Engineering G protein-coupled receptor signalling in yeast for biotechnological and medical purposes

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.

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.

High-throughput DNA engineering by mating bacteria

To reduce the operational friction and scale DNA engineering, we report here an in vivo DNA assembly technology platform called SCRIVENER (Sequential Conjugation and Recombination for In Vivo Elongation of Nucleotides with low ERrors). SCRIVENER combines bacterial conjugation, in vivo DNA cutting, and in vivo homologous recombination to seamlessly stitch blocks of DNA together by mating E. coli in large arrays or pools. This workflow is simpler, cheaper, and higher throughput than current DNA assembly approaches that require DNA to be moved in and out of cells at different procedural steps. We perform over 5,000 assemblies with two to 13 DNA blocks that range from 240 bp to 8 kb and show that SCRIVENER is capable of assembling constructs as long as 23 kb at relatively high throughput and fidelity. Most SCRIVENER errors are deletions between long interspersed repeats. However, SCRIVENER can overcome these errors by enabling assembly and sequence verification at high replication at a nominal additional cost per replicate. We show that SCRIVENER can be used to build combinatorial libraries in arrays or pools, and that DNA blocks onboarded into the platform can be repurposed and reused with any other DNA block in high throughput without a PCR step. Because of these features, DNA engineering with SCRIVENER has the potential to accelerate design-build-test-learn cycles of DNA products.

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.

Emerging trends in production of plant natural products and new-to-nature biopharmaceuticals in yeast

Natural products represent an inestimable source of valuable compounds for human health. Notably, those produced by plants remain challenging to access due to their low production. Potential shortages of plant-derived biopharmaceuticals caused by climate change or pandemics also regularly tense the market trends. Thus, biotechnological alternatives of supply based on synthetic biology have emerged. These innovative strategies mostly rely on the use of engineered microbial systems for compound synthesis. In this regard, yeasts remain the easiest-tractable eukaryotic models and a convenient chassis for reconstructing whole biosynthetic routes for the heterologous production of plant-derived metabolites. Here, we highlight the recent discoveries dedicated to the bioproduction of new-to-nature compounds in yeasts and provide an overview of emerging strategies for optimising bioproduction.

Technologies for the discovery of G protein-coupled receptor-targeting biologics

G protein-coupled receptors (GPCRs) are important pharmaceutical targets, working as entry points for signaling pathways involved in metabolic, neurological, and cardiovascular diseases. Although small molecules remain the major GPCR drug type, biologic therapeutics, such as peptides and antibodies, are increasingly found among clinical trials and Food and Drug Administration (FDA)-approved drugs. Here, we review state-of-the-art technologies for the engineering of biologics that target GPCRs, as well as proof-of-principle technologies that are ripe for this application. Looking ahead, inexpensive DNA synthesis will enable the routine generation of computationally predesigned libraries for use in display assays for the rapid discovery of GPCR binders. Advances in synthetic biology are enabling the increased throughput of functional GPCR assays to the point that they can be used to directly identify biologics that modulate GPCR activity. Finally, we give an overview of adjacent technologies that are ripe for application to discover biologics that target human GPCRs.

A Humanized CB1R Yeast Biosensor Enables Facile Screening of Cannabinoid Compounds

Yeast expression of human G-protein-coupled receptors (GPCRs) can be used as a biosensor platform for the detection of pharmaceuticals. Cannabinoid receptor type 1 (CB1R) is of particular interest, given the cornucopia of natural and synthetic cannabinoids being explored as therapeutics. We show for the first time that engineering the N-terminus of CB1R allows for efficient signal transduction in yeast, and that engineering the sterol composition of the yeast membrane modulates its performance. Using an engineered cannabinoid biosensor, we demonstrate that large libraries of synthetic cannabinoids and terpenes can be quickly screened to elucidate known and novel structure-activity relationships. The biosensor strains offer a ready platform for evaluating the activity of new synthetic cannabinoids, monitoring drugs of abuse, and developing therapeutic molecules.

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.

