Engineering Modular Biosensors to Confer Metabolite-Responsive Regulation of Transcription

Computational design of Periplasmic binding protein biosensors guided by molecular dynamics

Periplasmic binding proteins (PBPs) are bacterial proteins commonly used as scaffolds for substrate-detecting biosensors. In these biosensors, effector proteins (for example fluorescent proteins) are inserted into a PBP such that the effector protein's output changes upon PBP-substate binding. The insertion site is often determined by comparison of PBP apo/holo crystal structures, but random insertion libraries have shown that this can miss the best sites. Here, we present a PBP biosensor design method based on residue contact analysis from molecular dynamics. This computational method identifies the best previously known insertion sites in the maltose binding PBP, and suggests further previously unknown sites. We experimentally characterise fluorescent protein insertions at these new sites, finding they too give functional biosensors. Furthermore, our method is sufficiently flexible to both suggest insertion sites compatible with a variety of effector proteins, and be applied to binding proteins beyond PBPs.

Engineering Ca2+-Dependent DNA Polymerase Activity

Advancements in synthetic biology have provided new opportunities in biosensing, with applications ranging from genetic programming to diagnostics. Next generation biosensors aim to expand the number of accessible environments for measurements, increase the number of measurable phenomena, and improve the quality of the measurement. To this end, an emerging area in the field has been the integration of DNA as an information storage medium within biosensor outputs, leveraging nucleic acids to record the biosensor state over time. However, slow signal transduction steps, due to the time scales of transcription and translation, bottleneck many sensing-DNA recording approaches. DNA polymerases (DNAPs) have been proposed as a solution to the signal transduction problem by operating as both the sensor and responder, but there is presently a lack of DNAPs with functional sensitivity to many desirable target ligands. Here, we engineer components of the Pol δ replicative polymerase complex of Saccharomyces cerevisiae to sense and respond to Ca2+, a metal cofactor relevant to numerous biological phenomena. Through domain insertion and binding site grafting to Pol δ subunits, we demonstrate functional allosteric sensitivity to Ca2+. Together, this work provides an important foundation for future efforts in the development of DNAP-based biosensors.

Development of a Transcriptional Factor PuuR-Based Putrescine-Specific Biosensor in Corynebacterium glutamicum

Corynebacterium glutamicum is regarded as an industrially important microbial cell factory and is widely used to produce various value-added chemicals. Because of the importance of C. glutamicum applications, current research is increasingly focusing on developing C. glutamicum synthetic biology platforms. Because of its ability to condense with adipic acid to synthesize the industrial plastic nylon-46, putrescine is an important platform compound of industrial interest. Developing a high-throughput putrescine biosensor can aid in accelerating the design-build-test cycle of cell factories (production strains) to achieve high putrescine-generating strain production in C. glutamicum. This study developed a putrescine-specific biosensor (pSenPuuR) in C. glutamicum using Escherichia coli-derived transcriptional factor PuuR. The response characteristics of the biosensor to putrescine were further improved by optimizing the genetic components of pSenPuuR, such as the response promoter, reporter protein, and promoter for controlling PuuR expression. According to the findings of the study, pSenPuuR has the potential to be used to assess putrescine production in C. glutamicum and is suitable for high-throughput genetic variant screening.

Genetically encoded biosensors for microbial synthetic biology: From conceptual frameworks to practical applications

Genetically encoded biosensors are the vital components of synthetic biology and metabolic engineering, as they are regarded as powerful devices for the dynamic control of genotype metabolism and evolution/screening of desirable phenotypes. This review summarized the recent advances in the construction and applications of different genetically encoded biosensors, including fluorescent protein-based biosensors, nucleic acid-based biosensors, allosteric transcription factor-based biosensors and two-component system-based biosensors. First, the construction frameworks of these biosensors were outlined. Then, the recent progress of biosensor applications in creating versatile microbial cell factories for the bioproduction of high-value chemicals was summarized. Finally, the challenges and prospects for constructing robust and sophisticated biosensors were discussed. This review provided theoretical guidance for constructing genetically encoded biosensors to create desirable microbial cell factories for sustainable bioproduction.

