A Toolkit for Precise, Multigene Control in Saccharomyces cerevisiae

Cyanamide-inducible expression of homing nuclease I- SceI for selectable marker removal and promoter characterisation in Saccharomyces cerevisiae

In synthetic biology, microbial chassis including yeast Saccharomyces cerevisiae are iteratively engineered with increasing complexity and scale. Wet-lab genetic engineering tools are developed and optimised to facilitate strain construction but are often incompatible with each other due to shared regulatory elements, such as the galactose-inducible (GAL) promoter in S. cerevisiae. Here, we prototyped the cyanamide-induced I- SceI expression, which triggered double-strand DNA breaks (DSBs) for selectable marker removal. We further combined cyanamide-induced I- SceI-mediated DSB and maltose-induced MazF-mediated negative selection for plasmid-free in situ promoter substitution, which simplified the molecular cloning procedure for promoter characterisation. We then characterised three tetracycline-inducible promoters showing differential strength, a non-leaky β-estradiol-inducible promoter, cyanamide-inducible DDI2 promoter, bidirectional MAL32/MAL31 promoters, and five pairs of bidirectional GAL1/GAL10 promoters. Overall, alternative regulatory controls for genome engineering tools can be developed to facilitate genomic engineering for synthetic biology and metabolic engineering applications.

Structural Mapping of Protein Aggregates in Live Cells Modeling Huntington's Disease

While protein aggregation is a hallmark of many neurodegenerative diseases, acquiring structural information on protein aggregates inside live cells remains challenging. Traditional microscopy does not provide structural information on protein systems. Routinely used fluorescent protein tags, such as Green Fluorescent Protein (GFP), might perturb native structures. Here, we report a counter-propagating mid-infrared photothermal imaging approach enabling mapping of secondary structure of protein aggregates in live cells modeling Huntington's disease. By comparing mid-infrared photothermal spectra of label-free and GFP-tagged huntingtin inclusions, we demonstrate that GFP fusions indeed perturb the secondary structure of aggregates. By implementing spectra with small spatial step for dissecting spectral features within sub-micrometer distances, we reveal that huntingtin inclusions partition into a β-sheet-rich core and a ɑ-helix-rich shell. We further demonstrate that this structural partition exists only in cells with the [RNQ+] prion state, while [rnq-] cells only carry smaller β-rich non-toxic aggregates. Collectively, our methodology has the potential to unveil detailed structural information on protein assemblies in live cells, enabling high-throughput structural screenings of macromolecular assemblies.

Rapidly Inducible Yeast Surface Display for Antibody Evolution with OrthoRep

We recently developed "autonomous hypermutation yeast surface display" (AHEAD), a technology that enables the rapid generation of potent and specific antibodies in yeast. AHEAD pairs yeast surface display with an error-prone orthogonal DNA replication system (OrthoRep) to continuously and rapidly mutate surface-displayed antibodies, thereby enabling enrichment for stronger binding variants through repeated rounds of cell growth and fluorescence-activated cell sorting. AHEAD currently utilizes a standard galactose induction system to drive the selective display of antibodies on the yeast surface. However, achieving maximal display levels can require up to 48 h of induction. Here we report an updated version of the AHEAD platform that utilizes a synthetic β-estradiol-induced gene expression system to regulate the surface display of antibodies and find that induction is notably faster in achieving surface display for both our AHEAD system and traditional yeast surface display from nuclear plasmids that do not hypermutate. The updated AHEAD platform was fully functional in repeated rounds of evolution to drive the rapid evolution of antibodies.

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

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

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

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

A high-throughput synthetic biology approach for studying combinatorial chromatin-based transcriptional regulation

The construction of synthetic gene circuits requires the rational combination of multiple regulatory components, but predicting their behavior can be challenging due to poorly understood component interactions and unexpected emergent behaviors. In eukaryotes, chromatin regulators (CRs) are essential regulatory components that orchestrate gene expression. Here, we develop a screening platform to investigate the impact of CR pairs on transcriptional activity in yeast. We construct a combinatorial library consisting of over 1,900 CR pairs and use a high-throughput workflow to characterize the impact of CR co-recruitment on gene expression. We recapitulate known interactions and discover several instances of CR pairs with emergent behaviors. We also demonstrate that supervised machine learning models trained with low-dimensional amino acid embeddings accurately predict the impact of CR co-recruitment on transcriptional activity. This work introduces a scalable platform and machine learning approach that can be used to study how networks of regulatory components impact gene expression.

