tools by sensing diverse biomarkers in many diseases (e.g. cancer, infections, metabolic diseases), such as physical biomarkers (e.g. pressure, temperature) and chemical biomarkers (e.g. dissolved oxygen, glucose). Additionally, we highlight the challenges and problems of biosensor-based therapeutics and possible solutions for biosensor engineering thereof. Current biosensors enable for coarsely programable personal treatment and health management, however, new sensors with optimized dose-response functions, for example, fast response and tight-control performances, could significantly boost versatile uses in medical treatment in the coming future.

With the rapid population growth, the world is witnessing an ever-increasing demand for energy and natural resources. Consequently, soil, air, and water are polluted with diverse pollutants, including heavy metals (HM). The detection of heavy metals is necessary to remediate them, which is achieved with biosensors. Initially, these HM were detected using atomic absorption spectroscopy (AAS), emission spectroscopy, mass spectrometry, gas chromatography etc., but these were costly and time consuming which further paved a way for microbe-based biosensors. The development of genetic circuits for microbe-based biosensors has become more popular in recent years for heavy metal detection. In this review, we have especially discussed the various types of genetic circuits such as toggle switches, logic gates, and amplification modules used in these biosensors as they are used to enhance sensitivity and specificity. Genetic circuits also allow for rapid and multiple analyte detection at the same time. The use of microbial biosensors for the detection of HM in the soil as well as the water is also described below. Although with a higher success rate than classical biosensors, these microbial biosensors still have some drawbacks like bioavailability and size of the analyte which are needed to be addressed. • Genetic circuits in microbial biosensors provide specificity and sensitivity. • Logic gates can detect multiple heavy metals. • Robustness of these biosensors still needs to be addressed. [ABSTRACT FROM AUTHOR]

Advances in synthetic biology have led to the design of biological parts that can be assembled in different ways to perform specific functions. For example, genetic circuits can be designed to execute specific therapeutic functions, including gene therapy or targeted detection and the destruction of invading viruses. Viral infections are difficult to manage through drug treatment. Due to their high mutation rates and their ability to hijack the host’s ribosomes to make viral proteins, very few therapeutic options are available. One approach to addressing this problem is to disrupt the process of converting viral RNA into proteins, thereby disrupting the mechanism for assembling new viral particles that could infect other cells. This can be done by ensuring precise control over the abundance of viral RNA (vRNA) inside host cells by designing biological circuits to target vRNA for degradation. RNA-binding proteins (RBPs) have become important biological devices in regulating RNA processing. Incorporating naturally upregulated RBPs into a gene circuit could be advantageous because such a circuit could mimic the natural pathway for RNA degradation. This review highlights the process of viral RNA degradation and different approaches to designing genetic circuits. We also provide a customizable template for designing genetic circuits that utilize RBPs as transcription activators for viral RNA degradation, with the overall goal of taking advantage of the natural functions of RBPs in host cells to activate targeted viral RNA degradation.

The development of engineered living materials (ELMs) has recently attracted significant attention from researchers across multiple disciplines. Fungi-derived ELMs represent a new type of macroscale, cost-effective, environmentally sustainable materials. However, current fungi-based ELMs either have to undergo a final process to heat-kill the living cells or rely on the co-culture with a model organism for functional modification, which hinders the engineerability and versatility of these materials. In this study, we report a new type of ELMs – grown from programmable Aspergillus niger mycelial pellets – by a simple filtration step under ambient conditions. We demonstrate that A. Niger pellets can provide sufficient cohesion to maintain large-area self-supporting structures even under low pH conditions. Subsequently, by tuning the inducible expression of genes involved in melanin biosynthesis, we verified the fabrication of self-supporting living membrane materials with tunable colors in response to xylose concentration in the surroundings, which can be further explored as a potential biosensor for detecting xylose level in industrial wastewater. Notably, the living materials remain alive, self-regenerative, and functional even after 3-month storage. Thus, beyond reporting a new engineerable fungi chassis for constructing ELMs, our study provides new opportunities for developing bulk living materials for real-world applications such as the production of fabrics, packaging materials, and biosensors.