Design and engineering of genetically encoded protein biosensors for small molecules

Genetically encoded protein biosensors controlled by small organic molecules are valuable tools for many biotechnology applications, including control of cellular decisions in living cells. Here, we review recent advances in protein biosensor design and engineering for binding to novel ligands. We categorize sensor architecture as either integrated or portable, where portable biosensors uncouple molecular recognition from signal transduction. Proposed advances to improve portable biosensor development include standardizing a limited set of protein scaffolds, and automating ligand-compatibility screening and ligand-protein-interface design.

A pathway independent multi-modular ordered control system based on thermosensors and CRISPRi improves bioproduction in Bacillus subtilis

Dynamic regulation is an effective strategy for control of gene expression in microbial cell factories. In some pathway contexts, several metabolic modules must be controlled in a time dependent or ordered manner to maximize production, while the creation of genetic circuits with ordered regulation capacity still remains a great challenge. In this work, we develop a pathway independent and programmable system that enables multi-modular ordered control of metabolism in Bacillus subtilis. First, a series of thermosensors were created and engineered to expand their thresholds. Then we designed single-input-multi-output circuits for ordered control based on the use of thermosensors with different transition points. Meanwhile, a repression circuit was constructed by combining CRISPRi-based NOT gates. As a proof-of-concept, these genetic circuits were applied for multi-modular ordered control of 2′-fucosyllactose (2′-FL) biosynthesis, resulting in a production of 1839.7 mg/l in shake flask, which is 5.16-times that of the parental strain. In a 5-l bioreactor, the 2′-FL titer reached 28.2 g/l with down-regulation of autolysis. Taken together, this work provides programmable and versatile thermosensitive genetic toolkits for dynamic regulation in B. subtilis and a multi-modular ordered control framework that can be used to improve metabolic modules in other chassis cells and for other compounds.

Synthetic Protein Circuits and Devices Based on Reversible Protein-Protein Interactions: An Overview

Protein-protein interactions (PPIs) contribute to regulate many aspects of cell physiology and metabolism. Protein domains involved in PPIs are important building blocks for engineering genetic circuits through synthetic biology. These domains can be obtained from known proteins and rationally engineered to produce orthogonal scaffolds, or computationally designed de novo thanks to recent advances in structural biology and molecular dynamics prediction. Such circuits based on PPIs (or protein circuits) appear of particular interest, as they can directly affect transcriptional outputs, as well as induce behavioral/adaptational changes in cell metabolism, without the need for further protein synthesis. This last example was highlighted in recent works to enable the production of fast-responding circuits which can be exploited for biosensing and diagnostics. Notably, PPIs can also be engineered to develop new drugs able to bind specific intra- and extra-cellular targets. In this review, we summarize recent findings in the field of protein circuit design, with particular focus on the use of peptides as scaffolds to engineer these circuits.

Modular tuning engineering and versatile applications of genetically encoded biosensors

Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.

Multilayer Genetic Circuits for Dynamic Regulation of Metabolic Pathways

The dynamic regulation of metabolic pathways is based on changes in external signals and endogenous changes in gene expression levels and has extensive applications in the field of synthetic biology and metabolic engineering. However, achieving dynamic control is not trivial, and dynamic control is difficult to obtain using simple, single-level, control strategies because they are often affected by native regulatory networks. Therefore, synthetic biologists usually apply the concept of logic gates to build more complex and multilayer genetic circuits that can process various signals and direct the metabolic flux toward the synthesis of the molecules of interest. In this review, we first summarize the applications of dynamic regulatory systems and genetic circuits and then discuss how to design multilayer genetic circuits to achieve the optimal control of metabolic fluxes in living cells.

