Crosstalk between endogenous and synthetic components--synthetic signaling meets endogenous components

Concentration-Dependent CsrA Regulation of the uxuB Transcript Leads to Development of a Post-Transcriptional Bandpass Filter

Post-transcriptional control systems offer new avenues for designing synthetic circuits that provide reduced burden and fewer synthetic regulatory components compared to transcriptionally based tools. Herein, we repurpose a newly identified post-transcriptional interaction between the uxuB mRNA transcript, specifically the 5' UTR + 100 nucleotides of coding sequence (100 nt CDS), and the E. coli Carbon Storage Regulatory A (CsrA) protein to design a biological post-transcriptional bandpass filter. In this work, we characterize the uxuB mRNA as a heterogeneous target of CsrA, where the protein can both activate and repress uxuB activity depending on its intracellular concentration. We leverage this interaction to implement a novel strategy of regulation within the 5' UTR of an mRNA. Specifically, we report a hierarchical binding strategy that may be leveraged by CsrA within uxuB to produce a dose-dependent response in regulatory outcomes. In our semisynthetic circuit, the uxuB 5' UTR + 100 nt CDS sequence is used as a scaffold that is fused to a gene of interest, which allows the circuit to transition between ON/OFF states based on the concentration range of free natively expressed CsrA. Notably, this system exerts regulation comparable to previously developed transcriptional bandpass filters while reducing the number of synthetic circuit components and can be used in concert with additional post-transcriptionally controlled circuits to achieve complex multi-signal control. We anticipate that future characterization of native regulatory RNA-protein systems will enable the development of more complex RNP-based circuits for synthetic biology applications.

Prospects for synthetic biology in 21st Century agriculture

Plant synthetic biology has emerged as a transformative field in agriculture, offering innovative solutions to enhance food security, provide resilience to climate change, and transition to sustainable farming practices. By integrating advanced genetic tools, computational modeling, and systems biology, researchers can precisely modify plant genomes to enhance traits such as yield, stress tolerance, and nutrient use efficiency. The ability to design plants with specific characteristics tailored to diverse environmental conditions and agricultural needs holds great potential to address global food security challenges. Here, we highlight recent advancements and applications of plant synthetic biology in agriculture, focusing on key areas such as photosynthetic efficiency, nitrogen fixation, drought tolerance, pathogen resistance, nutrient use efficiency, biofortification, climate resilience, microbiology engineering, synthetic plant genomes, and the integration of artificial intelligence (AI) with synthetic biology. These innovations aim to maximize resource use efficiency, reduce reliance on external inputs, and mitigate environmental impacts associated with conventional agricultural practices. Despite challenges related to regulatory approval and public acceptance, the integration of synthetic biology in agriculture holds immense promise for creating more resilient and sustainable agricultural systems, contributing to global food security and environmental sustainability. Rigorous multi-field testing of these approaches will undoubtedly be required to ensure reproducibility.

Creation of an orthogonal and universal auto-inducible gene expression platform by reprogramming a two-component signal circuit for efficient production of industrial enzymes

Bacterial gene expression systems play a crucial role in producing valuable biological macromolecules, such as recombinant proteins and polysaccharides. However, traditional inducible gene systems have limitations that need costly chemical inducers that can harm the host. To address these challenges, a novel peptide-activated auto-inducible gene expression system was developed in Bacillus subtilis, leveraging Accessory gene regulatory system (Agr), a two-component signal system, from Staphylococcus aureus to trigger gene expression in response to an auto-inducible peptide (AIP). This system mimics a cell density-dependent regulatory mechanism, allowing for the intuitive activation of gene expression as accumulation of AIP. By precisely tuning the level of AIP, the auto-induction time was successfully delayed, however, at the expense of slightly reducing the strength of effector promoter P3, thus decreasing level of output expression. Furthermore, modulation of the stoichiometry of sensor protein AgrC allowed for fine-tuning of the auto-induction time, temporal dynamics, and expression levels. The robustness of the system was improved by strengthening P3 while maintaining the delayed auto-induction time. The versatility and efficacy of the system was demonstrated by the efficient production of various industrial enzymes. This study paves the way for the application of bacterial two-component signal systems to design synthetic gene circuits.