Systems and Synthetic Biology are complementary fields emerging side-byside into mainstream scientific research. Whilst systems biologists focus on understanding natural systems, synthetic biologists wish to modify, adapt and re-purpose biological systems towards certain desired goals, for example enhancing efficiency and robustness of desired biological traits. In both fields, data analysis, predictive mathematical modelling, experimental design, and controlled experimentation are crucial to obtain reproducible results and understand how applications can be scaled to larger systems and processes. As such, students from Life Sciences, Engineering, and Mathematics backgrounds must be taught fundamentals in biological systems, experimental techniques, mathematics, and data analysis/statistics. In addition, students must be trained for future multidisciplinary careers, where the interaction and communication between experimental and modelling researchers is fundamental. With the acceleration of technological developments (both computational and experimental) continuing unabated, educators need to bridge the increasing gap between fundamentally-required knowledge and skills that students need to pursue future academic or industrial research projects. In this paper, we will discuss how we have re-designed an introductory course in Systems and Synthetic Biology at Wageningen University and Research (Netherlands) that is targeted simultaneously to mathematical/computational students with an interest in biology and experimental methods, and to Life Science students interested in learning how biological systems can be mathematically analysed and modelled. The course highlights the links between fundamental methodologies and recently developed technologies within the Systems and Synthetic Biology fields. The course was re-designed for the 2021/22 academic year, we report that students from biology and biotechnology programmes graded their satisfaction of the course as 4.4 out of 5. We discuss how the course can act as a gateway to advanced courses in Systems Biology-oriented curricula (comprising: data infrastructure, modelling, and experimental synthetic biology), and towards future research projects. [ABSTRACT FROM AUTHOR]

Pulse generator circuits based on incoherent feed-forward logic have been developed in bacterial, yeast, and mammalian systems but are typically limited to production of short pulses lasting less than 1 day. To generate longer-lasting pulses, we introduce a feedback-based topology that induces multiday pulsatile gene expression with tunable duration and amplitude in mammalian cells. We constructed the circuit using the PERSIST platform, which consists of entirely post-transcriptional logic, because our experience suggests that this approach may attenuate long-term epigenetic silencing. To enable external regulation of PERSIST regulatory elements, we engineered inducer-stabilized CRISPR endoRNases that respond to FDA-approved drugs, generating small molecule responses with greater than 20-fold change. These inducer-responsive proteins were connected to a two-state cross-repression positive feedback topology to generate the pulse generator circuit architecture. We then optimized circuit design through chromosomal integration of circuit components at varying stoichiometries, resulting in a small library of circuits displaying tunable pulses lasting between two and 6 days in response to a single 24 h input of inducer. We expect that the small molecule-stabilized PERSIST proteins developed will serve as valuable components in the toolbox for post-transcriptional gene circuit development and that tunable post-transcriptional pulse generator circuits in mammalian cells will enable study of endogenous hysteretic gene networks and support advances in cell therapies and organoid engineering.

Synthetic Notch (synNotch) receptors have enabled mammalian cells to sense extracellular ligands and respond by activating user-prescribed transcriptional programs. Based on the synNotch system, we describe a cell-based in vivo sensor for cancerous cell detection. We attempted to engineer synNotch-programmed macrophages to sense cancer cells via urinary analysis of human chorionic gonadotropin (HCGB5). Principally, when the synNotch receptors of macrophages bind to the ligands of cancer cells, Notch is activated and undergoes intramembrane proteolysis to release the transcriptional activator into the nucleus. The transcriptional activator targets and activates downstream gene expression, such as human chorionic gonadotropin (HCGB5) in macrophages. When HCGB5 is secreted extracellularly into urine, it can be detected with commercial HCGB5 colloidal gold test strips. As a proof of principle, we demonstrated the feasibility of synNotch-programmed macrophages in detecting breast cancer cells engineered with artificial EGFP ligands. We demonstrated that HCGB5 expression was only induced when the cancer cell expressing EGFP ligands is present; thereby, extracellular HCGB5 expression is directly proportional to the number of cancer cells. Further optimizations of the synNotch system can realize the ultimate goal of establishing cell-based in vivo sensors as the paragon of cancer diagnostics for point-of-care testing and home self-test.

