The development and characterization of synthetic minimal yeast promoters

Microfluidic Fluorescence-Activated Cell Sorting of Convolutional Neural Network-Designed Synthetic Yeast Promoter

The artificial design and high-throughput screening (HTS) of synthetic yeast promoters are crucial for gene expression and metabolite biosynthesis in synthetic biology. It is essential to expand the screening scope and enhance the product identification in promoter engineering. Here, we develop a branch convolutional neural network (B-CNN), learning the sequence composition and structural properties of natural promoters, to comprehensively predict their relative strength and redesign the core region. It is combined with a genetic algorithm to identify mutant regions/sites of the alcohol oxidase 1 promoter (PAOX1) from Pichia pastoris (P. pastoris). Consecutive fluorescent recognition and automatic sorting of the GFP-expressing library of core PAOX1 were finished in a laboratory-designed microfluidic fluorescence-activated cell sorting (μFACS) system. The rigid μFACS chip was fabricated, achieving single-cell sorting and meeting the requirement of complicated sterilization with reduced volumes and improved cell throughput (7000 cells/s). After extensive exploration of the sorting parameters, P. pastoris with high-intensity PAOX1 (5.3× improvement) was successfully screened and validated by a microplate reader. The mutant PAOX1 was further applied for the biosynthesis of PD-L1-specific protein with a 30% increase in production, proving its effectiveness and feasibility. This study provided novel insights into the rational design and HTS of yeast functional components with enhanced performance.

Rewiring Estrogen Receptor α into Bisphenol Selective Receptors Using Darwin Assembly-Based Directed Evolution (DADE) in Saccharomyces cerevisiae

Bisphenols are widely used in manufacturing plastics and resins, but their environmental persistence raises concerns to human health and ecosystems. Accurate measurements for bisphenols are crucial for effective monitoring and regulation. Analytical methods detect only preselected bisphenols, while bioassays assessing estrogen receptor α activation suffer from poor sensitivity and strong background signals due to estrogenic contaminations. To develop a bioassay in Saccharomyces cerevisiae with increased sensitivity and specificity for bisphenols, we performed multi-site directed mutagenesis and directed evolution of more than 108 stably integrated estrogen receptor variants. By mutating the estrogen receptor α towards recognition of bisphenol A in yeast, we determined the preBASE variant (M421G_V422G_V533D_L536G_Y537S) with elevated bisphenol A sensitivity (EC50:329 nM) and lost estrogen responsiveness (EC50:0,17 mM). Further engineering yielded an off-target mutant, identified as the Bisphenol-Affinity and Specificity-Enhanced (BASE) variant (M421G_V422G_V533D_L536G_Y537S_L544I) that uses bisphenols as its primary agonist (EC50:32 mM) and impaired estrogen sensitivity (EC50:85M). The rewiring into a bisphenol receptor was confirmed in ligand binding assays to purified ligand binding domains. Taken together, the identified variants form stepping stones for further protein engineering to generate bisphenol specific high-throughput yeast-based bioassays.

A versatile genetic toolkit for engineering Wickerhamomyces ciferrii for tetraacetyl phytosphingosine production

Wickerhamomyces ciferrii: a non-conventional yeast with significant industrial potential for tetraacetyl phytosphingosine (TAPS), remains underutilized due to the lack of a comprehensive genetic toolbox. In this study, we developed a modular genetic system tailored for Wickerhamomyces ciferrii to enable strain engineering and metabolic pathway optimization. This toolkit includes episomal plasmids incorporating multiple selectable markers, replication origins, and fluorescent reporters. Systematic evaluation of four antibiotic resistance markers demonstrated that nourseothricin, geneticin, and zeocin effectively confer resistance, whereas hygromycin B did not support selection in this host. Among three tested replication origins, 2μ and CEN6/ARS4 enabled stable episomal maintenance, whereas panARS failed to replicate. Expression analysis of six fluorescent proteins under the endogenous PGK1 promoter revealed significant variability in transcript levels, which correlated with codon adaptation index values, emphasizing the importance of codon optimization for heterologous expression. Additionally, characterization of the endogenous TDH3, PGK1, and PDA1 promoters using two highly expressed fluorescent proteins confirmed that promoter strength is largely independent of the downstream coding sequence. To demonstrate the functional application of this toolkit, we overexpressed a phosphorylation-insensitive mutant of acetyl-CoA carboxylase (ACC1 S26A-S1161A ), resulting in a 2.4-fold increase in TAPS production. Collectively, this study establishes a versatile genetic platform for W. ciferrii, providing a robust foundation for future synthetic biology and metabolic engineering applications.

Advancing cellulose utilization and engineering consolidated bioprocessing yeasts: current state and perspectives

Despite the lack of implementation of consolidated bioprocessing (CBP) at an industrial scale, this bioconversion strategy still holds significant potential as an economically viable solution for converting lignocellulosic biomass (LCB) into biofuels and green chemicals, provided an appropriate organism can be isolated or engineered. The use of Saccharomyces cerevisiae for this purpose requires, among other things, the development of a cellulase expression system within the yeast. Over the past three decades, numerous studies have reported the expression of cellulase-encoding genes, both individually and in combination, in S. cerevisiae. Various strategies have emerged to produce a core set of cellulases, with differing degrees of success. While one-step conversion of cellulosic substrates to ethanol has been reported, the resulting titers and productivities fall well below industrial requirements. In this review, we examine the strategies employed for cellulase expression in yeast, highlighting the successes in developing basic cellulolytic CBP-enabled yeasts. We also summarize recent advancements in rational strain design and engineering, exploring how these approaches can be further enhanced through modern synthetic biology tools to optimize CBP-enabled yeast strains for potential industrial applications. KEY POINTS: • S. cerevisiae's lack of cellulolytic ability warrants its engineering for industry. • Advancements in the expression of core sets of cellulases have been reported. • Rational engineering is needed to enhance cellulase secretion and strain robustness. • Insights gained from omics strategies will direct the future development of CBP strains.

Recent advances in genetic engineering and chemical production in yeast species

Yeasts have emerged as well-suited microbial cell factory for the sustainable production of biofuels, organic acids, terpenoids, and specialty chemicals. This ability is bolstered by advances in genetic engineering tools, including CRISPR-Cas systems and modular cloning in both conventional (Saccharomyces cerevisiae) and non-conventional (Yarrowia lipolytica, Rhodotorula toruloides, Candida krusei) yeasts. Additionally, genome-scale metabolic models and machine learning approaches have accelerated efforts to create a broad range of compounds that help reduce dependency on fossil fuels, mitigate climate change, and offer sustainable alternatives to petrochemical-derived counterparts. In this review, we highlight the cutting-edge genetic tools driving yeast metabolic engineering and then explore the diverse applications of yeast-based platforms for producing value-added products. Collectively, this review underscores the pivotal role of yeast biotechnology in efforts to build a sustainable bioeconomy.

