Engineering a Model Cell for Rational Tuning of GPCR Signaling

Engineering Microbial Consortia as Living Materials: Advances and Prospectives

The field of Engineered Living Materials (ELMs) integrates engineered living organisms into natural biomaterials to achieve diverse objectives. Multiorganism consortia, prevalent in both naturally occurring and synthetic microbial cultures, exhibit complex functionalities and interrelationships, extending the scope of what can be achieved with individual engineered bacterial strains. However, the ELMs comprising microbial consortia are still in the developmental stage. In this Review, we introduce two strategies for designing ELMs constituted of microbial consortia: a top-down strategy, which involves characterizing microbial interactions and mimicking and reconstructing natural ecosystems, and a bottom-up strategy, which entails the rational design of synthetic consortia and their assembly with material substrates to achieve user-defined functions. Next, we summarize technologies from synthetic biology that facilitate the efficient engineering of microbial consortia for performing tasks more complex than those that can be done with single bacterial strains. Finally, we discuss essential challenges and future perspectives for microbial consortia-based ELMs.

Advances in yeast synthetic biology for human G protein-coupled receptor biology and pharmacology

G protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors in humans. Over 800 GPCRs regulate the (patho)biology of every organ, tissue, and cell type. Consequently, GPCRs are the most prominent therapeutic targets in medicine. Although over 30% of current U.S. Food and Drug Administration-approved drugs target GPCR signaling, most receptors remain understudied and therapeutically underutilized. Challenges include an incomplete understanding of GPCR signaling, pharmacology, structural biology, and the multiplicity of endogenous GPCR ligands, in addition to a scarcity of biological and pharmacological tools for elucidating GPCR-mediated cellular processes beyond initial signaling events. Various mammalian, insect, and yeast cell models currently address some of these needs. Here, we review recent advances in yeast synthetic biology that are helping to catalyze new and unexpected conceptual and technical breakthroughs in GPCR-based medicine and biotechnology.

Engineering a GPCR-based yeast biosensor for a highly sensitive melatonin detection from fermented beverages

Melatonin is a multifunctional molecule with diverse biological roles that holds great value as a health-promoting bioactive molecule in any food product and yeast's ability to produce it has been extensively demonstrated in the last decade. However, its quantification presents costly analytical challenges due to the usual low concentrations found as the result of yeast metabolism. This study addresses these analytical challenges by optimizing a yeast biosensor based on G protein-coupled receptors (GPCR) for melatonin detection and quantitation. Strategic genetic modifications were employed to significantly enhance its sensitivity and fluorescent signal output, making it suitable for detection of yeast-produced melatonin. The optimized biosensor demonstrated significantly improved sensitivity and fluorescence, enabling the screening of 101 yeast strains and the detection of melatonin in various wine samples. This biosensor's efficacy in quantifying melatonin in yeast growth media underscores its utility in exploring melatonin production dynamics and potential applications in functional food development. This study provides a new analytical approach that allows a rapid and cost-effective melatonin analysis to reach deeper insights into the bioactivity of melatonin in fermented products and its implications for human health. These findings highlight the broader potential of biosensor technology in streamlining analytical processes in fermentation science.

Limiting the Broadcast Range of a Secreting Cell during Intercellular Signaling Using Protease-Mediated Degradation

Synthetic biology is revolutionizing our approaches to biocomputing, diagnostics, and environmental monitoring through the use of designed genetic circuits that perform a function within a single cell. More complex functions can be performed by multiple cells that coordinate as they perform different subtasks. Cell-cell communication using molecular signals is particularly suited for aiding in this communication, but the number of molecules that can be used in different communication channels is limited. Here we investigate how proteases can limit the broadcast range of communicating cells. We find that adding barrierpepsin to Saccharomyces cerevisiae cells in two-dimensional multicellular networks that use α-factor signaling prevents cells beyond a specific radius from responding to α-factor signals. Such limiting of the broadcast range of cells could allow multiple cells to use the same signaling molecules to direct different communication processes and functions, provided that they are far enough from one another. These results suggest a means by which complex synthetic cellular networks using only a few signals for communication could be created by structuring a community of cells to create distinct broadcast environments.

LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae

Temperature is an important control factor for biologics biomanufacturing in precision fermentation. Here, we explored a highly responsive low temperature-inducible genetic system (LowTempGAL) in the model yeast Saccharomyces cerevisiae. Two temperature biosensors, a heat-inducible degron and a heat-inducible protein aggregation domain, were used to regulate the GAL activator Gal4p, rendering the leaky LowTempGAL systems. Boolean-type induction was achieved by implementing a second-layer control through low-temperature-mediated repression on GAL repressor gene GAL80, but suffered delayed response to low-temperature triggers and a weak response at 30°C. Application potentials were validated for protein and small molecule production. Proteomics analysis suggested that residual Gal80p and Gal4p insufficiency caused suboptimal induction. 'Turbo' mechanisms were engineered through incorporating a basal Gal4p expression and a galactose-independent Gal80p-supressing Gal3p mutant (Gal3Cp). Varying Gal3Cp configurations, we deployed the LowTempGAL systems capable for a rapid stringent high-level induction upon the shift from a high temperature (37-33°C) to a low temperature (≤30°C). Overall, we present a synthetic biology procedure that leverages 'leaky' biosensors to deploy highly responsive Boolean-type genetic circuits. The key lies in optimisation of the intricate layout of the multi-factor system. The LowTempGAL systems may be applicable in non-conventional yeast platforms for precision biomanufacturing.

High-throughput G protein-coupled receptor-based autocrine screening for secondary metabolite production in yeast

Biosensors are valuable tools in accelerating the test phase of the design-build-test-learn cycle of cell factory development, as well as in bioprocess monitoring and control. G protein-coupled receptor (GPCR)-based biosensors enable cells to sense a wide array of molecules and environmental conditions in a specific manner. Due to the extracellular nature of their sensing, GPCR-based biosensors require compartmentalization of distinct genotypes when screening production levels of a strain library to ensure that detected levels originate exclusively from the strain under assessment. Here, we explore the integration of production and sensing modalities into a single Saccharomyces cerevisiae strain and compartmentalization using three different methods: (1) cultivation in microtiter plates, (2) spatial separation on agar plates, and (3) encapsulation in water-in-oil-in-water double emulsion droplets, combined with analysis and sorting via a fluorescence-activated cell sorting machine. Employing tryptamine and serotonin as proof-of-concept target molecules, we optimize biosensing conditions and demonstrate the ability of the autocrine screening method to enrich for high producers, showing the enrichment of a serotonin-producing strain over a nonproducing strain. These findings illustrate a workflow that can be adapted to screening for a wide range of complex chemistry at high throughput using commercially available microfluidic systems.

