Design and engineering of intracellular-metabolite-sensing/regulation gene circuits inSaccharomyces cerevisiae

AMPK Activates Cellulase Secretion in Penicillium funiculosum by Downregulating P-HOG1 MAPK Levels

Cellulase production for hydrolyzing plant cell walls is energy-intensive in filamentous fungi during nutrient scarcity. AMP-activated protein kinase (AMPK), encoded by snf1, is known to be the nutrient and energy sensor in eukaryotes. Previous studies on AMPK identified its role in alternate carbon utilization in pathogenic fungi. However, the precise role of AMPK in cellulase production remains elusive. In the present study, we employed gene-deletion analysis, quantitative proteomics and chemical-genetic approaches to investigate the role of AMPK in cellulase synthesis in Penicillium funiculosum. Gene-deletion analysis revealed that AMPK does not promote transcription and translation but is essential for cellulase secretion in a calcium-dependent manner. Proteomic analysis of the snf1-deleted (Δsnf1) strain confirmed trapped cellulase inside the mycelia and identified HOG1 MAPK activation as the most significant Ca2+-induced signaling event during carbon stress in Δsnf1. Western blot analysis analysis revealed that the phosphorylated HOG1 (P-HOG1)/HOG1 MAPK ratio maintained by Ca2+-signaling/Ca2+-activated AMPK, respectively, forms a secretion checkpoint for cellulases, and disturbing this equilibrium blocks cellulase secretion. The proteomic analysis also indicated a massive increase in mTORC1-activated anabolic pathways during carbon stress in Δsnf1. Our study suggests that AMPK maintains homeostasis by acting as a global repressor during carbon stress.

Versatile xylose and arabinose genetic switches development for yeasts

Inducible transcription systems are essential tools in genetic engineering, where tight control, strong inducibility and fast response with cost-effective inducers are highly desired. However, existing systems in yeasts are rarely used in large-scale fermentations due to either cost-prohibitive inducers or incompatible performance. Here, we developed powerful xylose and arabinose induction systems in Saccharomyces cerevisiae, utilizing eukaryotic activators XlnR and AraRA from Aspergillus species and bacterial repressors XylR and AraRR. By integrating these signals into a highly-structured synthetic promoter, we created dual-mode systems with strong outputs and minimal leakiness. These systems demonstrated over 4000- and 300-fold regulation with strong activation and rapid response. The dual-mode xylose system was fully activated by xylose-rich agricultural residues like corncob hydrolysate, outperforming existing systems in terms of leakiness, inducibility, dynamic range, induction rate, and growth impact on host. We validated their utility in metabolic engineering with high-titer linalool production and demonstrated the transferability of the XlnR-based xylose induction system to Pichia pastoris, Candida glabrata and Candida albicans. This work provides robust genetic switches for yeasts and a general strategy for integrating activation-repression signals into synthetic promoters to achieve optimal performance.

Biosensor-Assisted Engineering for Diverse Microbial Cellular Physiologies

Recent advancements in biosensor technology have revolutionized the field of microbial engineering, enabling efficient and precise optimization of strains for the production of valuable chemicals. This review comprehensively explores the innovative integration of biosensors to enhance microbial cell factories, with a particular emphasis on the crucial role of high-throughput biosensor-assisted screening. Biosensor-assisted approaches have enabled the identification of novel transporters, the elucidation of underlying transport mechanisms, and the fine-tuning of metabolic pathways for enhanced production. Furthermore, this review illustrates the utilization of biosensors for manipulating cellular behaviors, including interactions with environmental factors, and the reduction of nongenetic cell-to-cell variations. This review highlights the indispensable role of biosensors in advancing the field of microbial engineering through the modulation and exploitation of diverse cellular physiological processes.

Self-controlled in silico gene knockdown strategies to enhance the sustainable production of heterologous terpenoid by Saccharomyces cerevisiae

Microbial bioengineering is a growing field for producing plant natural products (PNPs) in recent decades, using heterologous metabolic pathways in host cells. Once heterologous metabolic pathways have been introduced into host cells, traditional metabolic engineering techniques are employed to enhance the productivity and yield of PNP biosynthetic routes, as well as to manage competing pathways. The advent of computational biology has marked the beginning of a novel epoch in strain design through in silico methods. These methods utilize genome-scale metabolic models (GEMs) and flux optimization algorithms to facilitate rational design across the entire cellular metabolic network. However, the implementation of in silico strategies can often result in an uneven distribution of metabolic fluxes due to the rigid knocking out of endogenous genes, which can impede cell growth and ultimately impact the accumulation of target products. In this study, we creatively utilized synthetic biology to refine in silico strain design for efficient PNPs production. OptKnock simulation was performed on the GEM of Saccharomyces cerevisiae OA07, an engineered strain for oleanolic acid (OA) bioproduction that has been reported previously. The simulation predicted that the single deletion of fol1, fol2, fol3, abz1, and abz2, or a combined knockout of hfd1, ald2 and ald3 could improve its OA production. Consequently, strains EK1∼EK7 were constructed and cultivated. EK3 (OA07△fol3), EK5 (OA07△abz1), and EK6 (OA07△abz2) had significantly higher OA titers in a batch cultivation compared to the original strain OA07. However, these increases were less pronounced in the fed-batch mode, indicating that gene deletion did not support sustainable OA production. To address this, we designed a negative feedback circuit regulated by malonyl-CoA, a growth-associated intermediate whose synthesis served as a bypass to OA synthesis, at fol3, abz1, abz2, and at acetyl-CoA carboxylase-encoding gene acc1, to dynamically and autonomously regulate the expression of these genes in OA07. The constructed strains R_3A, R_5A and R_6A had significantly higher OA titers than the initial strain and the responding gene-knockout mutants in either batch or fed-batch culture modes. Among them, strain R_3A stand out with the highest OA titer reported to date. Its OA titer doubled that of the initial strain in the flask-level fed-batch cultivation, and achieved at 1.23 ± 0.04 g L-1 in 96 h in the fermenter-level fed-batch mode. This indicated that the integration of optimization algorithm and synthetic biology approaches was efficiently rational for PNP-producing strain design.