Promoter engineering with programmable upstream activating sequences in Aspergillus Niger cell factory

BACKGROUND

Aspergillus niger is an important industrial filamentous fungus used to produce organic acids and enzymes. A wide dynamic range of promoters, particularly strong promoters, are required for fine-tuning the regulation of gene expression to balance metabolic flux and achieve the high yields of desired products. However, the limited understanding of promoter architectures and activities restricts the efficient transcription regulation of targets in strain engineering in A. niger.

RESULTS

In this study, we identified two functional upstream activation sequences (UAS) located upstream of the core promoters of highly expressed genes in A. niger. We constructed and characterized a synthetic promoter library by fusing the efficient UAS elements upstream of the strong constitute PgpdA promoter in A. niger. It demonstrated that the strength of synthetic promoters was fine-tuned with a wide range by tandem assembly of the UAS elements. Notably, the most potent promoter exhibited 5.4-fold higher activity than the strongest PgpdA promoter reported previously, significantly extending the range of strong promoters. Using citric acid production as a case study, we employed the synthetic promoter library to enhance citric acid efflux by regulating the cexA expression in A. niger. It showed a 1.6-2.3-fold increase in citric acid production compared to the parent strain, achieving a maximum titer of 145.3 g/L.

CONCLUSIONS

This study proved that the synthetic promoter library was a powerful toolkit for precise tuning of transcription in A. niger. It also underscores the potential of promoter engineering for gene regulation in strain improvement of fungal cell factories.

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.

Designing strong inducible synthetic promoters in yeasts

Inducible promoters are essential for precise control of target gene expression in synthetic biological systems. However, engineering eukaryotic promoters is often more challenging than engineering prokaryotic promoters due to their greater mechanistic complexity. In this study, we describe a simple and reliable approach for constructing strongly inducible synthetic promoters with minimum leakiness in yeasts. The results indicate that the leakiness of yeast-inducible synthetic promoters is primarily the result of cryptic transcriptional activation of heterologous sequences that may be avoided by appropriate insulation and operator mutagenesis. Our promoter design approach has successfully generated robust, inducible promoters that achieve a > 103-fold induction in reporter gene expression. The utility of these promoters is demonstrated by using them to produce various biologics with titers up to 2 g/L, including antigens designed to raise specific antibodies against a SARS-CoV-2 omicron variant through chicken immunization.

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.

A novel interpretable deep learning-based computational framework designed synthetic enhancers with broad cross-species activity

Enhancers play a critical role in dynamically regulating spatial-temporal gene expression and establishing cell identity, underscoring the significance of designing them with specific properties for applications in biosynthetic engineering and gene therapy. Despite numerous high-throughput methods facilitating genome-wide enhancer identification, deciphering the sequence determinants of their activity remains challenging. Here, we present the DREAM (DNA cis-Regulatory Elements with controllable Activity design platforM) framework, a novel deep learning-based approach for synthetic enhancer design. Proficient in uncovering subtle and intricate patterns within extensive enhancer screening data, DREAM achieves cutting-edge sequence-based enhancer activity prediction and highlights critical sequence features implicating strong enhancer activity. Leveraging DREAM, we have engineered enhancers that surpass the potency of the strongest enhancer within the Drosophila genome by approximately 3.6-fold. Remarkably, these synthetic enhancers exhibited conserved functionality across species that have diverged more than billion years, indicating that DREAM was able to learn highly conserved enhancer regulatory grammar. Additionally, we designed silencers and cell line-specific enhancers using DREAM, demonstrating its versatility. Overall, our study not only introduces an interpretable approach for enhancer design but also lays out a general framework applicable to the design of other types of cis-regulatory elements.

GOLDBAR: A Framework for Combinatorial Biological Design

With the rise of new DNA part libraries and technologies for assembling DNA, synthetic biologists are increasingly constructing and screening combinatorial libraries to optimize their biological designs. As combinatorial libraries are used to generate data on design performance, new rules for composing biological designs will emerge. Most formal frameworks for combinatorial design, however, do not yet support formal comparison of design composition, which is needed to facilitate automated analysis and machine learning in massive biological design spaces. To address this need, we introduce a combinatorial design framework called GOLDBAR. Compared with existing frameworks, GOLDBAR enables synthetic biologists to intersect and merge the rules for entire classes of biological designs to extract common design motifs and infer new ones. Here, we demonstrate the application of GOLDBAR to refine/validate design spaces for TetR-homologue transcriptional logic circuits, verify the assembly of a partial nif gene cluster, and infer novel gene clusters for the biosynthesis of rebeccamycin. We also discuss how GOLDBAR could be used to facilitate grammar-based machine learning in synthetic biology.

Evolving dual-trait EPSP synthase variants using a synthetic yeast selection system

The enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) functions in the shikimate pathway which is responsible for the production of aromatic amino acids and precursors of other essential secondary metabolites in all plant species. EPSPS is also the molecular target of the herbicide glyphosate. While some plant EPSPS variants have been characterized with reduced glyphosate sensitivity and have been used in biotechnology, the glyphosate insensitivity typically comes with a cost to catalytic efficiency. Thus, there exists a need to generate additional EPSPS variants that maintain both high catalytic efficiency and high glyphosate tolerance. Here, we create a synthetic yeast system to rapidly study and evolve heterologous EPSP synthases for these dual traits. Using known EPSPS variants, we first validate that our synthetic yeast system is capable of recapitulating growth characteristics observed in plants grown in varying levels of glyphosate. Next, we demonstrate that variants from mutagenesis libraries with distinct phenotypic traits can be isolated depending on the selection criteria applied. By applying strong dual-trait selection pressure, we identify a notable EPSPS mutant after just a single round of evolution that displays robust glyphosate tolerance (Ki of nearly 1 mM) and improved enzymatic efficiency over the starting point (~2.5 fold). Finally, we show the crystal structure of corn EPSPS and the top resulting mutants and demonstrate that certain mutants have the potential to outperform previously reported glyphosate-resistant EPSPS mutants, such as T102I and P106S (denoted as TIPS), in whole-plant testing. Altogether, this platform helps explore the trade-off between glyphosate resistance and enzymatic efficiency.

Engineering artificial cross-species promoters with different transcriptional strengths

As a fundamental tool in synthetic biology, promoters are pivotal in regulating gene expression, enabling precise genetic control and spurring innovation across diverse biotechnological applications. However, most advances in engineered genetic systems rely on host-specific regulation of the genetic portion. With the burgeoning diversity of synthetic biology chassis cells, there emerges a pressing necessity to broaden the universal promoter toolkit spectrum, ensuring adaptability across various microbial chassis cells for enhanced applicability and customization in the evolving landscape of synthetic biology. In this study, we analyzed and validated the primary structures of natural endogenous promoters from Escherichia coli, Bacillus subtilis, Corynebacterium glutamicum, Saccharomyces cerevisiae, and Pichia pastoris, and through strategic integration and rational modification of promoter motifs, we developed a series of cross-species promoters (Psh) with transcriptional activity in five strains (prokaryotic and eukaryotic). This series of cross species promoters can significantly expand the synthetic biology promoter toolkit while providing a foundation and inspiration for standardized development of universal components The combinatorial use of key elements from prokaryotic and eukaryotic promoters presented in this study represents a novel strategy that may offer new insights and methods for future advancements in promoter engineering.