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.

Searching for the optimal microbial factory: high-throughput biosensors and analytical techniques for screening small molecules

High-throughput screening technologies have been lacking in comparison to the plethora of high-throughput genetic diversification techniques developed in biotechnology. This review explores the challenges and advancements in high-throughput screening for high-value natural products, focusing on the critical need to expand ligand targets for biosensors and increase the throughput of analytical techniques in screening microbial cell libraries for optimal strain performance. The engineering techniques to broaden the scope of ligands for biosensors, such as transcription factors, G protein-coupled receptors and riboswitches are discussed. On the other hand, integration of microfluidics with traditional analytical methods is explored, covering fluorescence-activated cell sorting, Raman-activated cell sorting and mass spectrometry, emphasising recent developments in maximising throughput.

Combining enzyme and metabolic engineering for microbial supply of therapeutic phytochemicals

The history of pharmacology is deeply intertwined with plant-derived compounds, which continue to be crucial in drug development. However, their complex structures and limited availability in plants challenge drug discovery, optimization, development, and industrial production via chemical synthesis or natural extraction. This review delves into the integration of metabolic and enzyme engineering to leverage micro-organisms as platforms for the sustainable and reliable production of therapeutic phytochemicals. We argue that engineered microbes can serve a triple role in this paradigm: facilitating pathway discovery, acting as cell factories for scalable manufacturing, and functioning as platforms for chemical derivatization. Analyzing recent progress and outlining future directions, the review highlights microbial biotechnology's transformative potential in expanding plant-derived human therapeutics' discovery and supply chains.

CRISPR-Cas9 mediated genome editing of Kluyveromyces marxianus for iterative, multiplexed gene disruption and pathway integration

Kluyveromyces marxianus, a thermotolerant, fast-growing, Crabtree-negative yeast, is a promising chassis for the manufacture of various bioproducts. Although several genome editing tools are available for this yeast, these tools still require refinement to enable more convenient and efficient genetic modification. In this study, we engineered the K. marxianus NBRC 104275 strain by impairing the nonhomologous end joining and enhancing the homologous recombination machinery, which resulted in improved homology-directed repair effective on homology arms of up to 40 bp in length. Additionally, we simplified the CRISPR-Cas9 editing system by constructing a strain for integrative expression of Cas9 nuclease and plasmids bearing different selection markers for gRNA expression, thereby facilitating iterative genome editing without the need for plasmid curing. We demonstrated that tRNA was more effective than the hammerhead ribozyme for processing gRNA primary transcripts, and readily assembled tRNA-gRNA arrays were used for multiplexed editing of at least four targets. This editing tool was further employed for simultaneous scarless in vivo assembly of a 12-kb cassette from three fragments and marker-free integration for expressing a fusion variant of fatty acid synthase, as well as the integration of genes for starch hydrolysis. Together, the genome editing tool developed in this study makes K. marxianus more amenable to genetic modification and will facilitate more extensive engineering of this nonconventional yeast for chemical production.

Yeast Platforms for Production and Screening of Bioactive Derivatives of Rauwolscine

Monoterpene indole alkaloids (MIAs) make up a highly bioactive class of metabolites produced by a range of tropical and subtropical plants. The corynanthe-type MIAs are a stereochemically complex subclass with therapeutic potential against a large number of indications including cancer, psychotic disorders, and erectile dysfunction. Here, we report yeast-based cell factories capable of de novo production of corynanthe-type MIAs rauwolscine, yohimbine, tetrahydroalstonine, and corynanthine. From this, we demonstrate regioselective biosynthesis of 4 fluorinated derivatives of these compounds and de novo biosynthesis of 7-chlororauwolscine by coexpression of a halogenase with the biosynthetic pathway. Finally, we capitalize on the ability of these cell factories to produce derivatives of these bioactive scaffolds to establish a proof-of-principle drug discovery pipeline in which the corynanthe-type MIAs are screened for bioactivity on human drug targets, expressed in yeast. In doing so, we identify antagonistic and agonistic behavior against the human adrenergic G protein-coupled receptors ADRA2A and ADRA2B, and the serotonergic receptor 5HT4b, respectively. This study thus demonstrates a proto-drug discovery pipeline for bioactive plant-inspired small molecules based on one-pot biocatalysis of natural and new-to-nature corynanthe-type MIAs in yeast.

Tailored UPRE2 variants for dynamic gene regulation in yeast

Genetic elements are foundational in synthetic biology serving as vital building blocks. They enable programming host cells for efficient production of valuable chemicals and recombinant proteins. The unfolded protein response (UPR) is a stress pathway in which the transcription factor Hac1 interacts with the upstream unfolded protein response element (UPRE) of the promoter to restore endoplasmic reticulum (ER) homeostasis. Here, we created a UPRE2 mutant (UPRE2m) library. Several rounds of screening identified many elements with enhanced responsiveness and a wider dynamic range. The most active element m84 displayed a response activity 3.72 times higher than the native UPRE2. These potent elements are versatile and compatible with various promoters. Overexpression of HAC1 enhanced stress signal transduction, expanding the signal output range of UPRE2m. Through molecular modeling and site-directed mutagenesis, we pinpointed the DNA-binding residue Lys60 in Hac1(Hac1-K60). We also confirmed that UPRE2m exhibited a higher binding affinity to Hac1. This shed light on the mechanism underlying the Hac1-UPRE2m interaction. Importantly, applying UPRE2m for target gene regulation effectively increased both recombinant protein production and natural product synthesis. These genetic elements provide valuable tools for dynamically regulating gene expression in yeast cell factories.

DELLA proteins recruit the Mediator complex subunit MED15 to coactivate transcription in land plants

DELLA proteins are negative regulators of the gibberellin response pathway in angiosperms, acting as central hubs that interact with hundreds of transcription factors (TFs) and regulators to modulate their activities. While the mechanism of TF sequestration by DELLAs to prevent DNA binding to downstream targets has been extensively documented, the mechanism that allows them to act as coactivators remains to be understood. Here, we demonstrate that DELLAs directly recruit the Mediator complex to specific loci in Arabidopsis, facilitating transcription. This recruitment involves DELLA amino-terminal domain and the conserved MED15 KIX domain. Accordingly, partial loss of MED15 function mainly disrupted processes known to rely on DELLA coactivation capacity, including cytokinin-dependent regulation of meristem function and skotomorphogenic response, gibberellin metabolism feedback, and flavonol production. We have also found that the single DELLA protein in the liverwort Marchantia polymorpha is capable of recruiting MpMED15 subunits, contributing to transcriptional coactivation. The conservation of Mediator-dependent transcriptional coactivation by DELLA between Arabidopsis and Marchantia implies that this mechanism is intrinsic to the emergence of DELLA in the last common ancestor of land plants.