Enhanced single-base mutation diversity by the combination of cytidine deaminase with DNA-repairing enzymes in yeast

The occurrence of random mutations can increase the diversity of the genome and promote the evolutionary process of organisms. High efficiency mutagenesis techniques significantly accelerate the evolutionary process. In this work, we describe a targeted mutagenesis system named MutaT7trans to significantly increase mutation rate and generate mutations across all four nucleotides in yeast. We constructed different DNA-repairing enzyme-PmCDA1-T7 RNA polymerase (T7 RNAP) fusion proteins, achieved targeted mutagenesis by flanking the target gene with T7 promoters, and tuned the mutation spectra by introducing different DNA-repairing enzymes. With this mutagenesis tool, the proportion of non-C → T mutations was 10-11-fold higher than the cytidine deaminase-based evolutionary tools, and the transversion mutation frequency was also elevated. The mutation rate of the target gene was significantly increased to 5.25 × 10-3 substitutions per base (s. p. b.). We also demonstrated that MutaT7trans could be used to evolve the CrtE, CrtI, and CrtYB gene in the β-carotene biosynthesis process and generate different types of mutations.

Genetically Encoded Biosensor Engineering for Application in Directed Evolution

Although rational genetic engineering is nowadays the favored method for microbial strain improvement, building up mutant libraries based on directed evolution for improvement is still in many cases the better option. In this regard, the demand for precise and efficient screening methods for mutants with high performance has stimulated the development of biosensor-based high-throughput screening strategies. Genetically encoded biosensors provide powerful tools to couple the desired phenotype to a detectable signal, such as fluorescence and growth rate. Herein, we review recent advances in engineering several classes of biosensors and their applications in directed evolution. Furthermore, we compare and discuss the screening advantages and limitations of two-component biosensors, transcription-factor-based biosensors, and RNA-based biosensors. Engineering these biosensors has focused mainly on modifying the expression level or structure of the biosensor components to optimize the dynamic range, specificity, and detection range. Finally, the applications of biosensors in the evolution of proteins, metabolic pathways, and genome-scale metabolic networks are described. This review provides potential guidance in the design of biosensors and their applications in improving the bioproduction of microbial cell factories through directed evolution.

Determinants of sugar-induced influx in the mammalian fructose transporter GLUT5

In mammals, glucose transporters (GLUT) control organism-wide blood-glucose homeostasis. In human, this is accomplished by 14 different GLUT isoforms, that transport glucose and other monosaccharides with varying substrate preferences and kinetics. Nevertheless, there is little difference between the sugar-coordinating residues in the GLUT proteins and even the malarial Plasmodium falciparum transporter PfHT1, which is uniquely able to transport a wide range of different sugars. PfHT1 was captured in an intermediate 'occluded' state, revealing how the extracellular gating helix TM7b has moved to break and occlude the sugar-binding site. Sequence difference and kinetics indicated that the TM7b gating helix dynamics and interactions likely evolved to enable substrate promiscuity in PfHT1, rather than the sugar-binding site itself. It was unclear, however, if the TM7b structural transitions observed in PfHT1 would be similar in the other GLUT proteins. Here, using enhanced sampling molecular dynamics simulations, we show that the fructose transporter GLUT5 spontaneously transitions through an occluded state that closely resembles PfHT1. The coordination of D-fructose lowers the energetic barriers between the outward- and inward-facing states, and the observed binding mode for D-fructose is consistent with biochemical analysis. Rather than a substrate-binding site that achieves strict specificity by having a high affinity for the substrate, we conclude GLUT proteins have allosterically coupled sugar binding with an extracellular gate that forms the high-affinity transition-state instead. This substrate-coupling pathway presumably enables the catalysis of fast sugar flux at physiological relevant blood-glucose concentrations.

High throughput mutagenesis and screening for yeast engineering

The eukaryotic yeast Saccharomyces cerevisiae is a model host utilized for whole cell biocatalytic conversions, protein evolution, and scientific inquiries into the pathogenesis of human disease. Over the past decade, the scale and pace of such studies has drastically increased alongside the advent of novel tools for both genome-wide studies and targeted genetic mutagenesis. In this review, we will detail past and present (e.g., CRISPR/Cas) genome-scale screening platforms, typically employed in the context of growth-based selections for improved whole cell phenotype or for mechanistic interrogations. We will further highlight recent advances that enable the rapid and often continuous evolution of biomolecules with improved function. Additionally, we will detail the corresponding advances in high throughput selection and screening strategies that are essential for assessing or isolating cellular and protein improvements. Finally, we will describe how future developments can continue to advance yeast high throughput engineering.