Synthetic microbe-to-plant communication channels

Plants and microbes communicate to collaborate to stop pests, scavenge nutrients, and react to environmental change. Microbiota consisting of thousands of species interact with each other and plants using a large chemical language that is interpreted by complex regulatory networks. In this work, we develop modular interkingdom communication channels, enabling bacteria to convey environmental stimuli to plants. We introduce a "sender device" in Pseudomonas putida and Klebsiella pneumoniae, that produces the small molecule p-coumaroyl-homoserine lactone (pC-HSL) when the output of a sensor or circuit turns on. This molecule triggers a "receiver device" in the plant to activate gene expression. We validate this system in Arabidopsis thaliana and Solanum tuberosum (potato) grown hydroponically and in soil, demonstrating its modularity by swapping bacteria that process different stimuli, including IPTG, aTc and arsenic. Programmable communication channels between bacteria and plants will enable microbial sentinels to transmit information to crops and provide the building blocks for designing artificial consortia.

Novel switchable ECF sigma factor transcription system for improving thaxtomin A production in Streptomyces

The application of the valuable natural product thaxtomin A, a potent bioherbicide from the potato scab pathogenic Streptomyces strains, has been greatly hindered by the low yields from its native producers. Here, we developed an orthogonal transcription system, leveraging extra-cytoplasmic function (ECF) sigma (σ) factor 17 (ECF17) and its cognate promoter P_ecf17, to express the thaxtomin gene cluster and improve the production of thaxtomin A. The minimal P_ecf17 promoter was determined, and a P_ecf17 promoter library with a wide range of strengths was constructed. Furthermore, a cumate inducible system was developed for precise temporal control of the ECF17 transcription system in S. venezuelae ISP5230. Theoretically, the switchable ECF17 transcription system could reduce the unwanted influences from host and alleviate the burdens introduced by overexpression of heterologous genes. The yield of thaxtomin A was significantly improved to 202.1 ± 15.3 μ g/mL using the switchable ECF17 transcription system for heterologous expression of the thaxtomin gene cluster in S. venezuelae ISP5230. Besides, the applicability of this transcription system was also tested in Streptomyces albus J1074, and the titer of thaxtomin A was raised to as high as 239.3 ± 30.6 μg/mL. Therefore, the inducible ECF17 transcription system could serve as a complement of the generally used transcription systems based on strong native constitutive promoters and housekeeping σ factors for the heterologous expression of valuable products in diverse Streptomyces hosts.

Response and tolerance mechanism of food crops under high temperature stress: a review

High temperature stress events are critical factors inhibiting crop yield. Meanwhile, world population is growing very rapidly and will be reached up to 9 billion by 2050. To feed increasing world population, it is challenging task to increase about 70% global food productions. Food crops have significant contribution toward global food demand and food security. However, consequences from increasing heat stress events are demolishing their abilities to survive and sustain yield when subjected to extreme high temperature stress. Therefore, there is dire need to better understand response and tolerance mechanism of food crops following exposure to heat stress. Here, we aimed to provide recent update on impact of high temperature stress on crop yield of food crops, pollination, pollinators, and novel strategies for improving tolerance of food crop under high temperature stress. Importantly, development of heat-resistant transgenic food crops can grant food security through transformation of superior genes into current germplasm, which are associated with various signaling pathways as well as epigenetic regulation in response to extreme high temperature stress.

Quantitative and Predictive Genetic Parts for Plant Synthetic Biology

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.

Engineering Multiple Abiotic Stress Tolerance in Canola, Brassica napus

Impacts of climate change like global warming, drought, flooding, and other extreme events are posing severe challenges to global crop production. Contribution of Brassica napus towards the oilseed industry makes it an essential component of international trade and agroeconomics. Consequences from increasing occurrences of multiple abiotic stresses on this crop are leading to agroeconomic losses making it vital to endow B. napus crop with an ability to survive and maintain yield when faced with simultaneous exposure to multiple abiotic stresses. For an improved understanding of the stress sensing machinery, there is a need for analyzing regulatory pathways of multiple stress-responsive genes and other regulatory elements such as non-coding RNAs. However, our understanding of these pathways and their interactions in B. napus is far from complete. This review outlines the current knowledge of stress-responsive genes and their role in imparting multiple stress tolerance in B. napus. Analysis of network cross-talk through omics data mining is now making it possible to unravel the underlying complexity required for stress sensing and signaling in plants. Novel biotechnological approaches such as transgene-free genome editing and utilization of nanoparticles as gene delivery tools are also discussed. These can contribute to providing solutions for developing climate change resilient B. napus varieties with reduced regulatory limitations. The potential ability of synthetic biology to engineer and modify networks through fine-tuning of stress regulatory elements for plant responses to stress adaption is also highlighted.

