Riboswitch-inspired toehold riboregulators for gene regulation in Escherichia coli

Advancing microbial production through artificial intelligence-aided biology

Microbial cell factories (MCFs) have been leveraged to construct sustainable platforms for value-added compound production. To optimize metabolism and reach optimal productivity, synthetic biology has developed various genetic devices to engineer microbial systems by gene editing, high-throughput protein engineering, and dynamic regulation. However, current synthetic biology methodologies still rely heavily on manual design, laborious testing, and exhaustive analysis. The emerging interdisciplinary field of artificial intelligence (AI) and biology has become pivotal in addressing the remaining challenges. AI-aided microbial production harnesses the power of processing, learning, and predicting vast amounts of biological data within seconds, providing outputs with high probability. With well-trained AI models, the conventional Design-Build-Test (DBT) cycle has been transformed into a multidimensional Design-Build-Test-Learn-Predict (DBTLP) workflow, leading to significantly improved operational efficiency and reduced labor consumption. Here, we comprehensively review the main components and recent advances in AI-aided microbial production, focusing on genome annotation, AI-aided protein engineering, artificial functional protein design, and AI-enabled pathway prediction. Finally, we discuss the challenges of integrating novel AI techniques into biology and propose the potential of large language models (LLMs) in advancing microbial production.

Design of a self-regulating mRNA gene circuit

Protein expression in vivo is predominately controlled via regulatory feedback mechanisms that adjust the level of mRNA transcription. However for positive sense single-stranded RNA viruses, protein expression is often controlled via secondary structural elements, such as internal ribosomal entry sites, that are encoded within the mRNA. The self-regulation of mRNA translation observed in this class of viruses suggests that it may be possible to design mRNAs that self-regulate their protein expression, enabling the creation of mRNAs for vaccines and other synthetic biology applications where protein levels in the cell can be tightly controlled without feedback to a transcriptional mechanism. As a proof of concept, I design a polycistronic mRNA based on bacteriophage MS2, where the upstream gene is capable of repressing synthesis of the downstream gene. Using a computational tool that simulates ribosome kinetics and the co-translational folding of the mRNA in response, I show that mutations to the mRNA can be identified which enhance the efficiency of the translation and the repression of the downstream gene. The results of this study open up the possibility of designing bespoke mRNA gene circuits in which the amount of protein synthesised in cells are self-regulated for therapeutic or antigenic purposes.

Induction of bacterial expression at the mRNA level by light

Vital organismal processes, including development, differentiation and adaptation, involve altered gene expression. Although expression is frequently controlled at the transcriptional stage, various regulation mechanisms operate at downstream levels. Here, we leverage the photoreceptor NmPAL to optogenetically induce RNA refolding and the translation of bacterial mRNAs. Blue-light-triggered NmPAL binding disrupts a cis-repressed mRNA state, thereby relieves obstruction of translation initiation, and upregulates gene expression. Iterative probing and optimization of the circuit, dubbed riboptoregulator, enhanced induction to 30-fold. Given action at the mRNA level, the riboptoregulator can differentially regulate individual structural genes within polycistronic operons. Moreover, it is orthogonal to and can be wed with other gene-regulatory circuits for nuanced and more stringent gene-expression control. We thus advance the pAurora2 circuit that combines transcriptional and translational mechanisms to optogenetically increase bacterial gene expression by >1000-fold. The riboptoregulator strategy stands to upgrade numerous regulatory circuits and widely applies to expression control in microbial biotechnology, synthetic biology and materials science.

Signal Amplification for Cell-Free Biosensors, an Analog-to-Digital Converter

Toehold switches are biosensors useful for the detection of endogenous and environmental RNAs. They have been successfully engineered to detect virus RNAs in cell-free gene expression reactions. Their inherent sequence programmability makes engineering a fast and predictable process. Despite improvements in the design, toehold switches suffer from leaky translation in the OFF state, which compromises the fold change and sensitivity of the biosensor. To address this, we constructed and tested signal amplification circuits for three toehold switches triggered by Dengue and SARS-CoV-2 RNAs and an artificial RNA. The serine integrase circuit efficiently contained leakage, boosted the expression fold change from OFF to ON, and decreased the detection limit of the switches by 3-4 orders of magnitude. Ultimately, the integrase circuit converted the analog switches' signals into digital-like output. The circuit is broadly useful for biosensors and eliminates the hard work of designing and testing multiple switches to find the best possible performer.