Yeast-based screening platforms to understand and improve human health

Detailed molecular understanding of the human organism is essential to develop effective therapies. Saccharomyces cerevisiae has been used extensively for acquiring insights into important aspects of human health, such as studying genetics and cell-cell communication, elucidating protein-protein interaction (PPI) networks, and investigating human G protein-coupled receptor (hGPCR) signaling. We highlight recent advances and opportunities of yeast-based technologies for cost-efficient chemical library screening on hGPCRs, accelerated deciphering of PPI networks with mating-based screening and selection, and accurate cell-cell communication with human immune cells. Overall, yeast-based technologies constitute an important platform to support basic understanding and innovative applications towards improving human health.

Cascaded amplifying circuit enables sensitive detection of fungal pathogens

The rapid and accurate detection of fungal pathogens is of utmost importance in the fields of healthcare, food safety, and environmental monitoring. In this study, we implemented a cascaded amplifying circuit in Saccharomyces cerevisiae to improve the G protein-coupled receptor (GPCR) mediated fungal detection. The GPCR signaling pathway was coupled with the galactose-regulated (GAL) system and a positive feedback loop was implemented to enhance the performance of yeast biosensor. We systematically compared four generations of biosensors for detecting the mating pheromone of Candida albicans, and the best biosensor exhibited the limit of detection (LOD) as low as 0.25 pM and the limit of quantification (LOQ) of 1 pM after 2 h incubation. Subsequently, we developed a betaxanthin-based colorimetric module for the easy visualization of signal outputs, and the resulting biosensors can give reliable naked-eye readouts. In summary, we demonstrated that cascaded amplifying circuits could substantially improve the engineered yeast biosensors with a better sensitivity and signal output magnitude, which will pave the way for their real-world applications in public health.

Droplet-based microfluidic platform for detecting agonistic peptides that are self-secreted by yeast expressing a G-protein-coupled receptor

BACKGROUND

Single-cell droplet microfluidics is an important platform for high-throughput analyses and screening because it provides an independent and compartmentalized microenvironment for reaction or cultivation by coencapsulating individual cells with various molecules in monodisperse microdroplets. In combination with microbial biosensors, this technology becomes a potent tool for the screening of mutant strains. In this study, we demonstrated that a genetically engineered yeast strain that can fluorescently sense agonist ligands via the heterologous expression of a human G-protein-coupled receptor (GPCR) and concurrently secrete candidate peptides is highly compatible with single-cell droplet microfluidic technology for the high-throughput screening of new agonistically active peptides.

RESULTS

The water-in-oil microdroplets were generated using a flow-focusing microfluidic chip to encapsulate engineered yeast cells coexpressing a human GPCR [i.e., angiotensin II receptor type 1 (AGTR1)] and a secretory agonistic peptide [i.e., angiotensin II (Ang II)]. The single yeast cells cultured in the droplets were then observed under a microscope and analyzed using image processing incorporating machine learning techniques. The AGTR1-mediated signal transduction elicited by the self-secreted Ang II peptide was successfully detected via the expression of a fluorescent reporter in single-cell yeast droplet cultures. The system could also distinguish Ang II analog peptides with different agonistic activities. Notably, we further demonstrated that the microenvironment of the single-cell droplet culture enabled the detection of rarely existing positive (Ang II-secreting) yeast cells in the model mixed cell library, whereas the conventional batch-culture environment using a shake flask failed to do so. Thus, our approach provided compartmentalized microculture environments, which can prevent the diffusion, dilution, and cross-contamination of peptides secreted from individual single yeast cells for the easy identification of GPCR agonists.

CONCLUSIONS

We established a droplet-based microfluidic platform that integrated an engineered yeast biosensor strain that concurrently expressed GPCR and self-secreted the agonistic peptides. This offers individually isolated microenvironments that allow the culture of single yeast cells secreting these peptides and gaging their signaling activities, for the high-throughput screening of agonistic peptides. Our platform base on yeast GPCR biosensors and droplet microfluidics will be widely applicable to metabolic engineering, environmental engineering, and drug discovery.

A molecular toolkit of cross-feeding strains for engineering synthetic yeast communities

Engineered microbial consortia often have enhanced system performance and robustness compared with single-strain biomanufacturing production platforms. However, few tools are available for generating co-cultures of the model and key industrial host Saccharomyces cerevisiae. Here we engineer auxotrophic and overexpression yeast strains that can be used to create co-cultures through exchange of essential metabolites. Using these strains as modules, we engineered two- and three-member consortia using different cross-feeding architectures. Through a combination of ensemble modelling and experimentation, we explored how cellular (for example, metabolite production strength) and environmental (for example, initial population ratio, population density and extracellular supplementation) factors govern population dynamics in these systems. We tested the use of the toolkit in a division of labour biomanufacturing case study and show that it enables enhanced and tuneable antioxidant resveratrol production. We expect this toolkit to become a useful resource for a variety of applications in synthetic ecology and biomanufacturing.

Exploring engineering strategies that enhance de novo production of exotic cyclopropane fatty acids in Saccharomyces cerevisiae

Cycloalkanes have broad applications as specialty fuels, lubricants, and pharmaceuticals but are not currently available from renewable sources, whereas, production of microbial cycloalkanes such as cyclopropane fatty acids (CFA) has bottlenecks. Here, a systematic investigation was undertaken into the biosynthesis of CFA in Saccharomyces cerevisiae heterologously expressing bacterial CFA synthase. The enzyme catalyzes formation of a 3-membered ring in unsaturated fatty acids. Monounsaturated fatty acids in phospholipids (PL) are the site of CFA synthesis; precursor cis-Δ9 C16 and C18 fatty acids were enhanced through OLE1 and SAM2 overexpression which enhanced CFA in PL. CFA turnover from PL to storage in triacylglycerols (TAG) was achieved by phospholipase PBL2 overexpression and acyl-CoA synthase to increase flux to TAG. Consequently, CFA storage as TAG reached 12 mg g-1 DCW, improved 3-fold over the base strain and >22% of TAG was CFA. Our research improves understanding of cycloalkane biosynthesis in yeast and offers insights into processing of other exotic fatty acids.