Evolution and synthetic biology

Evolutionary observations have often served as an inspiration for biological design. Decoding of the central dogma of life at a molecular level and understanding of the cellular biochemistry have been elegantly used to engineer various synthetic biology applications, including building genetic circuits in vitro and in cells, building synthetic translational systems, and metabolic engineering in cells to biosynthesize and even bioproduce complex high-value molecules. Here, we review three broad areas of synthetic biology that are inspired by evolutionary observations: (i) combinatorial approaches toward cell-based biomolecular evolution, (ii) engineering interdependencies to establish microbial consortia, and (iii) synthetic immunology. In each of the areas, we will highlight the evolutionary premise that was central toward designing these platforms. These are only a subset of the examples where evolution and natural phenomena directly or indirectly serve as a powerful source of inspiration in shaping synthetic biology and biotechnology.

Rational engineering approaches for establishing insect olfaction reporters in yeast

Insect olfaction directly impacts insect behavior and thus is an important consideration in the development of smart farming tools and in integrated pest management strategies. Insect olfactory receptors (ORs) have been traditionally studied using Drosophila empty neuron systems or with expression and functionalization in HEK293 cells or Xenopus laevis oocytes. Recently, the yeast Saccharomyces cerevisiae (S. cerevisiae) has emerged as a promising chassis for the functional expression of heterologous seven transmembrane receptors. S. cerevisiae provides a platform for the cheap and high throughput study of these receptors and potential deorphanization. In this study, we explore the foundations of a scalable yeast-based platform for the functional expression of insect olfactory receptors by employing a genetically encoded calcium sensor for quantitative evaluation of fluorescence and optimized experimental parameters for enhanced functionality. While the co-receptor of insect olfactory receptors remains non-functional in our yeast-based system, we thoroughly evaluated various experimental variables and identified future research directions for establishing an OR platform in S. cerevisiae.

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.

Recent advances in the analytical strategies of microbial biosensor for detection of pollutants

Microbial biosensor which integrates different types of microorganisms, such as bacteria, microalgae, fungi, and virus have become suitable technologies to address limitations of conventional analytical methods. The main applications of biosensors include the detection of environmental pollutants, pathogenic bacteria and compounds related to illness, and food quality. Each type of microorganisms possesses advantages and disadvantages with different mechanisms to detect the analytes of interest. Furthermore, there is an increasing trend in genetic modifications for the development of microbial biosensors due to potential for high-throughput analysis and portability. Many review articles have discussed the applications of microbial biosensor, but many of them focusing only about bacterial-based biosensor although other microbes also possess many advantages. Additionally, reviews on the applications of all microbes as biosensor especially viral and microbial fuel cell biosensors are also still limited. Therefore, this review summarizes all the current applications of bacterial-, microalgal-, fungal-, viral-based biosensor in regard to environmental, food, and medical-related applications. The underlying mechanism of each microbes to detect the analytes are also discussed. Additionally, microbial fuel cell biosensors which have great potential in the future are also discussed. Although many advantageous microbial-based biosensors have been discovered, other areas such as forensic detection, early detection of bacteria or virus species that can lead to pandemics, and others still need further investigation. With that said, microbial-based biosensors have promising potential for vast applications where the biosensing performance of various microorganisms are presented in this review along with future perspectives to resolve problems related on microbial biosensors.

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.

Screening microbially produced Δ9-tetrahydrocannabinol using a yeast biosensor workflow

Microbial production of cannabinoids promises to provide a consistent, cheaper, and more sustainable supply of these important therapeutic molecules. However, scaling production to compete with traditional plant-based sources is challenging. Our ability to make strain variants greatly exceeds our capacity to screen and identify high producers, creating a bottleneck in metabolic engineering efforts. Here, we present a yeast-based biosensor for detecting microbially produced Δ⁹-tetrahydrocannabinol (THC) to increase throughput and lower the cost of screening. We port five human cannabinoid G protein-coupled receptors (GPCRs) into yeast, showing the cannabinoid type 2 receptor, CB2R, can couple to the yeast pheromone response pathway and report on the concentration of a variety of cannabinoids over a wide dynamic and operational range. We demonstrate that our cannabinoid biosensor can detect THC from microbial cell culture and use this as a tool for measuring relative production yields from a library of Δ⁹-tetrahydrocannabinol acid synthase (THCAS) mutants.