An optogenetic toolkit for light-inducible antibiotic resistance

Antibiotics are a key control mechanism for synthetic biology and microbiology. Resistance genes are used to select desired cells and regulate bacterial populations, however their use to-date has been largely static. Precise spatiotemporal control of antibiotic resistance could enable a wide variety of applications that require dynamic control of susceptibility and survival. Here, we use light-inducible Cre recombinase to activate expression of drug resistance genes in Escherichia coli. We demonstrate light-activated resistance to four antibiotics: carbenicillin, kanamycin, chloramphenicol, and tetracycline. Cells exposed to blue light survive in the presence of lethal antibiotic concentrations, while those kept in the dark do not. To optimize resistance induction, we vary promoter, ribosome binding site, and enzyme variant strength using chromosome and plasmid-based constructs. We then link inducible resistance to expression of a heterologous fatty acid enzyme to increase production of octanoic acid. These optogenetic resistance tools pave the way for spatiotemporal control of cell survival.

Programmable synthetic biology tools for developing microbial cell factories

Microbial conversion to generate value-added chemicals from diverse biomass is one of the keystones of energy biotechnology. Programmable synthetic biology tools offer versatile, standardized options for developing microbial cell factories. These tools thus can be reprogrammed in a user-defined manner for flexible wiring of stimuli and response, highly efficient genome engineering, and extensive perturbation of metabolic flux and genetic circuits. They also can be modularly assembled to construct elaborate and unprecedented biological systems with unique features. This review highlights recent advances in programmable synthetic biology tools based on biosensors, CRISPR-Cas, and RNA devices for developing microbial cell factories that have the potential to be utilized for energy biotechnology.

Genetic switches based on nucleic acid strand displacement

Toehold-mediated strand displacement (TMSD) is an isothermal switching process that enables the sequence-programmable and reversible conversion of DNA or RNA strands between single- and double-stranded conformations or other secondary structures. TMSD processes have already found widespread application in DNA nanotechnology, where they are used to drive DNA-based molecular devices or for the realization of synthetic biochemical computing circuits. Recently, researchers have started to employ TMSD also for the control of RNA-based gene regulatory processes in vivo, in particular in the context of synthetic riboregulators and conditional guide RNAs for CRISPR/Cas. Here, we provide a review over recent developments in this emerging field and discuss the opportunities and challenges for such systems in in vivo applications.

Nucleic acid strand displacement - from DNA nanotechnology to translational regulation

Nucleic acid strand displacement reactions involve the competition of two or more DNA or RNA strands of similar sequence for binding to a complementary strand, and facilitate the isothermal replacement of an incumbent strand by an invader. The process can be biased by augmenting the duplex comprising the incumbent with a single-stranded extension, which can act as a toehold for a complementary invader. The toehold gives the invader a thermodynamic advantage over the incumbent, and can be programmed as a unique label to activate a specific strand displacement process. Toehold-mediated strand displacement processes have been extensively utilized for the operation of DNA-based molecular machines and devices as well as for the design of DNA-based chemical reaction networks. More recently, principles developed initially in the context of DNA nanotechnology have been applied for the de novo design of gene regulatory switches that can operate inside living cells. The article specifically focuses on the design of RNA-based translational regulators termed toehold switches. Toehold switches utilize toehold-mediated strand invasion to either activate or repress translation of an mRNA in response to the binding of a trigger RNA molecule. The basic operation principles of toehold switches will be discussed as well as their applications in sensing and biocomputing. Finally, strategies for their optimization will be described as well as challenges for their operation in vivo.

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.