The contribution of microorganisms to sustainable development: towards a green future through synthetic biology and systems biology

Microorganisms, though invisible, they play a pivotal role in influencing both the global economy and societal progress., and job market. This discussion highlights their significant impact on various sectors like food, pharmaceuticals, and chemicals. These versatile microorganisms act as efficient cell factories, producing chemicals from renewable sources and aiding in waste degradation. The historical development of microbial cell factories has relied on a trial-and-error approach, following a cyclic process of design, construction, testing, and refinement. The essay delves into the critical role of microorganisms in sustainable development, highlighting their capacity for sustainable chemical production and waste degradation. The incorporation of microbial technology presents significant opportunities for advancing the United Nations’ Sustainable Development Goals. Microorganisms contribute significantly to sustainable development by influencing the economy, creating jobs, improving food and pharmaceutical production, and advancing chemical manufacturing. Their utilization brings advantages like cleaner production methods, renewable resource utilization, and healthcare contributions. Overall, microorganisms are essential players in sustainable development, offering solutions for a more environmentally friendly and economically viable future.

The Ty1 retrotransposon harbors a DNA region that performs dual functions as both a gene silencing and chromatin insulator

In various eukaryotic kingdoms, long terminal repeat (LTR) retrotransposons repress transcription by infiltrating heterochromatin generated within their elements. In contrast, the budding yeast LTR retrotransposon Ty1 does not itself undergo transcriptional repression, although it is capable of repressing the transcription of the inserted genes within it. In this study, we identified a DNA region within Ty1 that exerts its silencing effect via sequence orientation. We identified a DNA region within the Ty1 group-specific antigen (GAG) gene that causes gene silencing, termed GAG silencing (GAGsi), in which the silent chromatin in the GAGsi region is created by euchromatin-specific histone modifications. A characteristic inverted repeat (IR) sequence is present at the 5' end of this region, forming a chromatin boundary between promoter-specific chromatin upstream of the IR sequence and silent chromatin downstream of the IR sequence. In addition, Esc2 and Rad57, which are involved in DNA repair, were required for GAGsi silencing. Finally, the chromatin boundary was required for the transcription of Ty1 itself. Thus, the GAGsi sequence contributes to the creation of a chromatin environment that promotes Ty1 transcription.

Deep mutational scanning quantifies DNA binding and predicts clinical outcomes of PAX6 variants

Nonsense and missense mutations in the transcription factor PAX6 cause a wide range of eye development defects, including aniridia, microphthalmia and coloboma. To understand how changes of PAX6:DNA binding cause these phenotypes, we combined saturation mutagenesis of the paired domain of PAX6 with a yeast one-hybrid (Y1H) assay in which expression of a PAX6-GAL4 fusion gene drives antibiotic resistance. We quantified binding of more than 2700 single amino-acid variants to two DNA sequence elements. Mutations in DNA-facing residues of the N-terminal subdomain and linker region were most detrimental, as were mutations to prolines and to negatively charged residues. Many variants caused sequence-specific molecular gain-of-function effects, including variants in position 71 that increased binding to the LE9 enhancer but decreased binding to a SELEX-derived binding site. In the absence of antibiotic selection, variants that retained DNA binding slowed yeast growth, likely because such variants perturbed the yeast transcriptome. Benchmarking against known patient variants and applying ACMG/AMP guidelines to variant classification, we obtained supporting-to-moderate evidence that 977 variants are likely pathogenic and 1306 are likely benign. Our analysis shows that most pathogenic mutations in the paired domain of PAX6 can be explained simply by the effects of these mutations on PAX6:DNA association, and establishes Y1H as a generalisable assay for the interpretation of variant effects in transcription factors.

Species-specific design of artificial promoters by transfer-learning based generative deep-learning model

Native prokaryotic promoters share common sequence patterns, but are species dependent. For understudied species with limited data, it is challenging to predict the strength of existing promoters and generate novel promoters. Here, we developed PromoGen, a collection of nucleotide language models to generate species-specific functional promoters, across dozens of species in a data and parameter efficient way. Twenty-seven species-specific models in this collection were finetuned from the pretrained model which was trained on multi-species promoters. When systematically compared with native promoters, the Escherichia coli- and Bacillus subtilis-specific artificial PromoGen-generated promoters (PGPs) were demonstrated to hold all distribution patterns of native promoters. A regression model was developed to score generated either by PromoGen or by another competitive neural network, and the overall score of PGPs is higher. Encouraged by in silico analysis, we further experimentally characterized twenty-two B. subtilis PGPs, results showed that four of tested PGPs reached the strong promoter level while all were active. Furthermore, we developed a user-friendly website to generate species-specific promoters for 27 different species by PromoGen. This work presented an efficient deep-learning strategy for de novo species-specific promoter generation even with limited datasets, providing valuable promoter toolboxes especially for the metabolic engineering of understudied microorganisms.

Rational evolution for altering the ligand preference of estrogen receptor alpha

Estrogen receptor α is commonly used in synthetic biology to control the activity of genome editing tools. The activating ligands, estrogens, however, interfere with various cellular processes, thereby limiting the applicability of this receptor. Altering its ligand preference to chemicals of choice solves this hurdle but requires adaptation of unspecified ligand-interacting residues. Here, we provide a solution by combining rational protein design with multi-site-directed mutagenesis and directed evolution of stably integrated variants in Saccharomyces cerevisiae. This method yielded an estrogen receptor variant, named TERRA, that lost its estrogen responsiveness and became activated by tamoxifen, an anti-estrogenic drug used for breast cancer treatment. This tamoxifen preference of TERRA was maintained in mammalian cells and mice, even when fused to Cre recombinase, expanding the mammalian synthetic biology toolbox. Not only is our platform transferable to engineer ligand preference of any steroid receptor, it can also profile drug-resistance landscapes for steroid receptor-targeted therapies.

A universal system for boosting gene expression in eukaryotic cell-lines

We demonstrate a transcriptional regulatory design algorithm that can boost expression in yeast and mammalian cell lines. The system consists of a simplified transcriptional architecture composed of a minimal core promoter and a synthetic upstream regulatory region (sURS) composed of up to three motifs selected from a list of 41 motifs conserved in the eukaryotic lineage. The sURS system was first characterized using an oligo-library containing 189,990 variants. We validate the resultant expression model using a set of 43 unseen sURS designs. The validation sURS experiments indicate that a generic set of grammar rules for boosting and attenuation may exist in yeast cells. Finally, we demonstrate that this generic set of grammar rules functions similarly in mammalian CHO-K1 and HeLa cells. Consequently, our work provides a design algorithm for boosting the expression of promoters used for expressing industrially relevant proteins in yeast and mammalian cell lines.