Synthetic sRNAs show promise as tools for targeted and programmable gene expression manipulation. However, the design of high-efficiency synthetic sRNAs is a challenging task that necessitates careful consideration of multiple factors. Therefore, this study aims to investigate rational design strategies that significantly and robustly enhance the efficiency of synthetic sRNAs. This is achieved by optimizing the following parameters: the sRNA scaffold, mRNA binding affinity, Hfq protein expression level, and mRNA secondary structure. By utilizing optimized synthetic sRNAs within a positive feedback circuit, we effectively addressed the issue of gene expression leakage─an enduring challenge in synthetic biology that undermines the reliability of genetic circuits in bacteria. Our designed synthetic sRNAs successfully prevented gene expression leakage, thus averting unintended circuit activation caused by initial expression noise, even in the absence of signal molecules. This result shows that high-efficiency synthetic sRNAs not only enable precise gene knockdown for metabolic engineering but also ensure the robust performance of synthetic circuits. The strategies developed here hold significant promise for broad applications across diverse biotechnological fields, establishing synthetic sRNAs as pivotal tools in advancing synthetic biology and gene regulation.

Synthetic genetic circuits have revolutionised our capacity to control cell viability by conferring microorganisms with programmable functionalities to limit survival to specific environmental conditions. Here, we present the GenoMine safeguard, a CRISPR-Cas9-based kill switch for the biotechnological workhorse Pseudomonas putida that employs repetitive genomic elements as cleavage targets to unleash a highly genotoxic response. To regulate the system's activation, we tested various circuit-based mechanisms including the digitalised version of an inducible expression system that operates at the transcriptional level and different options of post-transcriptional riboregulators. All of them were applied not only to directly control Cas9 and its lethal effects, but also to modulate the expression of two of its inhibitors: the AcrIIA4 anti-CRISPR protein and the transcriptional repressor TetR. Either upon direct induction of the endonuclease or under non-induced conditions of its inhibitors, the presence of Cas9 suppressed cell survival which could be exploited beyond biocontainment in situations where further CRISPR genome editing is undesirable., Competing Interests: Author VMdS has interests in LifeGlimmer GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Asin-Garcia, Martin-Pascual, de Buck, Allewijn, Müller and Martins dos Santos.)

Systems and Synthetic Biology are complementary fields emerging side-by-side into mainstream scientific research. Whilst systems biologists focus on understanding natural systems, synthetic biologists wish to modify, adapt and re-purpose biological systems towards certain desired goals, for example enhancing efficiency and robustness of desired biological traits. In both fields, data analysis, predictive mathematical modelling, experimental design, and controlled experimentation are crucial to obtain reproducible results and understand how applications can be scaled to larger systems and processes. As such, students from Life Sciences, Engineering, and Mathematics backgrounds must be taught fundamentals in biological systems, experimental techniques, mathematics, and data analysis/statistics. In addition, students must be trained for future multidisciplinary careers, where the interaction and communication between experimental and modelling researchers is fundamental. With the acceleration of technological developments (both computational and experimental) continuing unabated, educators need to bridge the increasing gap between fundamentally-required knowledge and skills that students need to pursue future academic or industrial research projects. In this paper, we will discuss how we have re-designed an introductory course in Systems and Synthetic Biology at Wageningen University and Research (Netherlands) that is targeted simultaneously to mathematical/computational students with an interest in biology and experimental methods, and to Life Science students interested in learning how biological systems can be mathematically analysed and modelled. The course highlights the links between fundamental methodologies and recently developed technologies within the Systems and Synthetic Biology fields. The course was re-designed for the 2021/22 academic year, we report that students from biology and biotechnology programmes graded their satisfaction of the course as 4.4 out of 5. We discuss how the course can act as a gateway to advanced courses in Systems Biology-oriented curricula (comprising: data infrastructure, modelling, and experimental synthetic biology), and towards future research projects.