Engineering a two-gene system to operate as a highly sensitive biosensor or a sharp switch upon induction with β-estradiol

The human estrogen receptor has been used for about thirty years, in the yeast S. cerevisiae, as a component of chimeric transcription factors. Its ligand, β-estradiol, permits to control the protein translocation into the nucleus and, as a consequence, the expression of the gene(s) targeted by the synthetic transcription factor. Activators that are orthogonal to the yeast genome have been realized by fusing the human estrogen receptor to an activation and a DNA-binding domain from bacteria, viruses, or higher eukaryotes. In this work, we optimized the working of a β-estradiol-sensing device-in terms of detection range and maximal output signal-where the human estrogen receptor is flanked by the bacterial protein LexA and either the strong VP64 (from herpes simplex virus) or the weaker B42 (from E. coli) activation domain. We enhanced the biosensor performance by thoroughly engineering both the chimeric activator and the reporter protein expression cassette. In particular, we constructed a synthetic promoter-where transcription is induced by the chimeric activators-based on the core sequence of the yeast CYC1 promoter, by tuning parameters such as the length of the 5' UTR, the distance between adjacent LexA binding sites (operators), and the spacing between the whole operator region and the main promoter TATA box. We found a configuration that works both as a highly sensitive biosensor and a sharp switch depending on the concentration of the chimeric activator and the strength of its activation domain.

Prebiotics-Controlled Disposable Engineered Bacteria for Intestinal Diseases

As a new method of diagnosis and treatment for intestinal diseases, intelligent engineered bacteria based on synthetic biology have been developed vigorously in recent years. However, how to deal with the engineered bacteria in vivo after completing the tasks is an urgent problem to be resolved. In this study, we constructed a thiosulfate (a biomarker of inflammatory bowel disease)-responsive engineered bacteria to generate two signals, sfGFP (monitoring) and gain-of-function (translation activation) mutation (ACG to ATG), in the initiation codon of lysisE (recording) via the CRISPR/Cas9-mediated base editing system. Once these two signals were detected, xylose could be added to induce lysis E expression, resulting in the destruction of the edited bacteria and the release of AvCystain simultaneously. Overall, our innovative engineered bacteria can record instant and historical information of the disease, and especially, the edited bacteria can be artificially attenuated and release drug in situ when needed, ultimately serving as a disposable and recyclable candidate for more types of diseases.

A Gene Circuit Combining the Endogenous I-E Type CRISPR-Cas System and a Light Sensor to Produce Poly-β-Hydroxybutyric Acid Efficiently

‘Metabolic burden,’ which arises when introducing exogenic synthesizing pathways into a host strain, remains a challenging issue in metabolic engineering. Redirecting metabolic flux from cell growth to product synthesis at an appropriate culture timepoint is ideal for resolving this issue. In this report, we introduce optogenetics—which is capable of precise temporal and spatial control—as a genetic switch, accompanied by the endogenous type I-E CRISPRi system in Escherichia coli (E. coli) to generate a metabolic platform that redirects metabolic flux. Poly-β-hydroxybutyric acid (PHB) production was taken as an example to demonstrate the performance of this platform. A two-to-three-fold increase in PHB content was observed under green light when compared with the production of PHB under red light, confirming the regulatory activity of this platform and its potential to redirect metabolic flux to synthesize target products.

Intracellular biosensor-based dynamic regulation to manipulate gene expression at the spatiotemporal level

The use of intracellular, biosensor-based dynamic regulation strategies to regulate and improve the production of useful compounds have progressed significantly over previous decades. By employing such an approach, it is possible to simultaneously realize high productivity and optimum growth states. However, industrial fermentation conditions contain a mixture of high- and low-performance non-genetic variants, as well as young and aged cells at all growth phases. Such significant individual variations would hinder the precise controlling of metabolic flux at the single-cell level to achieve high productivity at the macroscopic population level. Intracellular biosensors, as the regulatory centers of metabolic networks, can real-time sense intra- and extracellular conditions and, thus, could be synthetically adapted to balance the biomass formation and overproduction of compounds by individual cells. Herein, we highlight advances in the designing and engineering approaches to intracellular biosensors. Then, the spatiotemporal properties of biosensors associated with the distribution of inducers are compared. Also discussed is the use of such biosensors to dynamically control the cellular metabolic flux. Such biosensors could achieve single-cell regulation or collective regulation goals, depending on whether or not the inducer distribution is only intracellular.

Engineering of Synthetic Transcriptional Switches in Yeast

Transcriptional switches can be utilized for many purposes in synthetic biology, including the assembly of complex genetic circuits to achieve sophisticated cellular systems and the construction of biosensors for real-time monitoring of intracellular metabolite concentrations. Although to date such switches have mainly been developed in prokaryotes, those for eukaryotes are increasingly being reported as both rational and random engineering technologies mature. In this review, we describe yeast transcriptional switches with different modes of action and how to alter their properties. We also discuss directed evolution technologies for the rapid and robust construction of yeast transcriptional switches.

Force in numbers: high-throughput screening approaches to unlock microbial transport

Biological membranes are inherently complex, making transport processes in microbial cell factories a significant bottleneck. Lack of knowledge on transport proteins' characteristics and the need for advanced technical equipment often hamper transporter identification and optimization. For these reasons, moving away from individual characterization and towards high-throughput mining, engineering, and screening of transporters is an increasingly attractive approach. Superior transporters can be selected from large libraries by coupling their activity to growth, for substrates that function as feedstocks or toxic compounds. Other compounds can be screened thanks to recent advances in the design and deployment of synthetic genetic circuits (biosensors). Furthermore, novel strategies are rapidly increasing the repertoire of biomolecule transporters susceptible to high-throughput selection methods.