Repurposing plant hormone receptors as chemically-inducible genetic switches for dynamic regulation in yeast

Precise control of gene expression is critical for optimizing cellular metabolism and improving the production of valuable biochemicals. However, hard-wired approaches to pathway engineering, such as optimizing promoters, can take time and effort. Moreover, limited tools exist for controlling gene regulation in non-conventional hosts. Here, we develop a two-channel chemically-regulated gene expression system for the multi-stress tolerant yeast Kluyveromyces marxianus and use it to tune ethyl acetate production, a native metabolite produced at high titers in this yeast. To achieve this, we repurposed the plant hormone sensing modules (PYR1ABA/HAB1 and PYR1*MANDI/HAB1*) for high dynamic-range gene activation and repression controlled by either abscisic acid (ABA) or mandipropamid (mandi). To redirect metabolic flux towards ethyl acetate biosynthesis, we simultaneously repress pyruvate dehydrogenase (PDA1) and activate pyruvate decarboxylase (PDC1) to enhance ethyl acetate titers. Thus, we have developed new tools for chemically tuning gene expression in K. marxianus and S. cerevisiae that should be deployable across many non-conventional eukaryotic hosts.

Edible mycelium bioengineered for enhanced nutritional value and sensory appeal using a modular synthetic biology toolkit

Filamentous fungi are critical in the transition to a more sustainable food system. While genetic modification of these organisms has promise for enhancing the nutritional value, sensory appeal, and scalability of fungal foods, genetic tools and demonstrated use cases for bioengineered food production by edible strains are lacking. Here, we develop a modular synthetic biology toolkit for Aspergillus oryzae, an edible fungus used in fermented foods, protein production, and meat alternatives. Our toolkit includes a CRISPR-Cas9 method for gene integration, neutral loci, and tunable promoters. We use these tools to elevate intracellular levels of the nutraceutical ergothioneine and the flavor-and color molecule heme in the edible biomass. The strain overproducing heme is red in color and is readily formulated into imitation meat patties with minimal processing. These findings highlight the promise of synthetic biology to enhance fungal foods and provide useful genetic tools for applications in food production and beyond.

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

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

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

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

General mechanisms of weak acid-tolerance and current strategies for the development of tolerant yeasts

Yeast cells are often subjected to various types of weak acid stress in the process of industrial production, food processing, and preservation, resulting in growth inhibition and reduced fermentation performance. Under acidic conditions, weak acids enter the near-neutral yeast cytoplasm and dissociate into protons and anions, leading to cytoplasmic acidification and cell damage. Although some yeast strains have developed the ability to survive weak acids, the complexity and diversity of stresses during industrial production still require the application of appropriate strategies for phenotypes improvement. In this review, we summarized current knowledge concerning weak acid stress response and resistance, which may suggest important targets for further construction of more robust strains. We also highlight current feasible strategies for improving the weak acid resistance of yeasts, such as adaptive laboratory evolution, transcription factors engineering, and cell membrane/wall engineering. Moreover, the challenges and perspectives associated with improving the competitiveness of industrial strains are also discussed. This review provides effective strategies for improving the industrial phenotypes of yeast from multiple dimensions in future studies.

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

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

A Layered Genetic Design Enables the Yeast Galactose Regulon to Respond to Cyanamide

The commonly used expression systems in Saccharomyces cerevisiae typically rely on either constitutive or galactose-regulated promoters. The lack of inducible systems in S. cerevisiae limits the precise temporal regulation of protein function and yeast metabolism. We herein repurposed the galactose-regulated system to make it respond to cyanamide. By using a cyanamide-inducible DDI2 promoter to control Gal4 expression in CEN.PK2-1C with Δgal80, a tight and graded cyanamide-inducible GAL system with an enhanced signal output was constructed. Subsequently, we demonstrated that the cyanamide-inducible GAL system was capable of tightly regulating the pentafunctional Aro1 protein to achieve conditional shikimate pathway activity. Taken together, the cyanamide-inducible GAL system could be implemented for both fundamental research and applied biotechnology.

A roadmap to establish a comprehensive platform for sustainable manufacturing of natural products in yeast

Secondary natural products (NPs) are a rich source for drug discovery. However, the low abundance of NPs makes their extraction from nature inefficient, while chemical synthesis is challenging and unsustainable. Saccharomyces cerevisiae and Pichia pastoris are excellent manufacturing systems for the production of NPs. This Perspective discusses a comprehensive platform for sustainable production of NPs in the two yeasts through system-associated optimization at four levels: genetics, temporal controllers, productivity screening, and scalability. Additionally, it is pointed out critical metabolic building blocks in NP bioengineering can be identified through connecting multilevel data of the optimized system using deep learning.

Design of Four Small-Molecule-Inducible Systems in the Yeast Chromosome, Applied to Optimize Terpene Biosynthesis

The optimization of cellular functions often requires the balancing of gene expression, but the physical construction and screening of alternative designs are costly and time-consuming. Here, we construct a strain of Saccharomyces cerevisiae that contains a "sensor array" containing bacterial regulators that respond to four small-molecule inducers (vanillic acid, xylose, aTc, IPTG). Four promoters can be independently controlled with low background and a 40- to 5000-fold dynamic range. These systems can be used to study the impact of changing the level and timing of gene expression without requiring the construction of multiple strains. We apply this approach to the optimization of a four-gene heterologous pathway to the terpene linalool, which is a flavor and precursor to energetic materials. Using this approach, we identify bottlenecks in the metabolic pathway. This work can aid the rapid automated strain development of yeasts for the bio-manufacturing of diverse products, including chemicals, materials, fuels, and food ingredients.