Abstract Background Synthetic biological circuits are widely utilized to control microbial cell functions. Natural and synthetic riboswitches are attractive sensor modules for use in synthetic biology applications. However, tuning the fold-change of riboswitch circuits is challenging because a deep understanding of the riboswitch mechanism and screening of mutant libraries is generally required. Therefore, novel molecular parts and strategies for straightforward tuning of the fold-change of riboswitch circuits are needed. Results In this study, we devised a toehold switch-based modulator approach that combines a hybrid input construct consisting of a riboswitch and transcriptional repressor and de-novo-designed riboregulators named toehold switches. First, the introduction of a pair of toehold switches and triggers as a downstream signal-processing module to the hybrid input for coenzyme B12 resulted in a functional riboswitch circuit. Next, several optimization strategies that focused on balancing the expression levels of the RNA components greatly improved the fold-change from 260- to 887-fold depending on the promoter and host strain. Further characterizations confirmed low leakiness and high orthogonality of five toehold switch pairs, indicating the broad applicability of this strategy to riboswitch tuning. Conclusions The toehold switch-based modulator substantially improved the fold-change compared to the previous sensors with only the hybrid input construct. The programmable RNA-RNA interactions amenable to in silico design and optimization can facilitate further development of RNA-based genetic modulators for flexible tuning of riboswitch circuitry and synthetic biosensors.

Pyruvate is a key intermediate that is involved in various synthetic metabolic pathways for microbial chemical and fuel production. It is widely used in the food, chemical, and pharmaceutical industries. However, the microbial production of pyruvate and its derivatives compete with microbial cell growth, as pyruvate is an important metabolic intermediate that serves as a hub for various endogenous metabolic pathways, including gluconeogenesis, amino acid synthesis, TCA cycle, and fatty acid biosynthesis. To achieve a more efficient bioprocess for the production of pyruvate and its derivatives, it is necessary to reduce the metabolic imbalance between cell growth and target chemical production. For this purpose, we devised a dynamic metabolic engineering strategy within an Escherichia coli model, in which a metabolic toggle switch (MTS) was employed to redirect metabolic flux from the endogenous pathway toward the target synthetic pathway. Through a combination of TCA cycle interruption through MTS and reduction of pyruvate consumption in endogenous pathways, we achieved a drastic improvement (163 mM, 26-fold) in pyruvate production. In addition, we demonstrated the redirection of metabolic flux from excess pyruvate toward isobutanol production. The final isobutanol production titer of the strain harboring MTS was 26% improved compared with that of the control strain. [Display omitted] [ABSTRACT FROM AUTHOR]

Cell-free expression systems provide a suite of tools that are used in applications from sensing to biomanufacturing. One of these applications is genetic circuit prototyping, where the lack of cloning is required and a high degree of control over reaction components and conditions enables rapid testing of design candidates. Many studies have shown utility in the approach for characterizing genetic regulation elements, simple genetic circuit motifs, protein variants or metabolic pathways. However, variability in cell-free expression systems is a known challenge, whether between individuals, laboratories, instruments, or batches of materials. While the issue of variability has begun to be quantified and explored, little effort has been put into understanding the implications of this variability. For genetic circuit prototyping, it is unclear when and how significantly variability in reaction activity will impact qualitative assessments of genetic components, e.g. relative activity between promoters. Here, we explore this question by assessing DNA titrations of seven genetic circuits of increasing complexity using reaction conditions that ostensibly follow the same protocol but vary by person, instrument and material batch. Although the raw activities vary widely between the conditions, by normalizing within each circuit across conditions, reasonably consistent qualitative performance emerges for the simpler circuits. For the most complex case involving expression of three proteins, we observe a departure from this qualitative consistency, offering a provisional cautionary line where normal variability may disrupt reliable reuse of prototyping results. Our results also suggest that a previously described closed loop controller circuit may help to mitigate such variability, encouraging further work to design systems that are robust to variability. Graphical Abstract [ABSTRACT FROM AUTHOR]