A Standardized Set of MoClo-Compatible Inducible Promoter Systems for Tunable Gene Expression in Yeast

Small-molecule control of gene expression underlies the function of numerous engineered gene circuits that are capable of environmental sensing, computation, and memory. While many recently developed inducible promoters have been tailor-made for bacteria or mammalian cells, relatively few new systems have been built for Saccharomyces cerevisiae, limiting the scale of synthetic biology work that can be done in yeast. To address this, we created the yeast Tunable Expression Systems Toolkit (yTEST), which contains a set of five extensively characterized inducible promoter systems regulated by the small-molecules doxycycline (Dox), abscisic acid (ABA), danoprevir (DNV), 1-naphthaleneacetic acid (NAA), and 5-phenyl-indole-3-acetic acid (5-Ph-IAA). Assembly was made to be compatible with the modular cloning yeast toolkit (MoClo-YTK) to enhance the ease of use and provide a framework to benchmark and standardize each system. Using this approach, we built multiple systems with maximal expression levels greater than those of the strong constitutive TDH3 promoter. Furthermore, each of the five classes of systems could be induced at least 60-fold after a 6 h induction and the highest fold change observed was approximately 300. Thus, yTEST provides a reliable, diverse, and customizable set of inducible promoters to modulate gene expression in yeast for applications in synthetic biology, metabolic engineering, and basic research.

Evaluation and comparison of colorimetric outputs for yeast-based biosensors in laboratory and point-of-use settings

Recent research has shown the potential of yeast-based biosensors (YBBs) for point-of-use detection of pathogens and target molecules in saliva, blood, and urine samples. The choice of output can greatly affect the sensitivity, dynamic range, detection time, and ease-of-use of a sensor. For visual detection without the need for additional reagents or machinery, colorimetric outputs have shown great potential. Here, we evaluated the inducible generation of prodeoxyviolacein and proviolacein as colorimetric YBB outputs and benchmarked these against lycopene. The outputs were induced via the yeast mating pathway and were compared on agar plates, in liquid culture, and on paper slips. We found that all three outputs produced comparable pigment intensity on agar plates, making them applicable for bioengineering settings. In liquid media and on paper slips, lycopene resulted in a higher intensity pigment and a decreased time-of-detection.

Saccharomyces boulardii promoters for control of gene expression in vivo

BACKGROUND

Interest in the use of engineered microbes to deliver therapeutic activities has increased in recent years. The probiotic yeast Saccharomyces boulardii has been investigated for production of therapeutics in the gastrointestinal tract. Well-characterised promoters are a prerequisite for robust therapeutic expression in the gut; however, S. boulardii promoters have not yet been thoroughly characterised in vitro and in vivo.

RESULTS

We present a thorough characterisation of the expression activities of 12 S. boulardii promoters in vitro in glucose, fructose, sucrose, inulin and acetate, under both aerobic and anaerobic conditions, as well as in the murine gastrointestinal tract. Green fluorescent protein was used to report on promoter activity. Promoter expression was found to be carbon-source dependent, with inulin emerging as a favourable carbon source. Furthermore, relative promoter expression in vivo was highly correlated with expression in sucrose (R = 0.99).

CONCLUSIONS

These findings provide insights into S. boulardii promoter activity and aid in promoter selection in future studies utilising S. boulardii to produce therapeutics in the gut.

Engineering and evolution of the complete Reductive Glycine Pathway in Saccharomyces cerevisiae for formate and CO2 assimilation

Using captured CO2 and C1-feedstocks like formate and methanol derived from electrochemical activation of CO2 are key solutions for transforming industrial processes towards a circular carbon economy. Engineering formate and CO2-based growth in the biotechnologically relevant yeast Saccharomyces cerevisiae could boost the emergence of a formate-mediated circular bio-economy. This study adopts a growth-coupled selection scheme for modular implementation of the Reductive Glycine Pathway (RGP) and subsequent Adaptive Laboratory Evolution (ALE) to enable formate and CO2 assimilation for biomass formation in yeast. We first constructed a serine biosensor strain and then implemented the serine synthesis module of the RGP into yeast, establishing glycine and serine synthesis from formate and CO2. ALE improved the RGP-dependent growth by 8-fold. 13C-labeling experiments reveal glycine, serine, and pyruvate synthesis via the RGP, demonstrating the complete pathway activity. Further, we re-established formate and CO2-dependent growth in non-evolved biosensor strains via reverse-engineering a mutation in GDH1 identified from ALE. This mutation led to significantly more 13C-formate assimilation than in WT without any selection or overexpression of the RGP. Overall, we demonstrated the activity of the complete RGP, showing evidence for carbon transfer from formate to pyruvate coupled with CO2 assimilation.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Reshaping the yeast galactose regulon via GPCR signaling cascade

Dynamically regulated systems are preferable to control metabolic pathways for an improved strain performance with better productivity. Here, we harnessed to the G protein-coupled receptor (GPCR) signaling pathway to reshape the yeast galactose regulon. The galactose-regulated (GAL) system was coupled with the GPCR signaling pathway for mating pheromone via a synthetic transcription factor. In this study, we refabricated the dynamic range, sensitivity, and response time of the GAL system to α factor by modulating the key components of the GPCR signaling cascade. A series of engineered yeasts with self-secretion of α factor were constructed to achieve quorum-sensing behaviors. In addition, we also repurposed the GAL system to make it responsive to heat shock. Taken together, our work showcases the great potential of synthetic biology in creating user-defined metabolic controls. We envision that the plasticity of our genetic design would be of significant interest for the future fabrication of novel gene expression systems.

Customizing cellular signal processing by synthetic multi-level regulatory circuits

As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.

Biosynthesis of natural and halogenated plant monoterpene indole alkaloids in yeast

Monoterpenoid indole alkaloids (MIAs) represent a large class of plant natural products with marketed pharmaceutical activities against a wide range of indications, including cancer, malaria and hypertension. Halogenated MIAs have shown improved pharmaceutical properties; however, synthesis of new-to-nature halogenated MIAs remains a challenge. Here we demonstrate a platform for de novo biosynthesis of two MIAs, serpentine and alstonine, in baker's yeast Saccharomyces cerevisiae and deploy it to systematically explore the biocatalytic potential of refactored MIA pathways for the production of halogenated MIAs. From this, we demonstrate conversion of individual haloindole derivatives to a total of 19 different new-to-nature haloserpentine and haloalstonine analogs. Furthermore, by process optimization and heterologous expression of a modified halogenase in the microbial MIA platform, we document de novo halogenation and biosynthesis of chloroalstonine. Together, this study highlights a microbial platform for enzymatic exploration and production of complex natural and new-to-nature MIAs with therapeutic potential.