Dynamic Control of Metabolism

Metabolic engineering reprograms cells to synthesize value-added products. In doing so, endogenous genes are altered and heterologous genes can be introduced to achieve the necessary enzymatic reactions. Dynamic regulation of metabolic flux is a powerful control scheme to alleviate and overcome the competing cellular objectives that arise from the introduction of these production pathways. This review explores dynamic regulation strategies that have demonstrated significant production benefits by targeting the metabolic node corresponding to a specific challenge. We summarize the stimulus-responsive control circuits employed in these strategies that determine the criterion for actuating a dynamic response and then examine the points of control that couple the stimulus-responsive circuit to a shift in metabolic flux.

Genetically-encoded biosensors for analyzing and controlling cellular process in yeast

Yeast has been a robust platform to manufacture a broad range of biofuels, commodity chemicals, natural products and pharmaceuticals. The membrane-bound organelles in yeast provide us the means to access the specialized metabolism for various biosynthetic applications. The separation and compartmentalization of genetic and metabolic events presents us the opportunity to precisely control and program gene expression for higher order biological functions. To further advance yeast synthetic biology platform, genetically encoded biosensors and actuators haven been engineered for in vivo monitoring and controlling cellular processes with spatiotemporal resolutions. The dynamic response, sensitivity and operational range of these genetically encoded sensors are determined by the regulatory architecture, dynamic assemly and interactions of the related proteins and genetic elements. This review provides an update of the basic design principles underlying the allosteric transcription factors, GPCR and optogenetics-based sensors, aiming to precisely analyze and control yeast cellular processes for various biotechnological applications.

De Novo Designed Protein-Interaction Modules for In-Cell Applications

Protein-protein interactions control a wide variety of natural biological processes. α-Helical coiled coils frequently mediate such protein-protein interactions. Due to the relative simplicity of their sequences and structures and the ease with which properties such as strength and specificity of interaction can be controlled, coiled coils can be designed de novo to deliver a variety of non-natural protein-protein interaction domains. Herein, several de novo designed coiled coils are tested for their ability to mediate protein-protein interactions in Escherichia coli cells. The set includes a parallel homodimer, a parallel homotetramer, an antiparallel homotetramer, and a newly designed heterotetramer, all of which have been characterized in vitro by biophysical and structural methods. Using a transcription repression assay based on reconstituting the Lac repressor, we find that the modules behave as designed in the cellular environment. Each design imparts a different property to the resulting Lac repressor-coiled coil complexes, resulting in the benefit of being able to reconfigure the system in multiple ways. Modification of the system also allows the interactions to be controlled: assembly can be tuned by controlling the expression of the constituent components, and complexes can be disrupted through helix sequestration. The small and straightforward de novo designed components that we deliver are highly versatile and have considerable potential as protein-protein interaction domains in synthetic biology where proteins must be assembled in highly specific ways. The relative simplicity of the designs makes them amenable to future modifications to introduce finer control over their assembly and to adapt them for different contexts.

Reverse Engineering of an Aspirin-Responsive Transcriptional Regulator in Escherichia coli

Bacterial transcription factors (TFs) are key devices for the engineering of complex circuits in many biotechnological applications, yet there are few well-characterized inducer-responsive TFs that could be used in the context of an animal or human host. We have deciphered the inducer recognition mechanism of two AraC/XylS regulators from Pseudomonas putida (BenR and XylS) for creating a novel expression system responsive to acetyl salicylate (i.e., aspirin). Using protein homology modeling and molecular docking with the cognate inducer benzoate and a suite of chemical analogues, we identified the conserved binding pocket of BenR and XylS. By means of site-directed mutagenesis, we identified a single amino acid position required for efficient inducer recognition and transcriptional activation. Whereas this modification in BenR abolishes protein activity, in XylS, it increases the response to several inducers, including acetyl salicylic acid, to levels close to those achieved by the canonical inducer. Moreover, by constructing chimeric proteins with swapped N-terminal domains, we created novel regulators with mixed promoter and inducer recognition profiles. As a result, a collection of engineered TFs was generated with an enhanced response to benzoate, 3-methylbenzoate, 2-methylbenzoate, 4-methylbenzoate, salicylic acid, aspirin, and acetylsalicylic acid molecules for eliciting gene expression in E. coli.

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.