Transcription factor (TF)-based biosensors are useful synthetic biology tools for applications in a variety of areas of biotechnology. A major challenge of biosensor circuits is the limited repertoire of identified and well-characterized TFs for applications of interest, in addition to the challenge of optimizing selected biosensors. In this work, we implement the IclR family repressor TF TtgV from Pseudomonas putida DOT-T1E as an indole-derivative biosensor in Escherichia coli . We optimize the genetic circuit utilizing different components, providing insights into biosensor design and expanding on previous studies investigating this TF. We discover novel physiologically relevant ligands of TtgV, such as skatole. The broad specificity of TtgV makes it a useful target for directed evolution and protein engineering toward desired specificity. TtgV, as an indole-derivative biosensor, is a promising genetic component for the detection of compounds with biological activities relevant to health and the gut microbiome.

In synthetic biology, microbial chassis including yeast Saccharomyces cerevisiae are iteratively engineered with increasing complexity and scale. Wet-lab genetic engineering tools are developed and optimised to facilitate strain construction but are often incompatible with each other due to shared regulatory elements, such as the galactose-inducible ( GAL ) promoter in S. cerevisiae . Here, we prototyped the cyanamide-induced I- Sce I expression, which triggered double-strand DNA breaks (DSBs) for selectable marker removal. We further combined cyanamide-induced I- Sce I-mediated DSB and maltose-induced MazF-mediated negative selection for plasmid-free in situ promoter substitution, which simplified the molecular cloning procedure for promoter characterisation. We then characterised three tetracycline-inducible promoters showing differential strength, a non-leaky β-estradiol-inducible promoter, cyanamide-inducible DDI2 promoter, bidirectional MAL32/MAL31 promoters, and five pairs of bidirectional GAL1/GAL10 promoters. Overall, alternative regulatory controls for genome engineering tools can be developed to facilitate genomic engineering for synthetic biology and metabolic engineering applications., Competing Interests: Authors declare no conflicts of interest., (© 2024 The Authors.)

Environmental contamination with persistent organic pollutants has emerged as a serious threat of pollution. Bioremediation is a key to eliminate these harmful pollutants from the environment and has gained the interest of researchers during the past few decades. Scientific knowledge upon microbial interactions with individual pollutants over the past decades has helped to abate environmental pollution. Traditional bioremediation approaches have limitations for their applications; hence, it is essential to discover new bioremediation approaches with biotechnological interventions for best results. The developments in various methodologies are expected to increase the efficiency of bioremediation techniques and provide environmentally sound strategies. This paper deals with the profiling of microorganisms present in polluted sites using various techniques such as culture-based approaches and omics-based approaches. Besides this, it also provides up-to-date scientific literature on the microbial electrochemical technologies which are nowadays considered as the best approach for remediation of pollutants. Detailed information about future outlook and challenges to evaluate the effect of various treatment technologies for remediation of pollutants has been discussed. [ABSTRACT FROM AUTHOR]

Control of gene expression is crucial for several biotechnological applications, especially for implementing predictable and controllable genetic circuits. Such circuits are often implemented with a transcriptional regulator activated by a specific signal. These regulators should work independently of the host machinery, with low gratuitous induction or crosstalk with host components. Moreover, the signal should also be orthogonal, recognized only by the regulator with minimal interference with the host operation. In this context, transcriptional regulators activated by plant metabolites as flavonoids emerge as candidates to control gene expression in bacteria. However, engineering novel circuits requires the characterization of the genetic parts (e.g., genes, promoters, ribosome binding sites, and terminators) in the host of interest. Therefore, we decomposed the QdoR regulatory system of B. subtilis, responsive to the flavonoid quercetin, and reassembled its parts into genetic circuits programmed to have different levels of gene expression and noise dependent on the concentration of quercetin. We showed that only one of the promoters regulated by QdoR worked well in E. coli, enabling the construction of other circuits induced by quercetin. The QdoR expression was modulated with constitutive promoters of different transcriptional strengths, leading to low expression levels when QdoR was highly expressed and vice versa. E. coli strains expressing high and low levels of QdoR were mixed and induced with the same quercetin concentration, resulting in two stable populations expressing different levels of their gene reporters. Besides, we demonstrated that the level of QdoR repression generated different noise levels in gene expression dependent on the concentration of quercetin. The circuits presented here can be exploited in applications requiring adjustment of gene expression and noise using a highly available and natural inducer as quercetin.