Microbial production of cannabinoids promises a cheaper and more sustainable route to these important therapeutic molecules, but strain improvement and screening is challenging. Here, the authors develop a yeast-based Δ9-tetrahydrocannabinol (THC) biosensor for screening microbial mutant libraries.

The Use of Yeast in Biosensing

Yeast has been used as a model for several diseases as it is the simplest unicellular eukaryote, safe and easy to culture and harbors most of the fundamental processes that are present in almost all higher eukaryotes, including humans. From understanding the pathogenesis of disease to drug discovery studies, yeast has served as an important biosensor. It is not only due to the conservation of genetics, amenable modification of its genome and easily accessible analytical methods, but also some characteristic features such as its ability to survive with defective mitochondria, making it a highly flexible microbe for designing whole-cell biosensing systems. The aim of this review is to report on how yeasts have been utilized as biosensors, reporting on responses to various stimuli.

Tools for adapting to a complex habitat: G-protein coupled receptors in Trichoderma

Sensing the environment and interpretation of the received signals are crucial competences of living organisms in order to properly adapt to their habitat, succeed in competition and to reproduce. G-protein coupled receptors (GPCRs) are members of a large family of sensors for extracellular signals and represent the starting point of complex signaling cascades regulating a plethora of intracellular physiological processes and output pathways in fungi. In Trichoderma spp. current research involves a wide range of topics from enzyme production, light response and secondary metabolism to sexual and asexual development as well as biocontrol, all of which require delicate balancing of resources in response to the environmental challenges or biotechnological needs at hand, which are crucially impacted by the surroundings of the fungi and their intercellular signaling cascades triggering a precisely tailored response. In this review we summarize recent findings on sensing by GPCRs in Trichoderma, including the function of pheromone receptors, glucose sensing by CSG1 and CSG2, regulation of secondary metabolism by GPR8 and impacts on mycoparasitism by GPR1. Additionally, we provide an overview on structural determinants, posttranslational modifications and interactions for regulation, activation and signal termination of GPCRs in order to inspire future in depth analyses of their function and to understand previous regulatory outcomes of natural and biotechnological processes modulated or enabled by GPCRs.

Serotonin G Protein-Coupled Receptor-Based Biosensing Modalities in Yeast

Serotonin is a key neurotransmitter involved in numerous physiological processes and serves as an important precursor for manufacturing bioactive indoleamines and alkaloids used in the treatment of human pathologies. In humans, serotonin sensing and signaling can occur by 12 G protein-coupled receptors (GPCRs) coupled to Gα proteins. In yeast, human serotonin GPCRs coupled to Gα proteins have previously been shown to function as whole-cell biosensors of serotonin. However, systematic characterization of serotonin biosensing modalities between variant serotonin GPCRs and application thereof for high-resolution serotonin quantification is still awaiting. To systematically assess GPCR signaling in response to serotonin, we characterized reporter gene expression at two different pHs of a 144-sized library encoding all 12 human serotonin GPCRs in combination with 12 different Gα proteins engineered in yeast. From this screen, we observed changes in the biosensor sensitivities of >4 orders of magnitude. Furthermore, adopting optimal biosensing designs and pH conditions enabled high-resolution high-performance liquid chromatography-validated sensing of serotonin produced in yeast. Lastly, we used the yeast platform to characterize 19 serotonin GPCR polymorphisms found in human populations. While major differences in signaling were observed among the individual polymorphisms when studied in yeast, a cross-comparison of selected variants in mammalian cells showed both similar and disparate results. Taken together, our study highlights serotonin biosensing modalities of relevance to both biotechnological and potential human health applications.