Development of the Static and Dynamic Gene Expression Regulation Toolkit in Pseudomonas chlororaphis

The advancement of metabolic engineering and synthetic biology has promoted in-depth research on the nonmodel microbial metabolism, and the potential of nonmodel organisms in industrial biotechnology is becoming increasingly evident. The nonmodel organism Pseudomonas chlororaphis is a safe plant growth promoting bacterium for the production of phenazine compounds; however, its application is seriously hindered due to the lack of an effective gene expression precise regulation toolkit. In this study, we constructed a library of 108 promoter-5'-UTR (PUTR) and characterized them through fluorescent protein detection. Then, 6 PUTRs with stable low, intermediate, and high intensities were further characterized by report genes lacZ encoding β-galactosidase from Escherichia coli K12 and phzO encoding PCA monooxygenase from P. chlororaphis GP72 and thus developed as a static gene expression regulation system. Furthermore, the stable and high-intensity expressed PMOK_RS0128085UTR was fused with the LacO operator to construct an IPTG-induced plasmid, and a self-induced plasmid was constructed employing the high-intensity PMOK_RS0116635UTR regulated by cell density, resulting in a dynamic gene expression regulation system. In summary, this study established two sets of static and dynamic regulatory systems for P. chlororaphis, providing an effective toolkit for fine-tuning gene expression and reprograming the metabolism flux.

Genome streamlining to improve performance of a fast-growing cyanobacterium Synechococcus elongatus UTEX 2973

Cyanobacteria are photosynthetic organisms that have garnered significant recognition as potential hosts for sustainable bioproduction. However, their complex regulatory networks pose significant challenges to major metabolic engineering efforts, thereby limiting their feasibility as production hosts. Genome streamlining has been demonstrated to be a successful approach for improving productivity and fitness in heterotrophs but is yet to be explored to its full potential in phototrophs. Here, we present the systematic reduction of the genome of the cyanobacterium exhibiting the fastest exponential growth, Synechococcus elongatus UTEX 2973. This work, the first of its kind in a photoautotroph, involved an iterative process using state-of-the-art genome-editing technology guided by experimental analysis and computational tools. CRISPR-Cas3 enabled large, progressive deletions of predicted dispensable regions and aided in the identification of essential genes. The large deletions were combined to obtain a strain with 55-kb genome reduction. The strains with streamlined genome showed improvement in growth (up to 23%) and productivity (by 22.7%) as compared to the wild type (WT). This streamlining strategy not only has the potential to develop cyanobacterial strains with improved growth and productivity traits but can also facilitate a better understanding of their genome-to-phenome relationships.IMPORTANCEGenome streamlining is an evolutionary strategy used by natural living systems to dispense unnecessary genes from their genome as a mechanism to adapt and evolve. While this strategy has been successfully borrowed to develop synthetic heterotrophic microbial systems with desired phenotype, it has not been extensively explored in photoautotrophs. Genome streamlining strategy incorporates both computational predictions to identify the dispensable regions and experimental validation using genome-editing tool, and in this study, we have employed a modified strategy with the goal to minimize the genome size to an extent that allows optimal cellular fitness under specified conditions. Our strategy has explored a novel genome-editing tool in photoautotrophs, which, unlike other existing tools, enables large, spontaneous optimal deletions from the genome. Our findings demonstrate the effectiveness of this modified strategy in obtaining strains with streamlined genome, exhibiting improved fitness and productivity.

Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges

Machine learning (ML), particularly deep learning (DL), has made rapid and substantial progress in synthetic biology in recent years. Biotechnological applications of biosystems, including pathways, enzymes, and whole cells, are being probed frequently with time. The intricacy and interconnectedness of biosystems make it challenging to design them with the desired properties. ML and DL have a synergy with synthetic biology. Synthetic biology can be employed to produce large data sets for training models (for instance, by utilizing DNA synthesis), and ML/DL models can be employed to inform design (for example, by generating new parts or advising unrivaled experiments to perform). This potential has recently been brought to light by research at the intersection of engineering biology and ML/DL through achievements like the design of novel biological components, best experimental design, automated analysis of microscopy data, protein structure prediction, and biomolecular implementations of ANNs (Artificial Neural Networks). I have divided this review into three sections. In the first section, I describe predictive potential and basics of ML along with myriad applications in synthetic biology, especially in engineering cells, activity of proteins, and metabolic pathways. In the second section, I describe fundamental DL architectures and their applications in synthetic biology. Finally, I describe different challenges causing hurdles in the progress of ML/DL and synthetic biology along with their solutions.

Hybrid Synthetic Promoters in Saccharomyces cerevisiae Built on Foreign Promoter Sequences

Traditionally, hybrid promoters are constructed, in Saccharomyces cerevisiae, by joining the core region and the upstream activating sequences from different native promoters. Here, we describe a new design that makes use of the core promoters from foreign organisms: viruses, humans, and the yeast Schizosaccharomyces pombe. With this approach, we realized a library of 59 new constitutive promoters that span over nine folds in gene expression.

An extracellular glucose sensor for substrate-dependent secretion and display of cellulose-degrading enzymes

The efficient hydrolysis of lignocellulosic biomass into fermentable sugars is key for viable economic production of biofuels and biorenewable chemicals from second-generation feedstocks. Consolidated bioprocessing (CBP) combines lignocellulose saccharification and chemical production in a single step. To avoid wasting valuable resources during CBP, the selective secretion of enzymes (independent or attached to the surface) based on the carbon source available is advantageous. To enable enzyme expression and secretion based on extracellular glucose levels, we implemented a G-protein-coupled receptor (GPCR)-based extracellular glucose sensor; this allows the secretion and display of cellulases in the presence of the cellulosic fraction of lignocellulose by leveraging cellobiose-dependent signal amplification. We focused on the glucose-responsiveness of the HXT1 promoter and engineered PHXT1 by changing its core to that of the strong promoter PTHD3 , increasing extracellular enzyme activity by 81%. We then demonstrated glucose-mediated expression and cell-surface display of the β-glucosidase BglI on the surface of Saccharomyces cerevisiae. The display system was further optimized by re-directing fatty acid pools from lipid droplet synthesis toward formation of membrane precursors via knock-out of PAH1. This resulted in an up to 4.2-fold improvement with respect to the baseline strain. Finally, we observed cellobiose-dependent signal amplification of the system with an increase in enzymatic activity of up to 3.1-fold when cellobiose was added.