Converting a Periplasmic Binding Protein into a Synthetic Biosensing Switch through Domain Insertion

All biosensing platforms rest on two pillars: specific biochemical recognition of a particular analyte and transduction of that recognition into a readily detectable signal. Most existing biosensing technologies utilize proteins that passively bind to their analytes and therefore require wasteful washing steps, specialized reagents, and expensive instruments for detection. To overcome these limitations, protein engineering strategies have been applied to develop new classes of protein-based sensor/actuators, known as protein switches, responding to small molecules. Protein switches change their active state (output) in response to a binding event or physical signal (input) and therefore show a tremendous potential to work as a biosensor. Synthetic protein switches can be created by the fusion between two genes, one coding for a sensor protein (input domain) and the other coding for an actuator protein (output domain) by domain insertion. The binding of a signal molecule to the engineered protein will switch the protein function from an “off” to an “on” state (or vice versa) as desired. The molecular switch could, for example, sense the presence of a metabolite, pollutant, or a biomarker and trigger a cellular response. The potential sensing and response capabilities are enormous; however, the recognition repertoire of natural switches is limited. Thereby, bioengineers have been struggling to expand the toolkit of molecular switches recognition repertoire utilizing periplasmic binding proteins (PBPs) as protein-sensing components. PBPs are a superfamily of bacterial proteins that provide interesting features to engineer biosensors, for instance, immense ligand-binding diversity and high affinity, and undergo large conformational changes in response to ligand binding. The development of these protein switches has yielded insights into the design of protein-based biosensors, particularly in the area of allosteric domain fusions. Here, recent protein engineering approaches for expanding the versatility of protein switches are reviewed, with an emphasis on studies that used PBPs to generate novel switches through protein domain insertion.

Development of novel metabolite-responsive transcription factors via transposon-mediated protein fusion

Naturally evolved metabolite-responsive biosensors enable applications in metabolic engineering, ranging from screening large genetic libraries to dynamically regulating biosynthetic pathways. However, there are many metabolites for which a natural biosensor does not exist. To address this need, we developed a general method for converting metabolite-binding proteins into metabolite-responsive transcription factors-Biosensor Engineering by Random Domain Insertion (BERDI). This approach takes advantage of an in vitro transposon insertion reaction to generate all possible insertions of a DNA-binding domain into a metabolite-binding protein, followed by fluorescence activated cell sorting to isolate functional biosensors. To develop and evaluate the BERDI method, we generated a library of candidate biosensors in which a zinc finger DNA-binding domain was inserted into maltose binding protein, which served as a model well-studied metabolite-binding protein. Library diversity was characterized by several methods, a selection scheme was deployed, and ultimately several distinct and functional maltose-responsive transcriptional biosensors were identified. We hypothesize that the BERDI method comprises a generalizable strategy that may ultimately be applied to convert a wide range of metabolite-binding proteins into novel biosensors for applications in metabolic engineering and synthetic biology.

A Biosensor Strategy for E. coli Based on Ligand-Dependent Stabilization

The engineering of microorganisms to monitor environmental chemicals or to produce desirable bioproducts is often reliant on the availability of a suitable biosensor. However, the conversion of a ligand-binding protein into a biosensor has been difficult. Here, we report a general strategy for generating biosensors in Escherichia coli that act by ligand-dependent stabilization of a transcriptional activator and mediate ligand concentration-dependent expression of a reporter gene. We constructed such a biosensor by using the lac repressor, LacI, as the ligand-binding domain and fusing it to the Zif268 DNA-binding domain and RNA polymerase omega subunit transcription-activating domain. Using error-prone PCR mutagenesis of lacI and selection, we identified a biosensor with multiple mutations, only one of which was essential for biosensor behavior. By tuning parameters of the assay, we obtained a response dependent on the ligand isopropyl β-d-1-thiogalactopyranoside (IPTG) of up to a 7-fold increase in the growth rate of E. coli. The single destabilizing mutation combined with a lacI mutation that expands ligand specificity to d-fucose generated a biosensor with improved response both to d-fucose and to IPTG. However, a mutation equivalent to the one that destabilized LacI in either of two structurally similar periplasmic binding proteins did not confer ligand-dependent stabilization. Finally, we demonstrated the generality of this method by using mutagenesis and selection to engineer another ligand-binding domain, MphR, to function as a biosensor. This strategy may allow many natural proteins that recognize and bind to ligands to be converted into biosensors.