Functional expression of opioid receptors and other human GPCRs in yeast engineered to produce human sterols

The yeast Saccharomyces cerevisiae is powerful for studying human G protein-coupled receptors as they can be coupled to its mating pathway. However, some receptors, including the mu opioid receptor, are non-functional, which may be due to the presence of the fungal sterol ergosterol instead of cholesterol. Here we engineer yeast to produce cholesterol and introduce diverse mu, delta, and kappa opioid receptors to create sensitive opioid biosensors that recapitulate agonist binding profiles and antagonist inhibition. Additionally, human mu opioid receptor variants, including those with clinical relevance, largely display expected phenotypes. By testing mu opioid receptor-based biosensors with systematically adjusted cholesterol biosynthetic intermediates, we relate sterol profiles to biosensor sensitivity. Finally, we apply sterol-modified backgrounds to other human receptors revealing sterol influence in SSTR5, 5-HTR4, FPR1, and NPY1R signaling. This work provides a platform for generating human G protein-coupled receptor-based biosensors, facilitating receptor deorphanization and high-throughput screening of receptors and effectors.

Peptide-Dependent Growth in Yeast via Fine-Tuned Peptide/GPCR-Activated Essential Gene Expression

Building multicellular microbial consortia that communicate with each other and perform programmed functionalities is the next milestone for synthetic biology. Achieving cell-cell communication within these communities requires programming of the transduction of an extracellular signal into a customized intracellular response. G-protein-coupled receptors (GPCRs) are attractive candidates for engineering signal transduction as they can sense extracellular events with high sensitivity and specificity and transduce them into complex intracellular programs. We recently developed a scalable cell-cell communication language based on fungal mating GPCRs and their secreted peptide ligands. This language allows the assembly of engineered yeast strains into multicellular communication networks and allows them to be made interdependent by peptide signaling. In peptide signaling, one cell secretes a peptide that supports the growth of another cell at nanomolar concentrations, a scalable approach for engineering interdependence. Here we address the challenge of correlating the doubling time of Saccharomyces cerevisiae cells with an increasing external peptide concentration by linking GPCR activation to the expression of an essential gene. The required fine-tuning of downstream signaling is achieved via the transcriptional titration of a set of orthogonal GPCR-activated transcription factors, a series of corresponding promoters with different output dynamics, and the use of chemically recoded peptide ligands with varying activation potentials. As such, our work establishes three control points that allow the tuning of the basal and maximal activation of the GPCR response, fold change activation, and response sensitivity. The presented results enable the implementation of peptide-dependent and peptide-tunable growth but could also facilitate the design and calibration of more complex GPCR-controlled synthetic functionality in the future.

Saccharomyces cerevisiae as a Heterologous Host for Natural Products

Cell factories can provide a sustainable supply of natural products with applications as pharmaceuticals, food-additives or biofuels. Besides being an important model organism for eukaryotic systems, Saccharomyces cerevisiae is used as a chassis for the heterologous production of natural products. Its success as a cell factory can be attributed to the vast knowledge accumulated over decades of research, its overall ease of engineering and its robustness. Many methods and toolkits have been developed by the yeast metabolic engineering community with the aim of simplifying and accelerating the engineering process.In this chapter, a range of methodologies are highlighted, which can be used to develop novel natural product cell factories or to improve titer, rate and yields of an existing cell factory with the goal of developing an industrially relevant strain. The addressed topics are applicable for different stages of a cell factory engineering project and include the choice of a natural product platform strain, expression cassette design for heterologous or native genes, basic and advanced genetic engineering strategies, and library screening methods using biosensors. The many engineering methods available and the examples of yeast cell factories underline the importance and future potential of this host for industrial production of natural products.

Established tools and emerging trends for the production of recombinant proteins and metabolites in Pichia pastoris

Besides bakers' yeast, the methylotrophic yeast Komagataella phaffii (also known as Pichia pastoris) has been developed into the most popular yeast cell factory for the production of heterologous proteins. Strong promoters, stable genetic constructs and a growing collection of freely available strains, tools and protocols have boosted this development equally as thorough genetic and cell biological characterization. This review provides an overview of state-of-the-art tools and techniques for working with P. pastoris, as well as guidelines for the production of recombinant proteins with a focus on small-scale production for biochemical studies and protein characterization. The growing applications of P. pastoris for in vivo biotransformation and metabolic pathway engineering for the production of bulk and specialty chemicals are highlighted as well.