Encoding Genetic Circuits with DNA Barcodes Paves the Way for High-Throughput Profiling of Dose-Response Curves of Metabolite Biosensors

Metabolite biosensors, through which the intracellular metabolite concentrations could be converted to changes in gene expression, are widely used in a variety of applications according to the different output signals. However, it remains challenging to fine-tune the dose-response relationships of biosensors to meet the needs of various scenarios. On the other hand, the short read length of next-generation sequencing (NGS) has greatly limited the design capability of sequence libraries. To address these issues, we describe a DNA trackable assembly method, coupled with fluorescence-activated cell sorting and NGS (Sort-Seq), to achieve the characterization of dose-response curves in a massively parallel manner. As a proof of the concept, we constructed a malonyl-CoA biosensor library containing 5184 combinations with six levels of transcription factor dosage, four different operator positions, and 216 possible upstream enhancer sequence (UAS) designs in Saccharomyces cerevisiae BY4700. By using Sort-Seq and machine learning approach, we obtained comprehensive dose-response relationships of the combinatorial sequence space. Therefore, our pipeline provides a platform for the design, tuning, and profiling of biosensor response curves and shows great potential to facilitate the rational design of genetic circuits.

Promoters in Pichia pastoris: A Toolbox for Fine-Tuned Gene Expression

This chapter reviews the different promoters used to control gene expression in the yeast Pichia pastoris, mainly for recombinant protein production. It covers natural inducible, derepressed, and constitutive promoters, as well as engineered synthetic/hybrid promoters, orthologous promoters from related yeasts, and emerging bidirectional promoters. Key examples, characteristics, and regulatory mechanisms are discussed for each promoter class. Recent efforts in promoter engineering through rational design, mutagenesis, and computational approaches are also highlighted. Looking ahead, we anticipate further developments that will enhance promoter design for Pichia pastoris. Overall, this comprehensive overview underscores the importance of promoter choice and engineering for fully harnessing Pichia pastoris biotechnological potential.

Reshaping the yeast galactose regulon via GPCR signaling cascade

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

Advances in the dynamic control of metabolic pathways in Saccharomyces cerevisiae

The metabolic engineering of Saccharomyces cerevisiae has great potential for enhancing the production of high-value chemicals and recombinant proteins. Recent studies have demonstrated the effectiveness of dynamic regulation as a strategy for optimizing metabolic flux and improving production efficiency. In this review, we provide an overview of recent advancements in the dynamic regulation of S. cerevisiae metabolism. Here, we focused on the successful utilization of transcription factor (TF)-based biosensors within the dynamic regulatory network of S. cerevisiae. These biosensors are responsive to a wide range of endogenous and exogenous signals, including chemical inducers, light, temperature, cell density, intracellular metabolites, and stress. Additionally, we explored the potential of omics tools for the discovery of novel responsive promoters and their roles in fine-tuning metabolic networks. We also provide an outlook on the development trends in this field.

Building a eukaryotic chromosome arm by de novo design and synthesis

The genome of an organism is inherited from its ancestor and continues to evolve over time, however, the extent to which the current version could be altered remains unknown. To probe the genome plasticity of Saccharomyces cerevisiae, here we replace the native left arm of chromosome XII (chrXIIL) with a linear artificial chromosome harboring small sets of reconstructed genes. We find that as few as 12 genes are sufficient for cell viability, whereas 25 genes are required to recover the partial fitness defects observed in the 12-gene strain. Next, we demonstrate that these genes can be reconstructed individually using synthetic regulatory sequences and recoded open-reading frames with a "one-amino-acid-one-codon" strategy to remain functional. Finally, a synthetic neochromsome with the reconstructed genes is assembled which could substitute chrXIIL for viability. Together, our work not only highlights the high plasticity of yeast genome, but also illustrates the possibility of making functional eukaryotic chromosomes from entirely artificial sequences.

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.

Systematic sequence engineering enhances the induction strength of the glucose-regulated GTH1 promoter of Komagataella phaffii

The promoter of the high-affinity glucose transporter Gth1 (PGTH1) is tightly repressed on glucose and glycerol surplus, and strongly induced in glucose-limitation, thus enabling regulated methanol-free production processes in the yeast production host Komagataella phaffii. To further improve this promoter, an intertwined approach of nucleotide diversification through random and rational engineering was pursued. Random mutagenesis and fluorescence activated cell sorting of PGTH1 yielded five variants with enhanced induction strength. Reverse engineering of individual point mutations found in the improved variants identified two single point mutations with synergistic action. Sequential deletions revealed the key promoter segments for induction and repression properties, respectively. Combination of the single point mutations and the amplification of key promoter segments led to a library of novel promoter variants with up to 3-fold higher activity. Unexpectedly, the effect of gaining or losing a certain transcription factor binding site (TFBS) was highly dependent on its context within the promoter. Finally, the applicability of the novel promoter variants for biotechnological production was proven for the secretion of different recombinant model proteins in fed batch cultivation, where they clearly outperformed their ancestors. In addition to advancing the toolbox for recombinant protein production and metabolic engineering of K. phaffii, we discovered single nucleotide positions and correspondingly affected TFBS that distinguish between glycerol- and glucose-mediated repression of the native promoter.

Organelle-dependent polyprotein designs enable stoichiometric expression of nitrogen fixation components targeted to mitochondria

Introducing nitrogen fixation (nif   ) genes into eukaryotic genomes and targeting Nif components to mitochondria or chloroplasts is a promising strategy for engineering nitrogen-fixing plants. A prerequisite for achieving nitrogen fixation in crops is stable and stoichiometric expression of each component in organelles. Previously, we designed a polyprotein-based nitrogenase system depending on Tobacco Etch Virus protease (TEVp) to release functional Nif components from five polyproteins. Although this system satisfies the demand for specific expression ratios of Nif components in Escherichia coli, we encountered issues with TEVp cleavage of polyproteins targeted to yeast mitochondria. To overcome this obstacle, a version of the Nif polyprotein system was constructed by replacing TEVp cleavage sites with minimal peptide sequences, identified by knowledge-based engineering, that are susceptible to cleavage by the endogenous mitochondrial-processing peptidase. This replacement not only further reduces the number of genes required, but also prevents potential precleavage of polyproteins outside the target organelle. This version of the polyprotein-based nitrogenase system achieved levels of nitrogenase activity in E. coli, comparable to those observed with the TEVp-based polyprotein nitrogenase system. When applied to yeast mitochondria, stable and balanced expression of Nif components was realized. This strategy has potential advantages, not only for transferring nitrogen fixation to eukaryotic cells, but also for the engineering of other metabolic pathways that require mitochondrial compartmentalization.

