Naringenin-responsive riboswitch-based fluorescent biosensor module for Escherichia coli co-cultures

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

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

Emerging strategies for engineering microbial communities

From biosynthesis to bioremediation, microbes have been engineered to address a variety of biotechnological applications. A promising direction in these endeavors is harnessing the power of designer microbial consortia that consist of multiple populations with well-defined interactions. Consortia can accomplish tasks that are difficult or potentially impossible to achieve using monocultures. Despite their potential, the rules underlying microbial community maintenance and function (i.e. the task the consortium is engineered to carry out) are not well defined, though rapid progress is being made. This limited understanding is in part due to the greater challenges associated with increased complexity when dealing with multi-population interactions. Here, we review key features and design strategies that emerge from the analysis of both natural and engineered microbial communities. These strategies can provide new insights into natural consortia and expand the toolbox available to engineers working to develop novel synthetic consortia.

Engineering microbial consortia by division of labor

During microbial applications, metabolic burdens can lead to a significant drop in cell performance. Novel synthetic biology tools or multi-step bioprocessing (e.g., fermentation followed by chemical conversions) are therefore needed to avoid compromised biochemical productivity from over-burdened cells. A possible solution to address metabolic burden is Division of Labor (DoL) via natural and synthetic microbial consortia. In particular, consolidated bioprocesses and metabolic cooperation for detoxification or cross feeding (e.g., vitamin C fermentation) have shown numerous successes in industrial level applications. However, distributing a metabolic pathway among proper hosts remains an engineering conundrum due to several challenges: complex subpopulation dynamics/interactions with a short time-window for stable production, suboptimal cultivation of microbial communities, proliferation of cheaters or low-producers, intermediate metabolite dilution, transport barriers between species, and breaks in metabolite channeling through biosynthesis pathways. To develop stable consortia, optimization of strain inoculations, nutritional divergence and crossing feeding, evolution of mutualistic growth, cell immobilization, and biosensors may potentially be used to control cell populations. Another opportunity is direct integration of non-bioprocesses (e.g., microbial electrosynthesis) to power cell metabolism and improve carbon efficiency. Additionally, metabolic modeling and ¹³C-metabolic flux analysis of mixed culture metabolism and cross-feeding offers a computational approach to complement experimental research for improved consortia performance.

Synthetic Biology Tools to Engineer Microbial Communities for Biotechnology

Microbial consortia have been used in biotechnology processes, including fermentation, waste treatment, and agriculture, for millennia. Today, synthetic biologists are increasingly engineering microbial consortia for diverse applications, including the bioproduction of medicines, biofuels, and biomaterials from inexpensive carbon sources. An improved understanding of natural microbial ecosystems, and the development of new tools to construct synthetic consortia and program their behaviors, will vastly expand the functions that can be performed by communities of interacting microorganisms. Here, we review recent advancements in synthetic biology tools and approaches to engineer synthetic microbial consortia, discuss ongoing and emerging efforts to apply consortia for various biotechnological applications, and suggest future applications.

RNA Switches for Synthetic Biology

In addition to coding for protein sequences, RNA molecules encode a diverse set of gene-regulatory elements. RNA switches are one class of gene-regulatory elements that control protein expression in a manner that is dependent on the concentration of specific ligand molecules. These allosteric gene-regulatory elements have been shown as useful tools in engineering diverse cell types to display novel function. In particular, RNA switches have been used as genetically encoded biosensors and conditional controllers to direct cellular decisions based on the system's changing environment. A significant focus in the field has been the generation of novel RNA switches that are tailored for different biological systems. We review approaches that have been used to generate RNA switches, which leverage the unique physical properties of RNA and the myriad ways in which RNA can modulate gene expression.