A Multiplex MoClo Toolkit for Extensive and Flexible Engineering of Saccharomyces cerevisiae

Synthetic biology toolkits are one of the core foundations on which the field has been built, facilitating and accelerating efforts to reprogram cells and organisms for diverse biotechnological applications. The yeast Saccharomyces cerevisiae, an important model and industrial organism, has benefited from a wide range of toolkits. In particular, the MoClo Yeast Toolkit (YTK) enables the fast and straightforward construction of multigene plasmids from a library of highly characterized parts for programming new cellular behavior in a more predictable manner. While YTK has cultivated a strong parts ecosystem and excels in plasmid construction, it is limited in the extent and flexibility with which it can create new strains of yeast. Here, we describe a new and improved toolkit, the Multiplex Yeast Toolkit (MYT), that extends the capabilities of YTK and addresses strain engineering limitations. MYT provides a set of new integration vectors and selectable markers usable across common laboratory strains, as well as additional assembly cassettes to increase the number of transcriptional units in multigene constructs, CRISPR-Cas9 tools for highly efficient multiplexed vector integration, and three orthogonal and inducible promoter systems for conditional programming of gene expression. With these tools, we provide yeast synthetic biologists with a powerful platform to take their engineering ambitions to exciting new levels.

Synthetic yeast chromosome XI design provides a testbed for the study of extrachromosomal circular DNA dynamics

We describe construction of the synthetic yeast chromosome XI (synXI) and reveal the effects of redesign at non-coding DNA elements. The 660-kb synthetic yeast genome project (Sc2.0) chromosome was assembled from synthesized DNA fragments before CRISPR-based methods were used in a process of bug discovery, redesign, and chromosome repair, including precise compaction of 200 kb of repeat sequence. Repaired defects were related to poor centromere function and mitochondrial health and were associated with modifications to non-coding regions. As part of the Sc2.0 design, loxPsym sequences for Cre-mediated recombination are inserted between most genes. Using the GAP1 locus from chromosome XI, we show that these sites can facilitate induced extrachromosomal circular DNA (eccDNA) formation, allowing direct study of the effects and propagation of these important molecules. Construction and characterization of synXI contributes to our understanding of non-coding DNA elements, provides a useful tool for eccDNA study, and will inform future synthetic genome design.

Synthetic biology tools for environmental protection

Synthetic biology transforms the way we perceive biological systems. Emerging technologies in this field affect many disciplines of science and engineering. Traditionally, synthetic biology approaches were commonly aimed at developing cost-effective microbial cell factories to produce chemicals from renewable sources. Based on this, the immediate beneficial impact of synthetic biology on the environment came from reducing our oil dependency. However, synthetic biology is starting to play a more direct role in environmental protection. Toxic chemicals released by industries and agriculture endanger the environment, disrupting ecosystem balance and biodiversity loss. This review highlights synthetic biology approaches that can help environmental protection by providing remediation systems capable of sensing and responding to specific pollutants. Remediation strategies based on genetically engineered microbes and plants are discussed. Further, an overview of computational approaches that facilitate the design and application of synthetic biology tools in environmental protection is presented.

Living Magnetotactic Microrobots Based on Bacteria with a Surface-Displayed CRISPR/Cas12a System for Penaeus Viruses Detection

Bacterial microrobots are an emerging living material in the field of diagnostics. However, it is an important challenge to make bacterial microrobots with both controlled motility and specific functions. Herein, magnetically driven diagnostic bacterial microrobots are prepared by standardized and modular synthetic biology methods. To ensure mobility, the Mms6 protein is displayed on the surface of bacteria and is exploited for magnetic biomineralization. This gives the bacterial microrobot the ability to cruise flexibly and rapidly with a magnetization intensity up to about 18.65 emu g-1. To achieve the diagnostic function, the Cas12a protein is displayed on the bacterial surface and is used for aquatic pathogen nucleic acid detection. This allows the bacterial microrobot to achieve sensitive, rapid, and accurate on-site nucleic acid detection, with detection limits of 8 copies μL-1 for decapod iridescent virus 1 (DIV1) and 7 copies μL-1 for white spot syndrome virus (WSSV). In particular, the diagnostic results based on the bacterial microrobots remained consistent with the gold standard test results when tested on shrimp tissue. This approach is a flexible and customizable strategy for building bacterial microrobots, providing a reliable and versatile solution for the design of bacterial microrobots.

Automation protocol for high-efficiency and high-quality genomic DNA extraction from Saccharomyces cerevisiae

Although many protocols have been previously developed for genomic DNA (gDNA) extraction from S. cerevisiae, to take advantage of recent advances in laboratory automation and DNA-barcode sequencing, there is a need for automated methods that can provide high-quality gDNA at high efficiency. Here, we describe and demonstrate a fully automated protocol that includes five basic steps: cell wall and RNA digestion, cell lysis, DNA binding to magnetic beads, washing with ethanol, and elution. Our protocol avoids the use of hazardous reagents (e.g., phenol, chloroform), glass beads for mechanical cell disruption, or incubation of samples at 100°C (i.e., boiling). We show that our protocol can extract gDNA with high efficiency both from cells grown in liquid culture and from colonies grown on agar plates. We also show results from gel electrophoresis that demonstrate that the resulting gDNA is of high quality.

Visioning synthetic futures for yeast research within the context of current global techno-political trends

Yeast research is entering into a new period of scholarship, with new scientific tools, new questions to ask and new issues to consider. The politics of emerging and critical technology can no longer be separated from the pursuit of basic science in fields, such as synthetic biology and engineering biology. Given the intensifying race for technological leadership, yeast research is likely to attract significant investment from government, and that it offers huge opportunities to the curious minded from a basic research standpoint. This article provides an overview of new directions in yeast research with a focus on Saccharomyces cerevisiae, and places these trends in their geopolitical context. At the highest level, yeast research is situated within the ongoing convergence of the life sciences with the information sciences. This convergent effect is most strongly pronounced in areas of AI-enabled tools for the life sciences, and the creation of synthetic genomes, minimal genomes, pan-genomes, neochromosomes and metagenomes using computer-assisted design tools and methodologies. Synthetic yeast futures encompass basic and applied science questions that will be of intense interest to government and nongovernment funding sources. It is essential for the yeast research community to map and understand the context of their research to ensure their collaborations turn global challenges into research opportunities.