Background: Synthetic biological circuits are widely utilized to control microbial cell functions. Natural and synthetic riboswitches are attractive sensor modules for use in synthetic biology applications. However, tuning the fold-change of riboswitch circuits is challenging because a deep understanding of the riboswitch mechanism and screening of mutant libraries is generally required. Therefore, novel molecular parts and strategies for straightforward tuning of the fold-change of riboswitch circuits are needed. Results: In this study, we devised a toehold switch-based modulator approach that combines a hybrid input construct consisting of a riboswitch and transcriptional repressor and de-novo-designed riboregulators named toehold switches. First, the introduction of a pair of toehold switches and triggers as a downstream signal-processing module to the hybrid input for coenzyme B12 resulted in a functional riboswitch circuit. Next, several optimization strategies that focused on balancing the expression levels of the RNA components greatly improved the fold-change from 260- to 887-fold depending on the promoter and host strain. Further characterizations confirmed low leakiness and high orthogonality of five toehold switch pairs, indicating the broad applicability of this strategy to riboswitch tuning. Conclusions: The toehold switch-based modulator substantially improved the fold-change compared to the previous sensors with only the hybrid input construct. The programmable RNA-RNA interactions amenable to in silico design and optimization can facilitate further development of RNA-based genetic modulators for flexible tuning of riboswitch circuitry and synthetic biosensors. [ABSTRACT FROM AUTHOR]

Genetic circuits have been developed for quantitative measurement of enzyme activity, metabolic engineering of strain development, and dynamic regulation of microbial cells. A genetic circuit consists of several bio-elements, including enzymes and regulatory cassettes, that can generate the desired output signal, which is then used as a precise criterion for enzyme screening and engineering. Antagonists and inhibitors are small molecules with inhibitory effects on regulators and enzymes, respectively. In this study, an antagonist and an inhibitor were applied to a genetic circuit for a dynamic detection range. We developed a genetic circuit relying on regulators and enzymes, allowing for straightforward control of its output signal without additional genetic modification. We used para-nitrophenol and alanine as an antagonist of DmpR and inhibitor of tyrosine phenol-lyase, respectively. We show that the antagonist resets the detection range of the genetic circuit similarly to a resistor in an electrical logic circuit. These biological resistors in genetic circuits can be used as a rapid and precise controller of variable outputs with minimal circuit configuration.

Methylating chemicals are common in industry and agriculture and are often toxic, partly due to their propensity to methylate DNA. The Escherichia coli Ada protein detects methylating compounds by sensing aberrant methyl adducts on the phosphoester backbone of DNA. We characterize this system as a genetic sensor and engineer it to lower the detection threshold. By overexpressing Ada from a plasmid, we improve the sensor’s dynamic range to 350-fold induction and lower its detection threshold to 40 μM for methyl iodide. In eukaryotes, there is no known sensor of methyl adducts on the phosphoester backbone of DNA. By fusing the N-terminal domain of Ada to the Gal4 transcriptional activation domain, we built a functional sensor for methyl phosphotriester adducts in Saccharomyces cerevisiae. This sensor can be tuned to variable specifications by altering the expression level of the chimeric sensor and changing the number of Ada operators upstream of the Gal4-sensitive reporter promoter. These changes result in a detection threshold of 28 μM and 5.2-fold induction in response to methyl iodide. When the yeast sensor is exposed to different SN1 and SN2 alkylating compounds, its response profile is similar to that observed for the native Ada protein in E. coli, indicating that its native function is retained in yeast. Finally, we demonstrate that the specifications achieved for the yeast sensor are suitable for detecting methylating compounds at relevant concentrations in environmental samples. This work demonstrates the movement of a sensor from a prokaryotic to eukaryotic system and its rational tuning to achieve desired specifications.