Boosting Secondary Metabolite Production and Discovery through the Engineering of Novel Microbial Biosensors

Bacteria are a source of a large number of secondary metabolites with several biomedical and biotechnological applications. In recent years, there has been tremendous progress in the development of novel synthetic biology approaches both to increase the production rate of secondary metabolites of interest in native producers and to mine and reconstruct novel biosynthetic gene clusters in heterologous hosts. Here, we present the recent advances toward the engineering of novel microbial biosensors to detect the synthesis of secondary metabolites in bacteria and in the development of synthetic promoters and expression systems aiming at the construction of microbial cell factories for the production of these compounds. We place special focus on the potential of Gram-negative bacteria as a source of biosynthetic gene clusters and hosts for pathway assembly, on the construction and characterization of novel promoters for native hosts, and on the use of computer-aided design of novel pathways and expression systems for secondary metabolite production. Finally, we discuss some of the potentials and limitations of the approaches that are currently being developed and we highlight new directions that could be addressed in the field.

Harnessing Marine Biocatalytic Reservoirs for Green Chemistry Applications through Metagenomic Technologies

In a demanding commercial world, large-scale chemical processes have been widely utilised to satisfy consumer related needs. Chemical industries are key to promoting economic growth and meeting the requirements of a sustainable industrialised society. The market need for diverse commodities produced by the chemical industry is rapidly expanding globally. Accompanying this demand is an increased threat to the environment and to human health, due to waste produced by increased industrial production. This increased demand has underscored the necessity to increase reaction efficiencies, in order to reduce costs and increase profits. The discovery of novel biocatalysts is a key method aimed at combating these difficulties. Metagenomic technology, as a tool for uncovering novel biocatalysts, has great potential and applicability and has already delivered many successful achievements. In this review we discuss, recent developments and achievements in the field of biocatalysis. We highlight how green chemistry principles through the application of biocatalysis, can be successfully promoted and implemented in various industrial sectors. In addition, we demonstrate how two novel lipases/esterases were mined from the marine environment by metagenomic analysis. Collectively these improvements can result in increased efficiency, decreased energy consumption, reduced waste and cost savings for the chemical industry.

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.

New Intracellular Shikimic Acid Biosensor for Monitoring Shikimate Synthesis in Corynebacterium glutamicum

The quantitative monitoring of intracellular metabolites with in vivo biosensors provides an efficient means of identifying high-yield strains and observing product accumulation in real time. In this study, a shikimic acid (SA) biosensor was constructed from a LysR-type transcriptional regulator (ShiR) of Corynebacterium glutamicum. The SA biosensor specifically responded to the increase of intracellular SA concentration over a linear range of 19.5 ± 3.6 to 120.9 ± 1.2 fmole at the single-cell level. This new SA biosensor was successfully used to (1) monitor the SA production of different C. glutamicum strains; (2) develop a novel result-oriented high-throughput ribosome binding site screening and sorting strategy that was used for engineering high-yield shikimate-producing strains; and (3) engineer a whole-cell biosensor through the coexpression of the SA sensor and a shikimate transporter shiA gene in C. glutamicum RES167. This work demonstrated that a new intracellular SA biosensor is a valuable tool facilitating the fast development of microbial SA producer.

Design and Selection of a Synthetic Feedback Loop for Optimizing Biofuel Tolerance

Feedback control allows cells to dynamically sense and respond to environmental changes. However, synthetic controller designs can be challenging because of implementation issues, such as determining optimal expression levels for circuit components within a feedback loop. Here, we addressed this by coupling rational design with selection to engineer a synthetic feedback circuit to optimize tolerance of Escherichia coli to the biojet fuel pinene. E. coli can be engineered to produce pinene, but it is toxic to cells. Efflux pumps, such as the AcrAB-TolC pump, can improve tolerance, but pump expression impacts growth. To address this, we used feedback to dynamically regulate pump expression in response to stress. We developed a library with thousands of synthetic circuit variants and subjected it to three types of pinene treatment (none, constant, and varying pinene). We were able to select for strains that were biofuel tolerant without a significant growth cost in the absence of biofuel. Using next-generation sequencing, we found common characteristics in the designs and identified controllers that dramatically improved biofuel tolerance.