D-Xylose Sensing in Saccharomyces cerevisiae: Insights from D-Glucose Signaling and Native D-Xylose Utilizers

Extension of the substrate range is among one of the metabolic engineering goals for microorganisms used in biotechnological processes because it enables the use of a wide range of raw materials as substrates. One of the most prominent examples is the engineering of baker's yeast Saccharomyces cerevisiae for the utilization of d-xylose, a five-carbon sugar found in high abundance in lignocellulosic biomass and a key substrate to achieve good process economy in chemical production from renewable and non-edible plant feedstocks. Despite many excellent engineering strategies that have allowed recombinant S. cerevisiae to ferment d-xylose to ethanol at high yields, the consumption rate of d-xylose is still significantly lower than that of its preferred sugar d-glucose. In mixed d-glucose/d-xylose cultivations, d-xylose is only utilized after d-glucose depletion, which leads to prolonged process times and added costs. Due to this limitation, the response on d-xylose in the native sugar signaling pathways has emerged as a promising next-level engineering target. Here we review the current status of the knowledge of the response of S. cerevisiae signaling pathways to d-xylose. To do this, we first summarize the response of the native sensing and signaling pathways in S. cerevisiae to d-glucose (the preferred sugar of the yeast). Using the d-glucose case as a point of reference, we then proceed to discuss the known signaling response to d-xylose in S. cerevisiae and current attempts of improving the response by signaling engineering using native targets and synthetic (non-native) regulatory circuits.

Saccharomyces cerevisiae Promoter Engineering before and during the Synthetic Biology Era

Simple Summary

Promoters are DNA sequences where the process of transcription starts. They can work constitutively or be controlled by environmental signals of different types. The quantity of proteins and RNA present in yeast genetic circuits highly depends on promoter strength. Hence, they have been deeply studied and modified over, at least, the last forty years, especially since the year 2000 when Synthetic Biology was born. Here, we present how promoter engineering changed over these four decades and discuss its possible future directions due to novel computational methods and technology.

Abstract

Synthetic gene circuits are made of DNA sequences, referred to as transcription units, that communicate by exchanging proteins or RNA molecules. Proteins are, mostly, transcription factors that bind promoter sequences to modulate the expression of other molecules. Promoters are, therefore, key components in genetic circuits. In this review, we focus our attention on the construction of artificial promoters for the yeast S. cerevisiae, a popular chassis for gene circuits. We describe the initial techniques and achievements in promoter engineering that predated the start of the Synthetic Biology epoch of about 20 years. We present the main applications of synthetic promoters built via different methods and discuss the latest innovations in the wet-lab engineering of novel promoter sequences.

Structures and General Transport Mechanisms by the Major Facilitator Superfamily (MFS)

The major facilitator superfamily (MFS) is the largest known superfamily of secondary active transporters. MFS transporters are responsible for transporting a broad spectrum of substrates, either down their concentration gradient or uphill using the energy stored in the electrochemical gradients. Over the last 10 years, more than a hundred different MFS transporter structures covering close to 40 members have provided an atomic framework for piecing together the molecular basis of their transport cycles. Here, we summarize the remarkable promiscuity of MFS members in terms of substrate recognition and proton coupling as well as the intricate gating mechanisms undergone in achieving substrate translocation. We outline studies that show how residues far from the substrate binding site can be just as important for fine-tuning substrate recognition and specificity as those residues directly coordinating the substrate, and how a number of MFS transporters have evolved to form unique complexes with chaperone and signaling functions. Through a deeper mechanistic description of glucose (GLUT) transporters and multidrug resistance (MDR) antiporters, we outline novel refinements to the rocker-switch alternating-access model, such as a latch mechanism for proton-coupled monosaccharide transport. We emphasize that a full understanding of transport requires an elucidation of MFS transporter dynamics, energy landscapes, and the determination of how rate transitions are modulated by lipids.

Advanced strategies and tools to facilitate and streamline microbial adaptive laboratory evolution

Adaptive laboratory evolution (ALE) has served as a historic microbial engineering method that mimics natural selection to obtain desired microbes. The past decade has witnessed improvements in all aspects of ALE workflow, in terms of growth coupling, genotypic diversification, phenotypic selection, and genotype-phenotype mapping. The developing growth-coupling strategies facilitate ALE to a wider range of appealing traits. In vivo mutagenesis methods and multiplexed automated culture platforms open new gates to streamline its execution. Meanwhile, the application of multi-omics analyses and multiplexed genetic engineering promote efficient knowledge mining. This article provides a comprehensive and updated review of these advances, highlights newest significant applications, and discusses future improvements, aiming to provide a practical guide for implementation of novel, effective, and efficient ALE experiments.

Efflux Transporters' Engineering and Their Application in Microbial Production of Heterologous Metabolites

Metabolic engineering of microbial hosts for the production of heterologous metabolites and biochemicals is an enabling technology to generate meaningful quantities of desired products that may be otherwise difficult to produce by traditional means. Heterologous metabolite production can be restricted by the accumulation of toxic products within the cell. Efflux transport proteins (transporters) provide a potential solution to facilitate the export of these products, mitigate toxic effects, and enhance production. Recent investigations using knockout lines, heterologous expression, and expression profiling of transporters have revealed candidates that can enhance the export of heterologous metabolites from microbial cell systems. Transporter engineering efforts have revealed that some exhibit flexible substrate specificity and may have broader application potentials. In this Review, the major superfamilies of efflux transporters, their mechanistic modes of action, selection of appropriate efflux transporters for desired compounds, and potential transporter engineering strategies are described for potential applications in enhancing engineered microbial metabolite production. Future studies in substrate recognition, heterologous expression, and combinatorial engineering of efflux transporters will assist efforts to enhance heterologous metabolite production in microbial hosts.