Structural Basis of Design and Engineering for Advanced Plant Optogenetics

In optogenetics, light-sensitive proteins are specifically expressed in target cells and light is used to precisely control the activity of these proteins at high spatiotemporal resolution. Optogenetics initially used naturally occurring photoreceptors to control neural circuits, but has expanded to include carefully designed and engineered photoreceptors. Several optogenetic constructs are based on plant photoreceptors, but their application to plant systems has been limited. Here, we present perspectives on the development of plant optogenetics, considering different levels of design complexity. We discuss how general principles of light-driven signal transduction can be coupled with approaches for engineering protein folding to develop novel optogenetic tools. Finally, we explore how the use of computation, networks, circular permutation, and directed evolution could enrich optogenetics.

Gene networks that compensate for crosstalk with crosstalk

Crosstalk is a major challenge to engineering sophisticated synthetic gene networks. A common approach is to insulate signal-transduction pathways by minimizing molecular-level crosstalk between endogenous and synthetic genetic components, but this strategy can be difficult to apply in the context of complex, natural gene networks and unknown interactions. Here, we show that synthetic gene networks can be engineered to compensate for crosstalk by integrating pathway signals, rather than by pathway insulation. We demonstrate this principle using reactive oxygen species (ROS)-responsive gene circuits in Escherichia coli that exhibit concentration-dependent crosstalk with non-cognate ROS. We quantitatively map the degree of crosstalk and design gene circuits that introduce compensatory crosstalk at the gene network level. The resulting gene network exhibits reduced crosstalk in the sensing of the two different ROS. Our results suggest that simple network motifs that compensate for pathway crosstalk can be used by biological networks to accurately interpret environmental signals.

Crosstalk between genetic circuits is a major challenge for engineering sophisticated networks. Here the authors design networks that compensate for crosstalk by integrating, not insulating, pathways.

Engineering orthogonal synthetic timer circuits based on extracytoplasmic function σ factors

The rational design of synthetic regulatory circuits critically hinges on the availability of orthogonal and well-characterized building blocks. Here, we focus on extracytoplasmic function (ECF) σ factors, which are the largest group of alternative σ factors and hold extensive potential as synthetic orthogonal regulators. By assembling multiple ECF σ factors into regulatory cascades of varying length, we benchmark the scalability of the approach, showing that these ‘autonomous timer circuits’ feature a tuneable time delay between inducer addition and target gene activation. The implementation of similar timers in Escherichia coli and Bacillus subtilis shows strikingly convergent circuit behavior, which can be rationalized by a computational model. These findings not only reveal ECF σ factors as powerful building blocks for a rational, multi-layered circuit design, but also suggest that ECF σ factors are universally applicable as orthogonal regulators in a variety of bacterial species.

Engineering synthetic regulatory circuits in plants

Plant synthetic biology is a rapidly emerging field that aims to engineer genetic circuits to function in plants with the same reliability and precision as electronic circuits. These circuits can be used to program predictable plant behavior, producing novel traits to improve crop plant productivity, enable biosensors, and serve as platforms to synthesize chemicals and complex biomolecules. Herein we introduce the importance of developing orthogonal plant parts and the need for quantitative part characterization for mathematical modeling of complex circuits. In particular, transfer functions are important when designing electronic-like genetic controls such as toggle switches, positive/negative feedback loops, and Boolean logic gates. We then discuss potential constraints and challenges in synthetic regulatory circuit design and integration when using plants. Finally, we highlight current and potential plant synthetic regulatory circuit applications.