An Overview of Deep Generative Models in Functional and Evolutionary Genomics

Following the widespread use of deep learning for genomics, deep generative modeling is also becoming a viable methodology for the broad field. Deep generative models (DGMs) can learn the complex structure of genomic data and allow researchers to generate novel genomic instances that retain the real characteristics of the original dataset. Aside from data generation, DGMs can also be used for dimensionality reduction by mapping the data space to a latent space, as well as for prediction tasks via exploitation of this learned mapping or supervised/semi-supervised DGM designs. In this review, we briefly introduce generative modeling and two currently prevailing architectures, we present conceptual applications along with notable examples in functional and evolutionary genomics, and we provide our perspective on potential challenges and future directions.

Promoters and introns as key drivers for enhanced gene expression in Saccharomyces cerevisiae

The transcription of genes in the yeast Saccharomyces cerevisiae is governed by multiple layers of regulatory elements and proteins, cooperating to ensure optimum expression of the final protein product based on the cellular requirements. Promoters have always been regarded as the most important determinant of gene transcription, but introns also play a key role in the expression of intron-encoding genes. Some introns can enhance transcription when introduced either promoter-proximal or embedded in the open reading frame of genes. However, the outcome is seldom predictable, with some introns increasing or decreasing transcription depending on the promoter and reporter gene employed. This chapter provides an overview of the general structure and function of promoters and introns and how they may cooperate during transcription to allow intron-mediated enhancement of gene expression. Since S. cerevisiae is a suitable host for recombinant protein production on a commercial level, stronger and more controllable promoters are in high demand. Enhanced gene expression can be achieved via promoter engineering, which may include introns that increase the efficacy of recombinant expression cassettes. Different models for the role of introns in transcription are briefly discussed to show how these intervening sequences can actively interact with the transcription machinery. Furthermore, recent examples of improved protein production via the introduction of promoter-proximal introns are highlighted to showcase the potential value of intron-mediated enhancement of gene expression.

Predicting transcriptional responses to heat and drought stress from genomic features using a machine learning approach in rice

Plants have evolved various mechanisms to adapt to adverse environmental stresses, such as the modulation of gene expression. Expression of stress-responsive genes is controlled by specific regulators, including transcription factors (TFs), that bind to sequence-specific binding sites, representing key components of cis-regulatory elements and regulatory networks. Our understanding of the underlying regulatory code remains, however, incomplete. Recent studies have shown that, by training machine learning (ML) algorithms on genomic sequence features, it is possible to predict which genes will transcriptionally respond to a specific stress. By identifying the most important features for gene expression prediction, these trained ML models allow, in theory, to further elucidate the regulatory code underlying the transcriptional response to abiotic stress. Here, we trained random forest ML models to predict gene expression in rice (Oryza sativa) in response to heat or drought stress. Apart from thoroughly assessing model performance and robustness across various input training data, the importance of promoter and gene body sequence features to train ML models was evaluated. The use of enriched promoter oligomers, complementing known TF binding sites, allowed us to gain novel insights in DNA motifs contributing to the stress regulatory code. By comparing genomic feature importance scores for drought and heat stress over time, general and stress-specific genomic features contributing to the performance of the learned models and their temporal variation were identified. This study provides a solid foundation to build and interpret ML models accurately predicting transcriptional responses and enables novel insights in biological sequence features that are important for abiotic stress responses.

Genome-wide analysis reveals Hsf1 maintains high transcript abundance of target genes controlled by strong constitutive promoter in Saccharomyces cerevisiae

BACKGROUND

In synthetic biology, the strength of promoter elements is the basis for precise regulation of target gene transcription levels, which in turn increases the yield of the target product. However, the results of many researches proved that excessive transcription levels of target genes actually reduced the yield of the target product. This phenomenon has been found in studies using different microorganisms as chassis cells, thus, it becomes a bottleneck problem to improve the yield of the target product.

RESULTS

In this study, promoters PGK1p and TDH3p with different strengths were used to regulate the transcription level of alcohol acetyl transferase encoding gene ATF1. The results demonstrated that the strong promoter TDH3p decreased the production of ethyl acetate. The results of Real-time PCR proved that the transcription level of ATF1 decreased rapidly under the control of TDH3p, and the unfolded protein reaction was activated, which may be the reason for the abnormal production caused by the strong promoter. RNA-sequencing analysis showed that the overexpression of differential gene HSP30 increased the transcriptional abundance of ATF1 gene and production of ethyl acetate. Interestingly, deletion of the heat shock protein family (e.g., Hsp26, Hsp78, Hsp82) decreased the production of ethyl acetate, suggesting that the Hsp family was also involved in the regulation of ATF1 gene transcription. Furthermore, the results proved that the Hsf1, an upstream transcription factor of Hsps, had a positive effect on alleviating the unfolded protein response and that overexpression of Hsf1 reprogramed the pattern of ATF1 gene transcript levels. The combined overexpression of Hsf1 and Hsps further increased the production of ethyl acetate. In addition, kinase Rim15 may be involved in this regulatory pathway. Finally, the regulation effect of Hsf1 on recombinant strains constructed by other promoters was verified, which confirmed the universality of the strategy.

CONCLUSIONS

Our results elucidated the mechanism by which Rim15-Hsf1-Hsps pathway reconstructed the repression of high transcription level stress and increased the production of target products, thereby providing new insights and application strategies for the construction of recombinant strains in synthetic biology.

A Modular Cloning Toolkit Including CRISPRi for the Engineering of the Human Fungal Pathogen and Biotechnology Host Candida glabrata

The yeast Candida glabrata is an emerging, often drug-resistant opportunistic human pathogen that can cause severe systemic infections in immunocompromised individuals. At the same time, it is a valuable biotechnology host that naturally accumulates high levels of pyruvate─a valuable chemical precursor. Tools for the facile engineering of this yeast could greatly accelerate studies on its pathogenicity and its optimization for biotechnology. While a few tools for plasmid-based expression and genome engineering have been developed, there is no well-characterized cloning toolkit that would allow the modular assembly of pathways or genetic circuits. Here, by characterizing the Saccharomyces cerevisiae-based yeast molecular cloning toolkit (YTK) in C. glabrata and by adding missing components, we build a well-characterized CgTK (C. glabrata toolkit). We used the CgTK to build a CRISPR interference system for C. glabrata that can be used to generate selectable phenotypes via single-gRNA targeting such as is required for genome-wide library screens.

Chance promoter activities illuminate the origins of eukaryotic intergenic transcriptions

It is debated whether the pervasive intergenic transcription from eukaryotic genomes has functional significance or simply reflects the promiscuity of RNA polymerases. We approach this question by comparing chance promoter activities with the expression levels of intergenic regions in the model eukaryote Saccharomyces cerevisiae. We build a library of over 105 strains, each carrying a 120-nucleotide, chromosomally integrated, completely random sequence driving the potential transcription of a barcode. Quantifying the RNA concentration of each barcode in two environments reveals that 41-63% of random sequences have significant, albeit usually low, promoter activities. Therefore, even in eukaryotes, where the presence of chromatin is thought to repress transcription, chance transcription is prevalent. We find that only 1-5% of yeast intergenic transcriptions are unattributable to chance promoter activities or neighboring gene expressions, and these transcriptions exhibit higher-than-expected environment-specificity. These findings suggest that only a minute fraction of intergenic transcription is functional in yeast.