Design, Evolution, and Characterization of a Xylose Biosensor in Escherichia coli Using the XylR/xylO System with an Expanded Operating Range

Genetically encoded biosensors are extensively utilized in synthetic biology and metabolic engineering. However, reported xylose biosensors are far too sensitive with a limited operating range to be useful for most sensing applications. In this study, we describe directed evolution of Escherichia coli XylR, and construction of biosensors based on XylR and the corresponding operator xylO. The operating range of biosensors containing the mutant XylR was increased by nearly 10-fold comparing with the control. Two individual amino acid mutations (either L73P or N220T) in XylR were sufficient to extend the linear response range to upward of 10 g/L xylose. The evolved biosensors described here are well suited for developing whole-cell biosensors for detecting varying xylose concentrations across an expanded range. As an alternative use of this system, we also demonstrate the utility of XylR and xylO as a xylose inducible system to enable graded gene expression through testing with β-galactosidase gene and the lycopene synthetic pathway. This evolution strategy identified a less-sensitive biosensor for real applications, thus providing new insights into strategies for expanding operating ranges of other biosensors for synthetic biology applications.

Engineering transcription factor-based biosensors for repressive regulation through transcriptional deactivation design in Saccharomyces cerevisiae

Background

With the development of engineering the microbial cell factories, biosensors have been used widely for regulation of cellular metabolism and high-throughput screening. However, most of the biosensors constructed in Saccharomyces cerevisiae are designed for transcriptional activation. Very few studies have dedicated to the development of genetic circuit for repressive regulation, which is also indispensable for the dynamic control of metabolism.

Results

In this study, through transcriptional deactivation design, we developed transcription-factor-based biosensors to allow repressive regulation in response to ligand. Using a malonyl-CoA sensing system as an example, the biosensor was constructed and systematically engineered to optimize the dynamic range by comparing transcriptional activity of the activators, evaluating the positions and numbers of the operators in the promoter and comparing the effects of different promoters. A biosensor with 82% repression ratio was obtained. Based on this design principle, another two biosensors, which sense acyl-CoA or xylose and downregulate gene expression, were also successfully constructed.

Conclusions

Our work systematically optimized the biosensors for repressive regulation in yeast for the first time. It provided useful framework to construct similar biosensors. Combining the widely reported biosensors for transcriptional activation with the biosensors developed here, it is now possible to construct biosensors with opposing transcriptional activities in yeast.

Biosensors design in yeast and applications in metabolic engineering

Engineering microbial cell factories is a potential approach of sustainable production of chemicals, fuels and pharmaceuticals. However, testing the production of molecules in high throughput is still a time-consuming and laborious process since product synthesis usually does not confer a clear phenotype. Therefore, it is necessary to develop new techniques for fast high-producer screening. Genetically encoded biosensors are considered to be promising devices for high-throughput analysis owing to their ability to sense metabolites and couple detection to an actuator, thereby facilitating the rapid detection of small molecules at single-cell level. Here, we review recent advances in the design and engineering of biosensors in Saccharomyces cerevisiae, and their applications in metabolic engineering. Three types of biosensor are introduced in this review: transcription factor based, RNA-based and enzyme-coupled biosensors. The studies to improve the features of biosensors are also described. Moreover, we summarized their metabolic engineering applications in dynamic regulation and high producer selection. Current challenges in biosensor design and future perspectives on sensor applications are also discussed.

Engineering Prokaryotic Transcriptional Activator XylR as a Xylose-Inducible Biosensor for Transcription Activation in Yeast

Biosensors regulated by specific substrates are needed to develop genetic tools to meet the needs of engineering microbial cell factories. Here, a xylose-inducible biosensor (xylbiosensor), comprising the Escherichia coli activation factor XylR, fusion activation domain (AD) VPRH, and a hybrid promoter with operator xylO, was established in Yarrowia lipolytica. The addition of xylose to an engineered Y. lipolytica strain harboring the xylbiosensor could trigger significant transcriptional activation of target genes, such as mcherry and the xylose utilization gene. Furthermore, a novel promoter Pleu-Pxo-Ptef was developed to construct a bidirectional expression system. The xylbiosensor showed good portability in Saccharomyces cerevisiae, suggesting its potential value in other eukaryotic cells. This study is the first to construct a "turn-on" xylbiosensor induced by xylose addition based on a prokaryotic activator XylR and eukaryotic universal AD. The xylbiosensor exhibits potential in pathway engineering for xylose utilization and xylose-derived product biosynthesis in yeast.