Synthetic genetic circuits in crop plants

The love affair between crop breeding and genetics began over a century ago and has continued unabated, from mass selection programs to targeted genome modifications. Synthetic genetic circuits, a recent development, are combinations of regulatory and coding DNA introduced into a crop plant to achieve a desired function. Genetic circuits could accelerate crop improvement, allowing complex traits to be rationally designed and requisite DNA parts delivered directly into a genome of interest. However, there is not yet a standardized pipeline from exploratory laboratory testing to crop trials, and bringing transgenic products to market remains a considerable barrier. We highlight successes so far and future developments necessary to make genetic circuits a viable crop improvement technology over this century.

Synthetic strategies for plant signalling studies: molecular toolbox and orthogonal platforms

Plants deploy a wide array of signalling networks integrating environmental cues with growth, defence and developmental responses. The high level of complexity, redundancy and connection between several pathways hampers a comprehensive understanding of involved functional and regulatory mechanisms. The implementation of synthetic biology approaches is revolutionizing experimental biology in prokaryotes, yeasts and animal systems and can likewise contribute to a new era in plant biology. This review gives an overview on synthetic biology approaches for the development and implementation of synthetic molecular tools and techniques to interrogate, understand and control signalling events in plants, ranging from strategies for the targeted manipulation of plant genomes up to the spatiotemporally resolved control of gene expression using optogenetic approaches. We also describe strategies based on the partial reconstruction of signalling pathways in orthogonal platforms, like yeast, animal and in vitro systems. This allows a targeted analysis of individual signalling hubs devoid of interconnectivity with endogenous interacting components. Implementation of the interdisciplinary synthetic biology tools and strategies is not exempt of challenges and hardships but simultaneously most rewarding in terms of the advances in basic and applied research. As witnessed in other areas, these original theoretical-experimental avenues will lead to a breakthrough in the ability to study and comprehend plant signalling networks.

Use of plant colonizing bacteria as chassis for transfer of N₂-fixation to cereals

Engineering cereal crops that are self-supported by nitrogen fixation has been a dream since the 1970s when nitrogenase was transferred from Klebsiella pneumoniae to Escherichia coli. A renewed interest in this area has generated several new approaches with the common aim of transferring nitrogen fixation to cereal crops. Advances in synthetic biology have afforded the tools to rationally engineer microorganisms with traits of interest. Nitrogenase biosynthesis has been a recent target for the application of new synthetic engineering tools. Early successes in this area suggest that the transfer of nitrogenase and other supporting traits to microorganisms that already closely associate with cereal crops is a logical approach to deliver nitrogen to cereal crops.

Engineering reduced evolutionary potential for synthetic biology

The field of synthetic biology seeks to engineer reliable and predictable behaviors in organisms from collections of standardized genetic parts. However, unlike other types of machines, genetically encoded biological systems are prone to changes in their designed sequences due to mutations in their DNA sequences after these devices are constructed and deployed. Thus, biological engineering efforts can be confounded by undesired evolution that rapidly breaks the functions of parts and systems, particularly when they are costly to the host cell to maintain. Here, we explain the fundamental properties that determine the evolvability of biological systems. Then, we use this framework to review current efforts to engineer the DNA sequences that encode synthetic biology devices and the genomes of their microbial hosts to reduce their ability to evolve and therefore increase their genetic reliability so that they maintain their intended functions over longer timescales.

Translational cross talk in gene networks

It has been shown experimentally that competition for limited translational resources by upstream mRNAs can lead to an anticorrelation between protein counts. Here, we investigate a stochastic model for this phenomenon, in which gene transcripts of different types compete for a finite pool of ribosomes. Throughout, we utilize concepts from the theory of multiclass queues to describe a qualitative shift in protein count statistics as the system transitions from being underloaded (ribosomes exceed transcripts in number) to being overloaded (transcripts exceed ribosomes in number). The exact analytical solution of a simplified stochastic model, in which the numbers of competing mRNAs and ribosomes are fixed, exhibits weak positive correlations between steady-state protein counts when total transcript count slightly exceeds ribosome count, whereas the solution can exhibit strong negative correlations when total transcript count significantly exceeds ribosome count. Extending this analysis, we find approximate but reasonably accurate solutions for a more realistic model, in which abundances of mRNAs and ribosomes are allowed to fluctuate randomly. Here, ribosomal fluctuations contribute positively and mRNA fluctuations contribute negatively to correlations, and when mRNA fluctuations dominate ribosomal fluctuations, a strong anticorrelation extremum reliably occurs near the transition from the underloaded to the overloaded regime.