Developing a Temperature-Inducible Transcriptional Rheostat in Neurospora crassa

Heat shock protein (HSP)-encoding genes (hsp), part of the highly conserved heat shock response (HSR), are known to be induced by thermal stress in several organisms. In Neurospora crassa, three hsp genes, hsp30, hsp70, and hsp80, have been characterized; however, the role of defined cis elements in their responses to discrete changes in temperature remains largely unexplored. To fill this gap, while also aiming to obtain a reliable fungal heat shock-inducible system, we analyzed different sections of each hsp promoter by assessing the expression of real-time transcriptional reporters. Whereas all three promoters and their resected versions were acutely induced by high temperatures, only hsp30 displayed a broad range of expression and high tunability, amply exceeding other inducible promoter systems existing in Neurospora, such as quinic acid- or light-inducible ones. As proof of concept, we employed one of these promoters to control the expression of clr-2, which encodes the master regulator of Neurospora cellulolytic capabilities. The resulting strain fails to grow on cellulose at 25°C, whereas it grows robustly if heat shock pulses are delivered daily. Additionally, we designed two hsp30 synthetic promoters and characterized them, as well as the native promoters, using a gradient of high temperatures, yielding a wide range of responses to thermal stimuli. Thus, Neurospora hsp30-based promoters represent a new set of modular elements that can be used as transcriptional rheostats to adjust the expression of a gene of interest or for the implementation of regulated circuitries for synthetic biology and biotechnological strategies. IMPORTANCE A timely and dynamic response to strong temperature fluctuations is paramount for organismal biology. At the same time, inducible promoters are a powerful tool for fungal biotechnological and synthetic biology endeavors. In this work, we analyzed the activity of several N. crassa heat shock protein (hsp) promoters at a wide range of temperatures, observing that hsp30 exhibits remarkable sensitivity and a dynamic range of expression as we charted the response of this promoter to subtle increases in temperature, and also as we built and analyzed synthetic promoters based on hsp30 cis elements. As proof of concept, we tested the ability of hsp30 to provide tight control of a central process, cellulose degradation. While this study provides an unprecedented description of the regulation of the N. crassa hsp genes, it also contributes a noteworthy addition to the molecular toolset of transcriptional controllers in filamentous fungi.

De novo biosynthesis of berberine and halogenated benzylisoquinoline alkaloids in Saccharomyces cerevisiae

Berberine is an extensively used pharmaceutical benzylisoquinoline alkaloid (BIA) derived from plants. Microbial manufacturing has emerged as a promising approach to source valuable BIAs. Here, we demonstrated the complete biosynthesis of berberine in Saccharomyces cerevisiae by engineering 19 genes including 12 heterologous genes from plants and bacteria. Overexpressing bottleneck enzymes, fermentation scale-up, and heating treatment after fermentation increased berberine titer by 643-fold to 1.08 mg L-1. This pathway also showed high efficiency to incorporate halogenated tyrosine for the synthesis of unnatural BIA derivatives that have higher therapeutical potentials. We firstly demonstrate the in vivo biosynthesis of 11-fluoro-tetrahydrocolumbamine via nine enzymatic reactions. The efficiency and promiscuity of our pathway also allow for the simultaneous incorporation of two fluorine-substituted tyrosine derivatives to 8, 3'-di-fluoro-coclaurine. This work highlights the potential of yeast as a versatile microbial biosynthetic platform to strengthen current pharmaceutical supply chain and to advance drug development.

Logic Circuits Based on 2A Peptide Sequences in the Yeast Saccharomyces cerevisiae

Gene digital circuits are the subject of many studies in Synthetic Biology due to their various applications from pollutant detection to medical diagnostics and biocomputing. Complex logic functions are calculated via small genetic components that mimic Boolean gates, i.e., they implement basic logic operations. Gates interact by exchanging proteins or noncoding RNAs. To carry out logic operations in the yeast Saccharomyces cerevisiae, we chose three bacterial repressors commonly used for proofs of concept in Synthetic Biology, namely, TetR, LexA, and LacI. We coexpressed them via synthetic polycistronic cassettes based on 2A peptide sequences. Our initial results highlighted the successful application of four 2A peptides─from Equine rhinitis B virus-1 (ERBV-1 2A), Operophtera brumata cypovirus 18 (OpbuCPV18 2A), Ljungan virus (LV2A), and Thosea asigna virus (T2A)─to the construction of single and two-input Boolean gates. In order to improve protein coexpression, we modified the original 2A peptides with the addition of the glycine-serine-glycine (GSG) prefix or by using two different 2As sequences in tandem. Remarkably, we finally realized a well-working tri-cistronic vector that carried LexA-HBD(hER), TetR, and LacI separated, in the order, by GSG-T2A and ERBV-1 2A. This plasmid led to the implementation of three-input circuits containing AND and OR gates. Taken together, polycistronic constructs simplify the cloning and coexpression of multiple proteins with a dramatic reduction in the complexity of gene digital circuits.

Natural promoters and promoter engineering strategies for metabolic regulation in Saccharomyces cerevisiae

Sharomyces cerevisiae is currently one of the most important foreign gene expression systems. S. cerevisiae is an excellent host for high-value metabolite cell factories due to its advantages of simplicity, safety, and nontoxicity. A promoter, as one of the basic elements of gene transcription, plays an important role in regulating gene expression and optimizing metabolic pathways. Promoters control the direction and intensity of transcription, and the application of promoters with different intensities and performances will largely determine the effect of gene expression and ultimately affect the experimental results. Due to its significant role, there have been many studies on promoters for decades. While some studies have explored and analyzed new promoters with different functions, more studies have focused on artificially modifying promoters to meet their own scientific needs. Thus, this article reviews current research on promoter engineering techniques and related natural promoters in S. cerevisiae. First, we introduce the basic structure of promoters and the classification of natural promoters. Then, the classification of various promoter strategies is reviewed. Finally, by grouping related articles together using various strategies, this review anticipates the future development direction of promoter engineering.

A well-characterized polycistronic-like gene expression system in yeast

Efficient expression of multiple genes is critical to yeast metabolic engineering for the bioproduction of bulk and fine chemicals. A yeast polycistronic expression system is of particular interest because one promoter can drive the expression of multiple genes. 2A viral peptides enable the cotranslation of multiple proteins from a single mRNA by ribosomal skipping. However, the wide adaptation of 2A viral peptides for polycistronic-like gene expression in yeast awaits in-depth characterizations. Additionally, a one-step assembly of such a polycistronic-like system is highly desirable. To this end, we have developed a modular cloning (MoClo) compatible 2A peptide-based polycistronic-like system capable of expressing multiple genes from a single promoter in yeast. Characterizing the bi-, tri-, and quad-cistronic expression of fluorescent proteins showed high cleavage efficiencies of three 2A peptides: E2A from equine rhinitis B virus, P2A from porcine teschovirus-1, and O2A from Operophtera brumata cypovirus-18. Applying the polycistronic-like system to produce geraniol, a valuable industrial compound, resulted in comparable or higher titers than using conventional monocistronic constructs. In summary, this highly-characterized polycistronic-like gene expression system is another tool to facilitate multigene expression for metabolic engineering in yeast.