Recovery of the histamine H3 receptor activity lost in yeast cells through error-prone PCR and in vivo selection

G protein-coupled receptors (GPCRs) are the largest protein family in humans and are important drug targets. Yeast, especially Saccharomyces cerevisiae, is a useful host for modifying the function and stability of GPCRs through protein engineering, which is advantageous for mammalian cells. When GPCRs are expressed in yeast, their function is often impaired. In this study, we performed random mutagenesis using error-prone PCR and then an in vivo screening to obtain mutants that recovered the activity of the human histamine H3 receptor (H3R), which loses its signaling function when expressed in yeast. Four mutations with recovered activity were identified after screening. Three of the mutations were identified near the DRY and NPxxY motifs of H3R, which are important for activation and are commonly found in class A GPCRs. The mutants responded exclusively to the yeast YB1 strain harboring Gi-chimera proteins, showing retention of G protein specificity. Analysis of one of the mutants with recovered activity, C415R, revealed that it maintained its ligand-binding characteristics. The strategy used in this study may enable the recovery of the activity of other GPCRs that do not function in S. cerevisiae and may be useful in creating GPCRs mutants stabilized in their active conformations.

Modularized synthetic biology enabled intelligent biosensors

Biosensors that sense the concentration of a specified target and produce a specific signal output have become important technology for biological analysis. Recently, intelligent biosensors have received great interest due to their adaptability to meet sophisticated demands. Advances in developing standard modules and carriers in synthetic biology have shed light on intelligent biosensors that can implement advanced analytical processing to better accommodate practical applications. This review focuses on intelligent synthetic biology-enabled biosensors (SBBs). First, we illustrate recent progress in intelligent SBBs with the capability of computation, memory storage, and self-calibration. Then, we discuss emerging applications of SBBs in point-of-care testing (POCT) and wearable monitoring. Finally, future perspectives on intelligent SBBs are proposed.

Sensitivity analysis of biochemical systems using bond graphs

The sensitivity of systems biology models to parameter variation can give insights into which parameters are most important for physiological function, and also direct efforts to estimate parameters. However, in general, kinetic models of biochemical systems do not remain thermodynamically consistent after perturbing parameters. To address this issue, we analyse the sensitivity of biological reaction networks in the context of a bond graph representation. We find that the parameter sensitivities can themselves be represented as bond graph components, mirroring potential mechanisms for controlling biochemistry. In particular, a sensitivity system is derived which re-expresses parameter variation as additional system inputs. The sensitivity system is then linearized with respect to these new inputs to derive a linear system which can be used to give local sensitivity to parameters in terms of linear system properties such as gain and time constant. This linear system can also be used to find so-called sloppy parameters in biological models. We verify our approach using a model of the Pentose Phosphate Pathway, confirming the reactions and metabolites most essential to maintaining the function of the pathway.

Bayesian Optimization for Design of Multiscale Biological Circuits

Recent advances in synthetic biology have enabled the construction of molecular circuits that operate across multiple scales of cellular organization, such as gene regulation, signaling pathways, and cellular metabolism. Computational optimization can effectively aid the design process, but current methods are generally unsuited for systems with multiple temporal or concentration scales, as these are slow to simulate due to their numerical stiffness. Here, we present a machine learning method for the efficient optimization of biological circuits across scales. The method relies on Bayesian optimization, a technique commonly used to fine-tune deep neural networks, to learn the shape of a performance landscape and iteratively navigate the design space toward an optimal circuit. This strategy allows the joint optimization of both circuit architecture and parameters, and provides a feasible approach to solve a highly nonconvex optimization problem in a mixed-integer input space. We illustrate the applicability of the method on several gene circuits for controlling biosynthetic pathways with strong nonlinearities, multiple interacting scales, and using various performance objectives. The method efficiently handles large multiscale problems and enables parametric sweeps to assess circuit robustness to perturbations, serving as an efficient in silico screening method prior to experimental implementation.

Modular Metabolic Engineering and Synthetic Coculture Strategies for the Production of Aromatic Compounds in Yeast

Microbial-derived aromatics provide a sustainable and renewable alternative to petroleum-derived chemicals. In this study, we used the model yeast Saccharomyces cerevisiae to produce aromatic molecules by exploiting the concept of modularity in synthetic biology. Three different modular approaches were investigated for the production of the valuable fragrance raspberry ketone (RK), found in raspberry fruits and mostly produced from petrochemicals. The first strategy used was modular cloning, which enabled the generation of combinatorial libraries of promoters to optimize the expression level of the genes involved in the synthesis pathway of RK. The second strategy was modular pathway engineering and involved the creation of four modules, one for product formation: RK synthesis module (Mod. RK); and three for precursor synthesis: aromatic amino acid synthesis module (Mod. Aro), p-coumaric acid synthesis module (Mod. p-CA), and malonyl-CoA synthesis module (Mod. M-CoA). The production of RK by combinations of the expression of these modules was studied, and the best engineered strain produced 63.5 mg/L RK from glucose, which is the highest production described in yeast, and 2.1 mg RK/g glucose, which is the highest yield reported in any organism without p-coumaric acid supplementation. The third strategy was the use of modular cocultures to explore the effects of division of labor on RK production. Two two-member communities and one three-member community were created, and their production capacity was highly dependent on the structure of the synthetic community, the inoculation ratio, and the culture media. In certain conditions, the cocultures outperformed their monoculture controls for RK production, although this was not the norm. Interestingly, the cocultures showed up to 7.5-fold increase and 308.4 mg/L of 4-hydroxy benzalacetone, the direct precursor of RK, which can be used for the semi-synthesis of RK. This study illustrates the utility of modularity in synthetic biology tools and their applications to the synthesis of products of industrial interest.

Peroxisome biogenesis initiated by protein phase separation

Peroxisomes are organelles that carry out β-oxidation of fatty acids and amino acids. Both rare and prevalent diseases are caused by their dysfunction1. Among disease-causing variant genes are those required for protein transport into peroxisomes. The peroxisomal protein import machinery, which also shares similarities with chloroplasts2, is unique in transporting folded and large, up to 10 nm in diameter, protein complexes into peroxisomes3. Current models postulate a large pore formed by transmembrane proteins4; however, so far, no pore structure has been observed. In the budding yeast Saccharomyces cerevisiae, the minimum transport machinery includes the membrane proteins Pex13 and Pex14 and the cargo-protein-binding transport receptor, Pex5. Here we show that Pex13 undergoes liquid-liquid phase separation (LLPS) with Pex5-cargo. Intrinsically disordered regions in Pex13 and Pex5 resemble those found in nuclear pore complex proteins. Peroxisomal protein import depends on both the number and pattern of aromatic residues in these intrinsically disordered regions, consistent with their roles as 'stickers' in associative polymer models of LLPS5,6. Finally, imaging fluorescence cross-correlation spectroscopy shows that cargo import correlates with transient focusing of GFP-Pex13 and GFP-Pex14 on the peroxisome membrane. Pex13 and Pex14 form foci in distinct time frames, suggesting that they may form channels at different saturating concentrations of Pex5-cargo. Our findings lead us to suggest a model in which LLPS of Pex5-cargo with Pex13 and Pex14 results in transient protein transport channels7.