A New Biosensor for Stilbenes and a Cannabinoid Enabled by Genome Mining of a Transcriptional Regulator

In vivo biosensors are powerful tools for metabolic engineering and synthetic biology applications. However, the development of biosensors is hindered by the limited number of characterized transcriptional regulators. The versatile sensing abilities of microbes and genome sequences available hold great potential for developing novel biosensors via genome mining for new transcriptional regulators. Here we report the development and engineering of a new stilbene-responsive biosensor discovered by mining the Novosphingobium aromaticivorans DSM 12444 genome. The biosensor can distinguish resveratrol from its precursors, p-coumaric acid and trans-cinnamic acid. Remarkably, it can detect other biologically active stilbenes with resorcinol groups, and cannabidiolic acid with a β-resorcylic acid functional group. When coupled to resveratrol biosynthesis enzymes, the biosensor can sense altered resveratrol production in cells, demonstrating a 667-fold enrichment in one round of fluorescence-activated cell sorting. Our biosensor will be potentially applicable to metabolic engineering of microbial cell factories for production of stilbenes and cannabinoids.

Evolution-guided engineering of small-molecule biosensors

Allosteric transcription factors (aTFs) have proven widely applicable for biotechnology and synthetic biology as ligand-specific biosensors enabling real-time monitoring, selection and regulation of cellular metabolism. However, both the biosensor specificity and the correlation between ligand concentration and biosensor output signal, also known as the transfer function, often needs to be optimized before meeting application needs. Here, we present a versatile and high-throughput method to evolve prokaryotic aTF specificity and transfer functions in a eukaryote chassis, namely baker's yeast Saccharomyces cerevisiae. From a single round of mutagenesis of the effector-binding domain (EBD) coupled with various toggled selection regimes, we robustly select aTF variants of the cis,cis-muconic acid-inducible transcription factor BenM evolved for change in ligand specificity, increased dynamic output range, shifts in operational range, and a complete inversion-of-function from activation to repression. Importantly, by targeting only the EBD, the evolved biosensors display DNA-binding affinities similar to BenM, and are functional when ported back into a prokaryotic chassis. The developed platform technology thus leverages aTF evolvability for the development of new host-agnostic biosensors with user-defined small-molecule specificities and transfer functions.

High-Resolution Scanning of Optimal Biosensor Reporter Promoters in Yeast

Small-molecule binding allosteric transcription factors (aTFs) derived from bacteria enable real-time monitoring of metabolite abundances, high-throughput screening of genetic designs, and dynamic control of metabolism. Yet, engineering of reporter promoter designs of prokaryotic aTF biosensors in eukaryotic cells is complex. Here we investigate the impact of aTF binding site positions at single-nucleotide resolution in >300 reporter promoter designs in Saccharomyces cerevisiae. From this we identify biosensor output landscapes with transient and distinct aTF binding site position effects for aTF repressors and activators, respectively. Next, we present positions for tunable reporter promoter outputs enabling metabolite-responsive designs for a total of four repressor-type and three activator-type aTF biosensors with dynamic output ranges up to 8- and 26-fold, respectively. This study highlights aTF binding site positions in reporter promoters as key for successful biosensor engineering and that repressor-type aTF biosensors allows for more flexibility in terms of choice of binding site positioning compared to activator-type aTF biosensors.

Recent advances in high-throughput mass spectrometry that accelerates enzyme engineering for biofuel research

Enzymes play indispensable roles in producing biofuels, a sustainable and renewable source of transportation fuels. Lacking rational design rules, the development of industrially relevant enzyme catalysts relies heavily on high-throughput screening. However, few universal methods exist to rapidly characterize large-scale enzyme libraries. Therefore, assay development is necessary on an ad hoc basis to link enzyme properties to spectrophotometric signals and often requires the use of surrogate, optically active substrates. On the other hand, mass spectrometry (MS) performs label-free enzyme assays that utilize native substrates and is therefore generally applicable. But the analytical speed of MS is considered rate limiting, mainly due to the use of time-consuming chromatographic separation in traditional MS analysis. Thanks to new instrumentation and sample preparation methods, direct analyte introduction into a mass spectrometer without a prior chromatographic step can be achieved by laser, microfluidics, and acoustics, so that each sample can be analyzed within seconds. Here we review recent advances in MS platforms that improve the throughput of enzyme library screening and discuss how these advances can potentially facilitate biofuel research by providing high sensitivity, selectivity and quantitation that are difficult to obtain using traditional assays. We also highlight the limitations of current MS assays in studying biofuel-related enzymes and propose possible solutions.

Multi-functional genome-wide CRISPR system for high throughput genotype-phenotype mapping

Genome-scale engineering is an indispensable tool to understand genome functions due to our limited knowledge of cellular networks. Unfortunately, most existing methods for genome-wide genotype–phenotype mapping are limited to a single mode of genomic alteration, i.e. overexpression, repression, or deletion. Here we report a multi-functional genome-wide CRISPR (MAGIC) system to precisely control the expression level of defined genes to desired levels throughout the whole genome. By combining the tri-functional CRISPR system and array-synthesized oligo pools, MAGIC is used to create, to the best of our knowledge, one of the most comprehensive and diversified genomic libraries in yeast ever reported. The power of MAGIC is demonstrated by the identification of previously uncharacterized genetic determinants of complex phenotypes, particularly those having synergistic interactions when perturbed to different expression levels. MAGIC represents a powerful synthetic biology tool to investigate fundamental biological questions as well as engineer complex phenotypes for biotechnological applications.

Genome-scale engineering is generally limited to single methods of alteration such as overexpression, repression or deletion. Here the authors present a tri-functional CRISPR system that can engineer complex synergistic interactions in a genome-wide manner.

Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor

Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional output of metabolic activity, on the single-cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics, and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells. Therefore, drawing on the robust cell-intrinsic correlation between glycolytic flux and levels of fructose-1,6-bisphosphate (FBP), we transplanted the B. subtilis FBP-binding transcription factor CggR into yeast. With the developed biosensor, we robustly identified cell subpopulations with different FBP levels in mixed cultures, when subjected to flow cytometry and microscopy. Employing microfluidics, we were also able to assess the temporal FBP/glycolytic flux dynamics during the cell cycle. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.

Expanding the Dynamic Range of a Transcription Factor-Based Biosensor in Saccharomyces cerevisiae

Metabolite biosensors are useful tools for high-throughput screening approaches and pathway regulation approaches. An important feature of biosensors is the dynamic range. To expand the maximum dynamic range of a transcription factor-based biosensor in Saccharomyces cerevisiae, using the fapO/FapR system from Bacillus subtilis as an example case, five native promoters, including constitutive and glucose-regulated ones, were modified. By evaluating different binding site (BS) positions in the core promoters, we identified locations that resulted in a high maximum dynamic range with low expression under repressed conditions. We further identified BS positions in the upstream element region of the TEF1 promoter that did not influence the native promoter strength but resulted in repression in the presence of a chimeric repressor consisting of FapR and the yeast repressor Mig1. These modified promoters with broad dynamic ranges will provide useful information for the engineering of future biosensors and their use in complex genetic circuits.

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

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

Synthetic Biology of Yeast

With the rapid development of DNA synthesis and next-generation sequencing, synthetic biology that aims to standardize, modularize, and innovate cellular functions, has achieved vast progress. Here we review key advances in synthetic biology of the yeast Saccharomyces cerevisiae, which serves as an important eukaryal model organism and widely applied cell factory. This covers the development of new building blocks, i.e., promoters, terminators and enzymes, pathway engineering, tools developments, and gene circuits utilization. We will also summarize impacts of synthetic biology on both basic and applied biology, and end with further directions for advancing synthetic biology in yeast.

Pentose Metabolism in Saccharomyces cerevisiae: The Need to Engineer Global Regulatory Systems

Extending the host substrate range of industrially relevant microbes, such as Saccharomyces cerevisiae, has been a highly-active area of research since the conception of metabolic engineering. Yet, rational strategies that enable non-native substrate utilization in this yeast without the need for combinatorial and/or evolutionary techniques are underdeveloped. Herein, this review focuses on pentose metabolism in S. cerevisiae as a case study to highlight the challenges in this field. In the last three decades, work has focused on expressing exogenous pentose metabolizing enzymes as well as endogenous enzymes for effective pentose assimilation, growth, and biofuel production. The engineering strategies that are employed for pentose assimilation in this yeast are reviewed, and compared with metabolism and regulation of native sugar, galactose. In the case of galactose metabolism, multiple signals regulate and aid growth in the presence of the sugar. However, for pentoses that are non-native, it is unclear if similar growth and regulatory signals are activated. Such a comparative analysis aids in identifying missing links in xylose and arabinose utilization. While research on pentose metabolism have mostly concentrated on pathway level optimization, recent transcriptomics analyses highlight the need to consider more global regulatory, structural, and signaling components.

Blueprints for Biosensors: Design, Limitations, and Applications

Biosensors are enabling major advances in the field of analytics that are both facilitating and being facilitated by advances in synthetic biology. The ability of biosensors to rapidly and specifically detect a wide range of molecules makes them highly relevant to a range of industrial, medical, ecological, and scientific applications. Approaches to biosensor design are as diverse as their applications, with major biosensor classes including nucleic acids, proteins, and transcription factors. Each of these biosensor types has advantages and limitations based on the intended application, and the parameters that are required for optimal performance. Specifically, the choice of biosensor design must consider factors such as the ligand specificity, sensitivity, dynamic range, functional range, mode of output, time of activation, ease of use, and ease of engineering. This review discusses the rationale for designing the major classes of biosensor in the context of their limitations and assesses their suitability to different areas of biotechnological application.

In vivo biosensors: mechanisms, development, and applications

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

Lighting up yeast cell factories by transcription factor-based biosensors

Our ability to rewire cellular metabolism for the sustainable production of chemicals, fuels and therapeutics based on microbial cell factories has advanced rapidly during the last two decades. Especially the speed and precision by which microbial genomes can be engineered now allow for more advanced designs to be implemented and tested. However, compared to the methods developed for engineering cell factories, the methods developed for testing the performance of newly engineered cell factories in high throughput are lagging far behind, which consequently impacts the overall biomanufacturing process. For this purpose, there is a need to develop new techniques for screening and selection of best-performing cell factory designs in multiplex. Here we review the current status of the sourcing, design and engineering of biosensors derived from allosterically regulated transcription factors applied to the biotechnology work-horse budding yeast Saccharomyces cerevisiae. We conclude by providing a perspective on the most important challenges and opportunities lying ahead in order to harness the full potential of biosensor development for increasing both the throughput of cell factory development and robustness of overall bioprocesses.

An Orthogonal and pH-Tunable Sensor-Selector for Muconic Acid Biosynthesis in Yeast

Microbes offer enormous potential for production of industrially relevant chemicals and therapeutics, yet the rapid identification of high-producing microbes from large genetic libraries is a major bottleneck in modern cell factory development. Here, we develop and apply a synthetic selection system in Saccharomyces cerevisiae that couples the concentration of muconic acid, a plastic precursor, to cell fitness by using the prokaryotic transcriptional regulator BenM driving an antibiotic resistance gene. We show that the sensor-selector does not affect production nor fitness, and find that tuning pH of the cultivation medium limits the rise of nonproducing cheaters. We apply the sensor-selector to selectively enrich for best-producing variants out of a large library of muconic acid production strains, and identify an isolate that produces more than 2 g/L muconic acid in a bioreactor. We expect that this sensor-selector can aid the development of other synthetic selection systems based on allosteric transcription factors.