Magnesium starvation improves production of malonyl-CoA-derived metabolites in Escherichia coli

Starvation of essential nutrients, such as nitrogen, sulfur, magnesium, and phosphorus, leads cells into stationary phase and potentially enhances target metabolite production because cells do not consume carbon for the biomass synthesis. The overall metabolic behavior changes depend on the type of nutrient starvation in Escherichia coli. In the present study, we determined the optimum nutrient starvation type for producing malonyl-CoA-derived metabolites such as 3-hydroxypropionic acid (3HP) and naringenin in E. coli. For 3HP production, high production titer (2.3 or 2.0 mM) and high specific production rate (0.14 or 0.28 mmol gCDW^-1 h^-1) was observed under sulfur or magnesium starvation, whereas almost no 3HP production was detected under nitrogen or phosphorus starvation. Metabolic profiling analysis revealed that the intracellular malonyl-CoA concentration was significantly increased under the 3HP producing conditions. This accumulation should contribute to the 3HP production because malonyl-CoA is a precursor of 3HP. Strong positive correlation (r = 0.95) between intracellular concentrations of ATP and malonyl-CoA indicates that the ATP level is important for malonyl-CoA synthesis due to the ATP requirement by acetyl-CoA carboxylase. For naringenin production, magnesium starvation led to the highest production titer (144 ± 15 μM) and specific productivity (127 ± 21 μmol gCDW^-1). These results demonstrated that magnesium starvation is a useful approach to improve the metabolic state of strains engineered for the production of malonyl-CoA derivatives.

Production of plant-specific flavones baicalein and scutellarein in an engineered E. coli from available phenylalanine and tyrosine

Baicalein and scutellarein are bioactive flavones found in the medicinal plant Scutellaria baicalensis Georgi, used in traditional Chinese medicine. Extensive previous work has demonstrated the broad biological activity of these flavonoids, such as antifibrotic, antiviral and anticancer properties. However, their supply from plant material is insufficient to meet demand. Here, to provide an alternative production source and increase production levels of these flavones, we engineered an artificial pathway in an Escherichia coli cell factory for the first time. By first reconstructing the plant flavonoid biosynthetic pathway genes from five different species: phenylalanine ammonia lyase from Rhodotorula toruloides (PAL), 4-coumarate-coenzyme A ligase from Petroselinum crispum (4CL), chalcone synthase from Petunia hybrida (CHS), chalcone isomerase from Medicago sativa (CHI) and an oxidoreductase flavone synthase I from P. crispum (FNSI), production of the intermediates chrysin and apigenin was achieved by feeding phenylalanine and tyrosine as precursors. By comparative analysis of various versions of P450s, a construction expressing 2B1 incorporated with a 22-aa N-terminal truncated flavone C-6 hydroxylase from S. baicalensis (F6H) and partner P450 reductase from Arabidopsis thaliana (AtCPR) was found most effective for production of both baicalein (8.5 mg/L) and scutellarein (47.1 mg/L) upon supplementation with 0.5 g/L phenylalanine and tyrosine in 48 h of fermentation. Finally, optimization of malonyl-CoA availability further increased the production of baicalein to 23.6 mg/L and scutellarein to 106.5 mg/L in a flask culture. This report presents a significant advancement of flavone synthetic production and provides foundation for production of other flavones in microbial hosts.

In vivo biosensors: mechanisms, development, and applications

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

Reprogramming Probiotic Lactobacillus reuteri as a Biosensor for Staphylococcus aureus Derived AIP-I Detection

Gram-positive Staphylococcus aureus infection that results in pneumonia, urinary tract infection, and in severe cases, sepsis, has recently been classified as a serious threat to public health. Rapid and cost-effective detection of these infections are costly and time-consuming. Here, we present probiotic lactic acid bacteria engineered to detect autoinducer peptide-I (AIP-I), a quorum sensing molecule produced by Staphylococcus sp. during pathogenesis. We achieved this by adapting the well-characterized agr quorum sensing ( agrQS) from Staphylococcus aureus into Lactobacillus reuteri. The engineered biosensor is able to detect AIP-I levels in the nanomolar to micromolar range. We further investigated the function of the biosensor to detect real-time changes in AIP-I levels to understand the dynamics of Staphylococcus aureus under various strenuous conditions. The developed sensors would be useful for detection of Staphylococcus contamination in hospital settings and for high-throughput drug screening.

RNA-based dynamic genetic controllers: development strategies and applications

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Unique properties of RNA lead to the development of RNA-based dynamic genetic controllers.