RNA sensing in vivo evaluates past or ongoing endogenous RNA disturbances, which is crucial for identifying cell types and states and diagnosing diseases. Recently, the CRISPR-driven genetic circuits have offered promising solutions to burgeoning challenges in RNA sensing. This review delves into the cutting-edge developments of CRISPR-powered RNA sensors in vivo, reclassifying these RNA sensors into four categories based on their working mechanisms, including programmable reassembly of split single-guide RNA (sgRNA), RNA-triggered RNA processing and protein cleavage, miRNA-triggered RNA interference (RNAi), and strand displacement reactions. Then, we discuss the advantages and challenges of existing methodologies in diverse application scenarios and anticipate and analyze obstacles and opportunities in forthcoming practical implementations., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Functionalizing materials with biomacromolecules such as enzymes has broad applications in biotechnology and biomedicine. Here, we introduce a grafting method mediated by living cells to functionalize materials. We use polymeric scaffolds to trap engineered bacteria and micron-sized particles with chemical groups serving as active sites for grafting. The bacteria synthesize the desired protein for grafting and autonomously lyse to release it. The released functional moieties are locally grafted onto the active sites, generating the materials engineered by living grafting (MELGs). MELGs are resilient to perturbations because of both the bonding and the regeneration of functional domains synthesized by living cells. The programmability of the bacteria enables us to fabricate MELGs that can respond to external input, decompose a pollutant, reconstitute synthetic pathways for natural product synthesis, and purify mismatched DNA. Our work establishes a bacteria-assisted grafting strategy to functionalize materials with a broad range of biological activities in an integrated, flexible, and modular manner. A record of this paper's transparent peer review process is included in the supplemental information., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Synthetic biology aims to engineer biological systems for customized tasks through the bottom-up assembly of fundamental building blocks, which requires high-quality libraries of reliable, modular, and standardized genetic parts. To establish sets of parts that work well together, synthetic biologists created standardized part libraries in which every component is analyzed in the same metrics and context. Here we present a state-of-the-art review of the currently available part libraries for designing biocircuits and their gene expression regulation paradigms at transcriptional, translational, and post-translational levels in Escherichia coli . We discuss the necessary facets to integrate these parts into complex devices and systems along with the current efforts to catalogue and standardize measurement data. To better display the range of available parts and to facilitate part selection in synthetic biology workflows, we established biopartsDB, a curated database of well-characterized and useful genetic part and device libraries with detailed quantitative data validated by the published literature.

Transcription can be regulated by controlling the provision of transcriptional factors (TFs), because TFs determine the transcription process by specifying the binding of RNA polymerase holoenzyme on promoters. Manipulations, such as replacing endogenous TFs with mutants obtained through directed evolution (or rational design), and introducing compatible heterogeneous TFs, are effective ways to regulate transcription. Designing artificial TFs with desired properties by following the principles of protein design and reconstructing ancestral TFs with the information gained from a perspective of evolution by multiple sequence alignments of the related TFs, are feasible alternative options. The engineered TFs can be used to create inducible protein expression systems that respond to a specific stimulus. Moreover, the engineered TFs could lead to a transcriptional profile different from that of the wild‐type strains. Accordingly, these engineered TFs could be utilized to construct strains resistant to adverse conditions, since the emergence of resistance generally requires global transcriptional changes at the transcriptomic scale. Meanwhile, these engineered TFs can also be employed in the construction of sophisticatedly designed genetic circuits for diverse purposes. In this paper, we reviewed the advances in the above‐mentioned aspects. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.