Employing Engineered Enolase Promoter for Efficient Expression of Thermomyces lanuginosus Lipase in Yarrowia lipolytica via a Self-Excisable Vector

Yarrowia lipolytica is progressively being employed as a workhouse for recombinant protein expression. Here, we expanded the molecular toolbox by engineering the enolase promoter (pENO) and developed a new self-excisable vector, and based on this, a combined strategy was employed to enhance the expression of Thermomyces lanuginosus lipase (TLL) in Y. lipolytica. The strength of 11 truncated enolase promoters of different length was first identified using eGFP as a reporter. Seven of the truncated promoters were selected to examine their ability for driving TLL expression. Then, a series of enolase promoters with higher activities were developed by upstream fusing of different copies of UAS1B, and the recombinant strain Po1f/hp16e₁₀₀-tll harboring the optimal promoter hp16e₁₀₀ obtained a TLL activity of 447 U/mL. Additionally, a new self-excisable vector was developed based on a Cre/loxP recombination system, which achieved efficient markerless integration in Y. lipolytica. Subsequently, strains harboring one to four copies of the tll gene were constructed using this tool, with the three-copy strain Po1f/3tll showing the highest activity of 579 U/mL. The activity of Po1f/3tll was then increased to 720 U/mL by optimizing the shaking flask fermentation parameters. Moreover, the folding-related proteins Hac1, Pdi, and Kar2 were employed to further enhance TLL expression, and the TLL activity of the optimal recombinant strain Po1f/3tll-hac1-pdi-kar2 reached 1197 U/mL. By using this combined strategy, TLL activity was enhanced by approximately 39.9-fold compared to the initial strain. Thus, the new vector and the combined strategy could be a useful tool to engineer Y. lipolytica for high-level expression of heterologous protein.

A Novel Method to Screen Strong Constitutive Promoters in Escherichia coli and Serratia marcescens for Industrial Applications

Promoters serve as the switch of gene transcription, playing an important role in regulating gene expression and metabolites production. However, the approach to screening strong constitutive promoters in microorganisms is still limited. In this study, a novel method was designed to identify strong constitutive promoters in E. coli and S. marcescens based on random genomic interruption and fluorescence-activated cell sorting (FACS) technology. First, genomes of E. coli, Bacillus subtilis, and Corynebacterium glutamicum were randomly interrupted and inserted into the upstream of reporter gene gfp to construct three promoter libraries, and a potential strong constitutive promoter (P_BS) suitable for E. coli was screened via FACS technology. Second, the core promoter sequence (P_BS76) of the screened promoter was identified by sequence truncation. Third, a promoter library of P_BS76 was constructed by installing degenerate bases via chemical synthesis for further improving its strength, and the intensity of the produced promoter P_BS76-100 was 59.56 times higher than that of the promoter P_{BBa_J23118}. Subsequently, promoters P_BBa__J23118, P_BS76, P_BS76-50, P_BS76-75, P_BS76-85, and P_BS76-100 with different strengths were applied to enhance the metabolic flux of L-valine synthesis, and the L-valine yield was significantly improved. Finally, a strong constitutive promoter suitable for S. marcescens was screened by a similar method and applied to enhance prodigiosin production by 34.81%. Taken together, the construction of a promoter library based on random genomic interruption was effective to screen the strong constitutive promoters for fine-tuning gene expression and reprogramming metabolic flux in various microorganisms.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

Construction and Optimization of Malonyl-CoA Sensors in Saccharomyces cerevisiae by Combining Promoter Engineering Strategies

Biosensors can be used for high-throughput screening, real-time monitoring of metabolites, and dynamic regulation of metabolic processes, which have been a popular research direction in recent years. Here, five promoters from Saccharomyces cerevisiae were selected to construct Malonyl-CoA sensors with the fapO/fapR system derived from Bacillus subtilis, and pCCW12 was finally selected for further optimization. Based on pCCW12, a series of sensors with different response sensitivities were obtained by selecting different fapO insertion sites and combining the best two or three of them. Then, through a combination of promoter hybrid, intron insertion, and transcription factor modification strategies, we obtained sensors with different effects, one of which, the H-pCCW12(TFBS)-Cti6~fapR sensor, had the lowest background noise, doubled response range and higher response sensitivity compared to the original sensor. Sensors with different characteristics constructed in this study, can be applied to Malonyl-CoA related high-throughput screening and finer regulation of metabolism. It also proves that the combined application of different promoter engineering strategies is a feasible idea for the precise construction and regulation of biosensors.

A new combinatorial megaplasmid library assembly method designed to screen for minimal pathways by using SCRaMbLE

Human proteins expressed in yeast are common to enhance protein production while the expression of functional human pathways remain challenging. Here, we propose a simple and economical high-throughput gene assembly method to create a yeast megaplasmid library from human cDNA to screen for minimal human functional pathways. We introduced artificial promoters followed by symmetric loxP sites into the megaplasmids using Golden Gate assembly coupled with streptavidin-bead-based purification. The isolated high molecular weight, randomly assembled cDNA megaplasmid library may be useful for high-throughput directed evolution experiments and may be adapted for use in other model organisms.

Applicability of the heterologous yeast promoters for recombinant protein production in Pichia pastoris

Promoter choice is an important step in recombinant protein production, which directly determines the expression manner as constitutive or inducible and the expression level of the recombinant protein. This study aims to investigate the applicability of heterologous yeast promoters (Kluyveromyces marxianus TPI, Hansenula polymorpha PMA, Candida tropicalis ICL, and Saccharomyces cerevisiae CUP) in Pichia pastoris. The regulation mode of the CtICL and ScCUP promoters in P. pastoris was found to be inducible and that of the KmTPI and HpPMA was constitutive. The carbon sources in which the promoters exhibited the highest activity were determined as glycerol for PMA and TPI, glucose for CUP, and ethanol for ICL. The DNA region showing the highest activity was determined as 1000 bp for all promoters by promoter deletion analysis. Results from the study demonstrate the potential of inducible and constitutive heterologous promoters allowing expression under different conditions in the P. pastoris expression system and offers alternatives to frequently used promoters. KEY POINTS: • Heterologous promoters exhibited similar expression pattern in P. pastoris with its native host. • HpPMA has the highest promoter activity among the heterologous promoters tested. • Reporter gene expression with ScCUP is responsive to elevating Cu²⁺in P. pastoris.