Challenges in the Application of Synthetic Biology Toward Synthesis of Commodity Products by Cyanobacteria via "Direct Conversion"

Cyanobacterial direct conversion of CO₂ to several commodity chemicals has been recognized as a potential contributor to support the much-needed sustainable development of human societies. However, the feasibility of this "green conversion" hinders on our ability to overcome the hurdles presented by the natural evolvability of microbes. The latter may result in the genetic instability of engineered cyanobacterial strains leading to impaired productivity. This challenge is general to any "cell factory" approach in which the cells grow for multiple generations, and based on several studies carried out in different microbial hosts, we could identify that three distinct strategies have been proposed to tackle it. These are (1) to reduce microbial evolvability by decreasing the native mutation rate, (2) to align product formation with cell growth/fitness, and, paradoxically, (3) to efficiently reallocate cellular resources to product formation by uncoupling it from growth. The implementation of either of these strategies requires an advanced synthetic biology toolkit. Here, we review the existing methods available for cyanobacteria and identify areas of focus in which specific developments are still needed. Furthermore, we discuss how potentially stabilizing strategies may be used in combination leading to further increases of productivity while ensuring the stability of the cyanobacterial-based direct conversion process.

Developing a Genetically Encoded, Cross-Species Biosensor for Detecting Ammonium and Regulating Biosynthesis of Cyanophycin

Responding to nitrogen status is essential for all living organisms. Bacteria have evolved various complex and exquisite regulatory systems to control nitrogen metabolism. However, natural nitrogen regulatory systems, owing to their complexity, often function only in their original hosts and do not respond properly when transferred to another species. By harnessing the Lactococcus GlnRA system, we developed a genetically encoded, cross-species ammonium biosensor that displays a dynamic range up to 9-fold upon detection of ammonium ion. We demonstrated applications of this ammonium biosensor in three different species (Escherichia coli, Pseudomonas putida, and Synechocystis sp.) to detect different nitrogen sources. This ammonium sensor was further used to regulate the biosynthesis of a nitrogen-rich polymer, cyanophycin, based on ammonium concentration. Given the importance of nitrogen responses, the developed biosensor should be broadly applicable to synthetic biology and bioengineering.

Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors

Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose-response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism.

Programming Post-Translational Control over the Metabolic Labeling of Cellular Proteins with a Noncanonical Amino Acid

Transcriptional control can be used to program cells to label proteins with noncanonical amino acids by regulating the expression of orthogonal aminoacyl tRNA synthetases (aaRSs). However, we cannot yet program cells to control labeling in response to aaRS and ligand binding. To identify aaRSs whose activities can be regulated by interactions with ligands, we used a combinatorial approach to discover fragmented variants of Escherichia coli methionyl tRNA synthetase (MetRS) that require fusion to associating proteins for maximal activity. We found that these split proteins could be leveraged to create ligand-dependent MetRS using two approaches. When a pair of MetRS fragments was fused to FKBP12 and the FKBP-rapamycin binding domain (FRB) of mTOR and mutations were introduced that direct substrate specificity toward azidonorleucine (Anl), Anl metabolic labeling was significantly enhanced in growth medium containing rapamycin, which stabilizes the FKBP12-FRB complex. In addition, fusion of MetRS fragments to the termini of the ligand-binding domain of the estrogen receptor yielded proteins whose Anl metabolic labeling was significantly enhanced when 4-hydroxytamoxifen (4-HT) was added to the growth medium. These findings suggest that split MetRS can be fused to a range of ligand-binding proteins to create aaRSs whose metabolic labeling activities depend upon post-translational interactions with ligands.