Automated design of protein-binding riboswitches for sensing human biomarkers in a cell-free expression system

Cell-free genetically encoded biosensors have been developed to detect small molecules and nucleic acids, but they have yet to be reliably engineered to detect proteins. Here we develop an automated platform to convert protein-binding RNA aptamers into riboswitch sensors that operate within low-cost cell-free assays. We demonstrate the platform by engineering 35 protein-sensing riboswitches for human monomeric C-reactive protein, human interleukin-32γ, and phage MS2 coat protein. The riboswitch sensors regulate output expression levels by up to 16-fold with input protein concentrations within the human serum range. We identify two distinct mechanisms governing riboswitch-mediated regulation of translation rates and leverage computational analysis to refine the protein-binding aptamer regions, improving design accuracy. Overall, we expand the cell-free sensor toolbox and demonstrate how computational design is used to develop protein-sensing riboswitches with future applications as low-cost medical diagnostics.

Overcoming the Limitations of CRISPR-Cas9 Systems in Saccharomyces cerevisiae: Off-Target Effects, Epigenome, and Mitochondrial Editing

Modification of the genome of the yeast Saccharomyces cerevisiae has great potential for application in biological research and biotechnological advancements, and the CRISPR-Cas9 system has been increasingly employed for these purposes. The CRISPR-Cas9 system enables the precise and simultaneous modification of any genomic region of the yeast to a desired sequence by altering only a 20-nucleotide sequence within the guide RNA expression constructs. However, the conventional CRISPR-Cas9 system has several limitations. In this review, we describe the methods that were developed to overcome these limitations using yeast cells. We focus on three types of developments: reducing the frequency of unintended editing to both non-target and target sequences in the genome, inducing desired changes in the epigenetic state of the target region, and challenging the expansion of the CRISPR-Cas9 system to edit genomes within intracellular organelles such as mitochondria. These developments using yeast cells to overcome the limitations of the CRISPR-Cas9 system are a key factor driving the advancement of the field of genome editing.

Ultra-high throughput mapping of genetic design space

Massively parallel genetic screens have been used to map sequence-to-function relationships for a variety of genetic elements. However, because these approaches only interrogate short sequences, it remains challenging to perform high throughput (HT) assays on constructs containing combinations of sequence elements arranged across multi-kb length scales. Overcoming this barrier could accelerate synthetic biology; by screening diverse gene circuit designs, "composition-to-function" mappings could be created that reveal genetic part composability rules and enable rapid identification of behavior-optimized variants. Here, we introduce CLASSIC, a generalizable genetic screening platform that combines long- and short-read next-generation sequencing (NGS) modalities to quantitatively assess pooled libraries of DNA constructs of arbitrary length. We show that CLASSIC can measure expression profiles of >10 ⁵ drug-inducible gene circuit designs (ranging from 6-9 kb) in a single experiment in human cells. Using statistical inference and machine learning (ML) approaches, we demonstrate that data obtained with CLASSIC enables predictive modeling of an entire circuit design landscape, offering critical insight into underlying design principles. Our work shows that by expanding the throughput and understanding gained with each design-build-test-learn (DBTL) cycle, CLASSIC dramatically augments the pace and scale of synthetic biology and establishes an experimental basis for data-driven design of complex genetic systems.

Peptide Variant Detection by a Living Yeast Biosensor via an Epitope-Selective Protease

We previously demonstrated that we could hijack the fungal pheromone signaling pathway to provide a living yeast biosensor where peptide biomarkers were recognized by G-protein-coupled receptors and engineered to transcribe a readout. Here, we demonstrated that the protease could be reintroduced to the biosensor to provide a simple mechanism for distinguishing single-amino-acid changes in peptide ligands that, otherwise, would likely be difficult to detect using binding-based assays. We characterized the dose-response curves for five fungal pheromone G-protein-coupled receptors, peptides, and proteases-Saccharomyces cerevisiae, Candida albicans, Schizosaccharomyces pombe, Schizosaccharomyces octosporus, and Schizosaccharomyces japonicus. Alanine scanning was carried out for the most selective of these-S. cerevisiae and C. albicans-with and without the protease. Two peptide variants were discovered, which showed diminished cleavage by the protease (CaPep2A and CaPep2A13A). Those peptides were then distinguished by utilizing the biosensor strains with and without the protease, which selectively cleaved and altered the apparent concentration of peptide required for half-maximal activation for 2 peptides-CaPep and CaPep13A, respectively-by more than one order of magnitude. These results support the hypothesis that the living yeast biosensor with a sequence-specific protease can translate single-amino-acid changes into more than one order of magnitude apparent shift in the concentration of peptide required for half-maximal activation. With further engineering by computational modeling and directed evolution, the biosensor could likely distinguish a wide variety of peptide sequences beyond the alanine scanning carried out here. In the future, we envision incorporating proteases into our living yeast biosensor for use as a point of care diagnostic, a scalable communication language, and other applications.

Adaptive partitioning of a gene locus to the nuclear envelope in Saccharomyces cerevisiae is driven by polymer-polymer phase separation

Partitioning of active gene loci to the nuclear envelope (NE) is a mechanism by which organisms increase the speed of adaptation and metabolic robustness to fluctuating resources in the environment. In the yeast Saccharomyces cerevisiae, adaptation to nutrient depletion or other stresses, manifests as relocalization of active gene loci from nucleoplasm to the NE, resulting in more efficient transport and translation of mRNA. The mechanism by which this partitioning occurs remains a mystery. Here, we demonstrate that the yeast inositol depletion-responsive gene locus INO1 partitions to the nuclear envelope, driven by local histone acetylation-induced polymer-polymer phase separation from the nucleoplasmic phase. This demixing is consistent with recent evidence for chromatin phase separation by acetylation-mediated dissolution of multivalent histone association and fits a physical model where increased bending stiffness of acetylated chromatin polymer causes its phase separation from de-acetylated chromatin. Increased chromatin spring stiffness could explain nucleation of transcriptional machinery at active gene loci.