Continuous contamination of the environment with xenobiotics and related recalcitrant compounds has emerged as a serious pollution threat. Bioremediation is the key to eliminating persistent contaminants from the environment. Traditional bioremediation processes show limitations, therefore it is necessary to discover new bioremediation technologies for better results. In this review we provide an outlook of alternative strategies for bioremediation via synthetic biology, including exploring the prerequisites for analysis of research data for developing synthetic biological models of microbial bioremediation. Moreover, cell coordination in synthetic microbial community, cell signaling, and quorum sensing as engineered for enhanced bioremediation strategies are described, along with promising gene editing tools for obtaining the host with target gene sequences responsible for the degradation of recalcitrant compounds. The synthetic genetic circuit and two-component regulatory system (TCRS)-based microbial biosensors for detection and bioremediation are also briefly explained. These developments are expected to increase the efficiency of bioremediation strategies for best results.

Abstract A primary objective of synthetic biology is the construction of genetic circuits with behaviors that can be predicted based on the properties of the constituent genetic parts from which they are built. However a significant issue in the construction of synthetic genetic circuits is a phenomenon known as context dependence in which the behavior of a given part changes depending on the choice of adjacent or nearby parts. Interactions between parts compromise the modularity of the circuit, impeding the implementation of predictable genetic constructs. To address this issue, investigators have devised genetic insulators that prevent these unintended context-dependent interactions between neighboring parts. One of the most commonly used insulators in bacterial systems is the self-cleaving ribozyme RiboJ. Despite its utility as an insulator, there has been no systematic quantitative assessment of the effect of RiboJ on the expression level of downstream genetic parts. Here, we characterized the impact of insulation with RiboJ on expression of a reporter gene driven by a promoter from a library of 24 frequently employed constitutive promoters in an Escherichia coli model system. We show that, depending on the strength of the promoter, insulation with RiboJ increased protein abundance between twofold and tenfold and increased transcript abundance by an average of twofold. This result demonstrates that genetic insulators in E. coli can impact the expression of downstream genes, information that is essential for the design of predictable genetic circuits and constructs.

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs. [ABSTRACT FROM AUTHOR]

Continuous contamination of the environment with xenobiotics and related recalcitrant compounds has emerged as a serious pollution threat. Bioremediation is the key to eliminating persistent contaminants from the environment. Traditional bioremediation processes show limitations, therefore it is necessary to discover new bioremediation technologies for better results. In this review we provide an outlook of alternative strategies for bioremediation via synthetic biology, including exploring the prerequisites for analysis of research data for developing synthetic biological models of microbial bioremediation. Moreover, cell coordination in synthetic microbial community, cell signaling, and quorum sensing as engineered for enhanced bioremediation strategies are described, along with promising gene editing tools for obtaining the host with target gene sequences responsible for the degradation of recalcitrant compounds. The synthetic genetic circuit and two-component regulatory system (TCRS)-based microbial biosensors for detection and bioremediation are also briefly explained. These developments are expected to increase the efficiency of bioremediation strategies for best results. [ABSTRACT FROM AUTHOR]

Quorum sensing (QS), a microbial cell-to-cell communication process, dynamically regulates a variety of metabolism and physiological activities. In this review, we provide an update on QS applications based on autoinducer molecules including acyl-homoserine lactones (AHLs), auto-inducing peptides (AIPs), autoinducer 2 (AI-2) and indole in population-level control of bacteria, and highlight the potential in developing novel clinical therapies. We summarize the development in the combination of various genetic circuits such as genetic oscillators, toggle switches and logic gates with AHL-based QS devices in Gram-negative bacteria. An overview is then offered to the state-of-the-art of much less researched applications of AIP-based QS devices with Gram-positive bacteria, followed by a review of the applications of AI-2 and indole based QS for interspecies communication among microbial communities. Building on these general-purpose QS applications, we highlight the disruptions and manipulations of QS devices as potential clinical therapies for diseases caused by biofilm formation, antibiotic resistance and the phage invasion. The last part of reviewed literature is dedicated to mathematical modelling for QS applications. Finally, the key challenges and future perspectives of QS applications in monoclonal synthetic biology and synthetic ecology are discussed. [ABSTRACT FROM AUTHOR]