A semi-synthetic regulon enables rapid growth of yeast on xylose

Nutrient assimilation is the first step that allows biological systems to proliferate and produce value-added products. Yet, implementation of heterologous catabolic pathways has so far relied on constitutive gene expression without consideration for global regulatory systems that may enhance nutrient assimilation and cell growth. In contrast, natural systems prefer nutrient-responsive gene regulation (called regulons) that control multiple cellular functions necessary for cell survival and growth. Here, in Saccharomyces cerevisiae, by partially- and fully uncoupling galactose (GAL)-responsive regulation and metabolism, we demonstrate the significant growth benefits conferred by the GAL regulon. Next, by adapting the various aspects of the GAL regulon for a non-native nutrient, xylose, we build a semi-synthetic regulon that exhibits higher growth rate, better nutrient consumption, and improved growth fitness compared to the traditional and ubiquitous constitutive expression strategy. This work provides an elegant paradigm to integrate non-native nutrient catabolism with native, global cellular responses to support fast growth.

Efficient assimilation of nutrients is essential for the production of value-added products in microbial fermentation. Here the authors design a semi-synthetic xylose regulon to improve growth characteristics of Saccharomyces cerevisiae on this non-native sugar.

Genomic and phenotypic characterization of a refactored xylose-utilizing Saccharomyces cerevisiae strain for lignocellulosic biofuel production

BACKGROUND

Engineered strains of Saccharomyces cerevisiae have significantly improved the prospects of biorefinery by improving the bioconversion yields in lignocellulosic bioethanol production and expanding the product profiles to include advanced biofuels and chemicals. However, the lignocellulosic biorefinery concept has not been fully applied using engineered strains in which either xylose utilization or advanced biofuel/chemical production pathways have been upgraded separately. Specifically, high-performance xylose-fermenting strains have rarely been employed as advanced biofuel and chemical production platforms and require further engineering to expand their product profiles.

RESULTS

In this study, we refactored a high-performance xylose-fermenting S. cerevisiae that could potentially serve as a platform strain for advanced biofuels and biochemical production. Through combinatorial CRISPR-Cas9-mediated rational and evolutionary engineering, we obtained a newly refactored isomerase-based xylose-fermenting strain, XUSE, that demonstrated efficient conversion of xylose into ethanol with a high yield of 0.43 g/g. In addition, XUSE exhibited the simultaneous fermentation of glucose and xylose with negligible glucose inhibition, indicating the potential of this isomerase-based xylose-utilizing strain for lignocellulosic biorefinery. The genomic and transcriptomic analysis of XUSE revealed beneficial mutations and changes in gene expression that are responsible for the enhanced xylose fermentation performance of XUSE.

CONCLUSIONS

In this study, we developed a high-performance xylose-fermenting S. cerevisiae strain, XUSE, with high ethanol yield and negligible glucose inhibition. Understanding the genomic and transcriptomic characteristics of XUSE revealed isomerase-based engineering strategies for improved xylose fermentation in S. cerevisiae. With high xylose fermentation performance and room for further engineering, XUSE could serve as a promising platform strain for lignocellulosic biorefinery.

Discovery and engineering of a 1-butanol biosensor in Saccharomyces cerevisiae

The present study aimed to develop a universal methodology for the discovery of biosensors sensitive to particular stresses or metabolites by using a transcriptome analysis, in order to address the need for in vivo biosensors to drive the engineering of microbial cell factories. The method was successfully applied to the discovery of 1-butanol sensors. In particular, the genome-wide transcriptome profiling of S. cerevisiae exposed to three similar short-chain alcohols, 1-butanol, 1-propanol, and ethanol, identified genes that were differentially expressed only under the treatment of 1-butanol. From these candidates, two promoters that responded specifically to 1-butanol were characterized in a dose-dependent manner and were used to distinguish differences in production levels among different 1-butanol producer strains. This strategy opens up new opportunities for the discovery of promoter-based biosensors and can potentially be used to identify biosensors for any metabolite that causes cellular transcriptomic changes.

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

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

Multigene Pathway Engineering with Regulatory Linkers (M-PERL)

Multigene pathway engineering usually needs amounts of part libraries on transcriptional and translational regulation as well as mutant enzymes to achieve the optimal part combinations of the target pathways. We report a new strategy for multigene pathway engineering with regulatory linkers (M-PERL) focusing on tuning the transcriptional start site (TSS) of yeast promoters. The regulatory linkers are composed of two homologous ends of two adjacent gene parts for assembly and a central regulatory region between them. We investigated the effect of the homologous end's length on multigene assembly, analyzed the influences of truncated, replaced, and elongated TSS and the adjacent region on promoters, and introduced 5 to 40 random bases of N (A/T/C/G) in the central regulatory region of the linkers which effectively varied the promoter's strengths. The distinct libraries of five regulatory linkers were used simultaneously to assemble and tune all five genes in the violacein synthesis pathway. The gene expressions affected the product profiles significantly, and the recombinants for enhanced single component synthesis and varied composition synthesis were obtained. This study offers an efficient tool to assemble and regulate multigene pathways.