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Natural riboswitches are re-engineered to detect new molecules.

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RNA-based regulatory mechanisms are exploited to construct novel dynamic RNA controllers.

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Computational methods and in vitro–in vivo selection enable de novo design of dynamic RNA controllers.

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Dynamic RNA controllers are utilized for metabolic engineering and synthetic biology.

Dynamic regulation of gene expression in response to various molecules is crucial for both basic science and practical applications. RNA is considered an attractive material for creating dynamic genetic controllers because of its specific binding to ligands, structural flexibility, programmability, and small size. Here, we review recent advances in strategies for developing RNA-based dynamic controllers and applications. First, we describe studies that re-engineered natural riboswitches to generate new dynamic controllers. Next, we summarize RNA-based regulatory mechanisms that have been exploited to build novel artificial dynamic controllers. We also discuss computational methods and high-throughput selection approaches for de novo design of dynamic RNA controllers. Finally, we explain applications of dynamic RNA controllers for metabolic engineering and synthetic biology.

Design, Optimization and Application of Small Molecule Biosensor in Metabolic Engineering

The development of synthetic biology and metabolic engineering has painted a great future for the bio-based economy, including fuels, chemicals, and drugs produced from renewable feedstocks. With the rapid advance of genome-scale modeling, pathway assembling and genome engineering/editing, our ability to design and generate microbial cell factories with various phenotype becomes almost limitless. However, our lack of ability to measure and exert precise control over metabolite concentration related phenotypes becomes a bottleneck in metabolic engineering. Genetically encoded small molecule biosensors, which provide the means to couple metabolite concentration to measurable or actionable outputs, are highly promising solutions to the bottleneck. Here we review recent advances in the design, optimization and application of small molecule biosensor in metabolic engineering, with particular focus on optimization strategies for transcription factor (TF) based biosensors.

Systematic optimization of L-tryptophan riboswitches for efficient monitoring of the metabolite in Escherichia coli

Riboswitches form a class of genetically encoded sensor-regulators and are considered as promising tools for monitoring various metabolites. Functional parameters of a riboswitch, like dynamic or operational range, should be optimized before the riboswitch is implemented in a specific application for monitoring the target molecule efficiently. However, optimization of a riboswitch was not straightforward and required detailed studies owing to its complex sequence-function relationship. Here, we present three approaches for tuning and optimization of functional parameters of a riboswitch using an artificial L-tryptophan riboswitch as an example. First, the constitutive expression level was adjusted to control the dynamic range of an L-tryptophan riboswitch. The dynamic range increased as the constitutive expression level increased. Then, the function of a riboswitch-encoded protein was utilized to connect the regulatory response of the riboswitch to another outcome for amplifying the dynamic range. Riboswitch-mediated control of the host cell growth enabled the amplification of the riboswitch response. Finally, L-tryptophan aptamers with different dissociation constants were employed to alter the operational range of the riboswitch. The dose-response curve was shifted towards higher L-tryptophan concentrations when an aptamer with higher dissociation constant was employed. All strategies were effective in modifying the distinct functional parameters of the L-tryptophan riboswitch, and they could be easily applied to optimization of other riboswitches owing to their simplicity.

Heterologous biosynthesis of natural product naringenin by co-culture engineering

Co-culture engineering is an emerging approach for microbial biosynthesis of a variety of biochemicals. In this study, E. coli-E. coli co-cultures were developed for heterologous biosynthesis of the natural product naringenin. The co-cultures were composed of two independent E. coli strains dedicated to functional expression of different portions of the biosynthetic pathway, respectively. The co-culture biosynthesis was optimized by investigating the effect of carbon source, E. coli strain selection, timing of IPTG induction and the inoculation ratio between the co-culture strains. Compared with the mono-culture strategy, the utilization of the designed co-cultures significantly improved the naringenin production, largely due to the reduction of metabolic stress, employment of proper hosts for improving pathway enzyme activities, and flexible adjustment of the relative biosynthetic strength between the co-culture strains. The findings of this study extend the applicability of co-culture engineering in complex natural product biosynthesis.