Exploring G protein-coupled receptors and yeast surface display strategies for viral detection in baker's yeast: SARS-CoV-2 as a case study

Viral infections pose intense burdens to healthcare systems and global economies. The correct diagnosis of viral diseases represents a crucial step towards effective treatments and control. Biosensors have been successfully implemented as accessible and accurate detection tests for some of the most important viruses. While most biosensors are based on physical or chemical interactions of cell-free components, the complexity of living microorganisms holds a poorly explored potential for viral detection in the face of the advances of synthetic biology. Indeed, cell-based biosensors have been praised for their versatility and economic attractiveness, however, yeast platforms for viral disease diagnostics are still limited to indirect antibody recognition. Here we propose a novel strategy for viral detection in Saccharomyces cerevisiae, which combines the transductive properties of G Protein-Coupled Receptors (GPCRs) with the Yeast Surface Display (YSD) of specific enzymes enrolled in the viral recognition process. The GPCR/YSD complex might allow for active virus detection through a modulated signal activated by a GPCR agonist, whose concentration correlates to the viral titer. Additionally, we explore this methodology in a case study for the detection of highly pathogenic coronaviruses that share the same cell receptor upon infection (i.e. the Angiotensin-Converting Enzyme 2, ACE2), as a conceptual example of the potential of the GPCR/YSD strategy for the diagnosis of COVID-19.

A computational model for GPCR-ligand interaction prediction

G protein-coupled receptors (GPCRs) play an essential role in critical human activities, and they are considered targets for a wide range of drugs. Accordingly, based on these crucial roles, GPCRs are mainly considered and focused on pharmaceutical research. Hence, there are a lot of investigations on GPCRs. Experimental laboratory research is very costly in terms of time and expenses, and accordingly, there is a marked tendency to use computational methods as an alternative method. In this study, a prediction model based on machine learning (ML) approaches was developed to predict GPCRs and ligand interactions. Decision tree (DT), random forest (RF), multilayer perceptron (MLP), support vector machine (SVM), and Naive Bayes (NB) were the algorithms that were investigated in this study. After several optimization steps, receiver operating characteristic (ROC) for DT, RF, MLP, SVM, and NB algorithm were 95.2, 98.1, 96.3, 95.5, and 97.3, respectively. Accordingly final model was made base on the RF algorithm. The current computational study compared with others focused on specific and important types of proteins (GPCR) interaction and employed/examined different types of sequence-based features to obtain more accurate results. Drug science researchers could widely use the developed prediction model in this study. The developed predictor was applied over 16,132 GPCR-ligand pairs and about 6778 potential interactions predicted.

G protein-coupled receptors expressed and studied in yeast. The adenosine receptor as a prime example

G protein-coupled receptors (GPCRs) are the largest class of membrane proteins with around 800 members in the human genome/proteome. Extracellular signals such as hormones and neurotransmitters regulate various biological processes via GPCRs, with GPCRs being the bodily target of 30-40% of current drugs on the market. Complete identification and understanding of GPCR functionality will provide opportunities for novel drug discovery. Yeast expresses three different endogenous GPCRs regulating pheromone and sugar sensing, with the pheromone pathway offering perspectives for the characterization of heterologous GPCR signaling. Moreover, yeast offers a ''null" background for studies on mammalian GPCRs, including GPCR activation and signaling, ligand identification, and characterization of disease-related mutations. This review focuses on modifications of the yeast pheromone signaling pathway for functional GPCR studies, and on opportunities and usage of the yeast system as a platform for human GPCR studies. Finally, this review discusses in some further detail studies of adenosine receptors heterologously expressed in yeast, and what Geoff Burnstock thought of this approach.