Optogenetic control of beta-carotene bioproduction in yeast across multiple lab-scales

Optogenetics arises as a valuable tool to precisely control genetic circuits in microbial cell factories. Light control holds the promise of optimizing bioproduction methods and maximizing yields, but its implementation at different steps of the strain development process and at different culture scales remains challenging. In this study, we aim to control beta-carotene bioproduction using optogenetics in Saccharomyces cerevisiae and investigate how its performance translates across culture scales. We built four lab-scale illumination devices, each handling different culture volumes, and each having specific illumination characteristics and cultivating conditions. We evaluated optogenetic activation and beta-carotene production across devices and optimized them both independently. Then, we combined optogenetic induction and beta-carotene production to make a light-inducible beta-carotene producer strain. This was achieved by placing the transcription of the bifunctional lycopene cyclase/phytoene synthase CrtYB under the control of the pC120 optogenetic promoter regulated by the EL222-VP16 light-activated transcription factor, while other carotenogenic enzymes (CrtI, CrtE, tHMG) were expressed constitutively. We show that illumination, culture volume and shaking impact differently optogenetic activation and beta-carotene production across devices. This enabled us to determine the best culture conditions to maximize light-induced beta-carotene production in each of the devices. Our study exemplifies the stakes of scaling up optogenetics in devices of different lab scales and sheds light on the interplays and potential conflicts between optogenetic control and metabolic pathway efficiency. As a general principle, we propose that it is important to first optimize both components of the system independently, before combining them into optogenetic producing strains to avoid extensive troubleshooting. We anticipate that our results can help designing both strains and devices that could eventually lead to larger scale systems in an effort to bring optogenetics to the industrial scale.

Engineering Pheromone-Mediated Quorum Sensing with Enhanced Response Output Increases Fucosyllactose Production in Saccharomyces cerevisiae

Engineering dynamic control of gene expression is desirable because many engineered functions interfere with endogenous cellular processes that have evolved to facilitate growth and survival. Minimizing conflict between growth and production phases can therefore improve product titers in microbial cell factories. We developed an autoinduced gene expression system by rewiring the Saccharomyces cerevisiae pheromone response pathway. To ameliorate growth reduction due to the early onset response at low population densities, α-pheromone of Kluyveromyces lactis (Kα) instead of S. cerevisiae (Sα) was expressed in mating type "a" yeast. Kα-induced expression of pathway genes was further enhanced by the transcriptional activator Gal4p expressed under the control of the pheromone-responsive FUS1 promoter (P_fus1). As a demonstration, the engineered circuit combined with the deletion of the endogenous galactose metabolic pathway genes was applied to the production of human milk oligosaccharides, 2'-fucosyllactose (2'-FL) and 3-fucosllactose (3-FL). The engineered strains produced 3.37 g/L 2'-FL and 2.36 g/L 3-FL on glucose with a volumetric productivity of 0.14 and 0.03 g/L·h^-1 in batch flask cultivation, respectively. These represented 147 and 153% increases over the control strains on galactose wherein the respective pathway genes are expressed under GAL promoters only. Further fed-batch fermentation achieved titers of 32.05 and 20.91 g/L for 2' and 3-FL, respectively. The genetic program developed here thus represents a promising option for implementing dynamic regulation in yeast and could be used for the production of biochemicals that may place a heavy metabolic burden on cell growth.

Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

We previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. The design process of NFEPP was based on mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands, recognizing that GPCRs function differently under pathological versus healthy conditions. We now present an additional and novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels and their dependence on parameters of inflamed and healthy tissue (pH, radicals). The model is validated against in vitro experimental data for the ligands NFEPP and fentanyl at different pH values and radical concentrations. We observe markedly reduced binding affinity and calcium channel inhibition for NFEPP at normal pH compared to lower pH, in contrast to the effect of fentanyl. For increasing radical concentrations, we find enhanced constitutive G-protein activation but reduced ligand binding affinity. Assessing the different effects, the results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account.

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.

Improved Split TEV GPCR β-arrestin-2 Recruitment Assays via Systematic Analysis of Signal Peptide and β-arrestin Binding Motif Variants

G protein-coupled receptors (GPCRs) are major disease-relevant drug targets; robust monitoring of their activities upon drug treatment is key to drug discovery. The split TEV cell-based assay technique monitors the interaction of an activated GPCR with β-arrestin-2 through TEV protein fragment complementation using a luminescent signal as the readout. In this work, split TEV GPCR β-arrestin-2 recruitment assays were optimized to monitor the endogenous ligand-induced activities of six GPCRs (DRD1, DRD2, HTR2A, GCGR, AVPR2, and GLP1R). Each GPCR was tested in four forms; i.e., its wildtype form, a variant with a signal peptide (SP) to facilitate receptor expression, a variant containing the C-terminal tail from the V2 vasopressin receptor (V2R tail) to promote β-arrestin-2 recruitment, and a variant containing both the SP and V2R tail. These 24 GPCR variants were systematically tested for assay performance in four cell lines (HEK-293, PC12 Tet-Off, U-2 OS, and HeLa). We found that the assay performance differed significantly for each GPCR variant and was dependent on the cell line. We found that V2R improved the DRD2 split TEV assays and that HEK-293 cells were the preferred cell line across the GPCRs tested. When taking these considerations into account, the defined selection of assay modifications and conditions may improve the performance of drug development campaigns that apply the split TEV technique as a screening tool.

Olfactory Receptors as an Emerging Chemical Sensing Scaffold

Chemical biosensors are an increasingly ubiquitous part of our lives. Beyond enzyme-coupled assays, recent synthetic biology advances now allow us to hijack more complex biosensing systems to respond to difficult to detect analytes, such as chemical small molecules. Here, we briefly overview recent advances in the biosensing of small molecules, including nucleic acid aptamers, allosteric transcription factors, and two-component systems. We then look more closely at a recently developed chemical sensing system, G protein-coupled receptor (GPCR)-based sensors. Finally, we consider the chemical sensing capabilities of the largest GPCR subfamily, olfactory receptors (ORs). We examine ORs' role in nature, their potential as a biomedical target, and their ability to detect compounds not amenable for detection using other biological scaffolds. We conclude by evaluating the current challenges, opportunities, and future applications of GPCR- and OR-based sensors.

Engineered cell differentiation and sexual reproduction in probiotic and mating yeasts

G protein-coupled receptors (GPCRs) enable cells to sense environmental cues and are indispensable for coordinating vital processes including quorum sensing, proliferation, and sexual reproduction. GPCRs comprise the largest class of cell surface receptors in eukaryotes, and for more than three decades the pheromone-induced mating pathway in baker's yeast Saccharomyces cerevisiae has served as a model for studying heterologous GPCRs (hGPCRs). Here we report transcriptome profiles following mating pathway activation in native and hGPCR-signaling yeast and use a model-guided approach to correlate gene expression to morphological changes. From this we demonstrate mating between haploid cells armed with hGPCRs and endogenous biosynthesis of their cognate ligands. Furthermore, we devise a ligand-free screening strategy for hGPCR compatibility with the yeast mating pathway and enable hGPCR-signaling in the probiotic yeast Saccharomyces boulardii. Combined, our findings enable new means to study mating, hGPCR-signaling, and cell-cell communication in a model eukaryote and yeast probiotics.