Transcriptional regulation based on transcription factors is an effective regulatory method widely used in microbial cell factories. Currently, few naturally transcriptional regulatory elements have been discovered from Saccharomyces cerevisiae and applied. Moreover, the discovered elements cannot meet the demand for specific metabolic regulation of exogenous compounds due to the high background expression or narrow dynamic ranges. There are abundant transcriptional regulatory elements in plants. However, the sequences and functions of most elements have not been fully characterized and optimized. Particularly, the applications of these elements in microbial cell factories are still in the infancy stage. In this study, natural regulatory elements from Medicago truncatula were selected, including the transcription factors MtTASR2 and MtTASR3, along with their associated promoter P_roHMGR1, for functional characterization and engineering modification. We constructed an inducible transcriptional regulation tool and applied it in the regulation of heterologous β-carotene synthesis in S. cerevisiae, which increased the β-carotene production by 7.31 folds compared with the original strain. This study demonstrates that plant-derived transcriptional regulatory elements can be used to regulate the expression of multiple genes in S. cerevisiae, providing new strategies and ideas for the specific regulation and application of these elements in microbial cell factories.
Medicago truncatula/metabolism* ; Saccharomyces cerevisiae/metabolism* ; Transcription Factors/genetics* ; beta Carotene/biosynthesis* ; Promoter Regions, Genetic/genetics* ; Gene Expression Regulation, Plant ; Metabolic Engineering/methods* ; Regulatory Elements, Transcriptional/genetics* ; Plant Proteins/genetics*

Wickerhamomyces ciferrii (W.c), an unconventional heterothallic yeast species, is renowned for its high production of tetraacetyl phytosphingosine (TAPS). Due to its excellent performance in TAPS production, this study aimed to construct a genetic operating system of W.c to enhance the production of TAPS and to screen high-yielding strains by mutagenesis and genetic engineering, thus laying the foundation for further development of industrial production of sphingolipid metabolites. In this study, we selected two autonomous replication elements (CEN, 2μ) and mined 11 endogenous promoter elements to establish a genetic operating system in W. ciferrii. The overexpression of Syr2 and Lcb2 in the sphingolipid metabolism pathway significantly increased the production of TAPS. Meanwhile, we established a method for the identification of haploid mating types of W. ciferrii by combining RT-PCR and flow cytometry. Five strains of W. ciferrii with different mating types constructed from the standard diploid W. ciferrii ATCC 14091 were screened out. A-type haploid W.c 140 showcased the highest production of TAPS with a yield of 4.74 mg/g and a titer of 32.61 mg/L. Mutant strains W.c 140-A9 and W.c 140-A11 were induced by atmospheric pressure room temperature plasma mutagenesis. The recombinant strains W.c 140 OELcb2 and W.c 140 OESyr2 with overexpression were constructed with the genetic operating system established in this study. The TAPS yields of the mutant strains increased by 61.39% and 67.09%, respectively, compared with that of starting strain W.c 140. The recombinant strains cultured in the LCBNB medium achieved yields of 10.60 mg/g and 12.14 mg/g, respectively, representing 2.24 and 2.56 times of that in strain W.c 140. Moreover, the yields of the two recombinant strains were significantly higher than that of the diploid strain ATCC 14091. The genetic operating system and the haploid strain W.c 140 established in this study provide a basis for the subsequent establishment of genetic engineering tools for W. ciferrii.
Sphingosine/genetics* ; Saccharomycetales/metabolism* ; Genetic Engineering/methods* ; Promoter Regions, Genetic ; Metabolic Engineering/methods* ; Fungal Proteins/genetics*

Biosensors have become powerful tools for real-time monitoring of specific small molecules and precise control of gene expression in biological systems. High-throughput sensors for 1, 4-butanediamine biosynthesis can greatly improve the screening efficiency of high-yielding 1, 4-butanediamine strains. However, the strategies for adapting the characteristics of biosensors are still rarely studied, which limits the applicability of 1, 4-butanediamine biosensors. In this paper, we propose the development of a 1, 4-butanediamine biosensor based on the transcriptional regulator PuuR, whose homologous operator puuO is installed in the constitutive promoter P_gapA of Escherichia coli to control the expression of the downstream superfolder green fluorescent protein (sfGFP) as the reporter protein. Finally, the biosensor showed a stable linear relationship between the GFP/OD₆₀₀ value and the concentration of 1, 4-butanediamine when the concentration of 1, 4-butanediamine was 0-50 mmol/L. The promoters with different strengths in the E. coli genome were used to modify the 1, 4-butanediamine biosensor, and the functional properties of the PuuR-based 1, 4-butanediamine biosensor were explored and improved, which laid the groundwork for high-throughput screening of engineered strains highly producing 1, 4-butanediamine.
Biosensing Techniques/methods* ; Escherichia coli/metabolism* ; Promoter Regions, Genetic/genetics* ; Green Fluorescent Proteins/metabolism* ; Transcription Factors/genetics* ; Escherichia coli Proteins/genetics* ; Diamines/metabolism* ; Gene Expression Regulation, Bacterial

Narrow leaf 1 (NAL1) plays an important role in plant branching, while little is known about the roles of this gene in petunias. In this study, PhNAL1b was cloned from Petunia×hybrida cv. Mitchell Diploid, with a total length of 1 767 bp, encoding a protein composed of 588 amino acid residues and containing the peptidase S64 domain. The PhNAL1b promoter region contained several elements involved in the responses to auxin, jasmonic acid, abscisic acid, and light. The expression analysis showed that PhNAL1b had the highest expression level in roots and the lowest expression level in flowers, and its transcription could be inhibited by decapitation and cytokinin. The subcellular localization analysis showed that PhNAL1b was located in the nucleus and was a nuclear protein. Virus-induced gene silencing was employed to downregulate the expression of PhNAL1b, which resulted in significant increases in branch number and plant height. The results indicated that PhNAL1b played an important role in regulating the branching of petunias. This study lays a foundation for revealing the mechanism of NAL1 in regulating branch development and provides genetic resources for plant architecture improvement.
Petunia/growth & development* ; Plant Proteins/metabolism* ; Diploidy ; Gene Expression Regulation, Plant ; Cloning, Molecular ; Promoter Regions, Genetic

Nucleic acid elements are essential functional sequences that play critical roles in regulating gene expression, optimizing pathways, and enabling gene editing to enhance the production of target products in biomanufacturing. Therefore, the design and optimization of these elements are crucial in constructing efficient cell factories. Artificial intelligence (AI) provides robust support for biomanufacturing by accurately predicting functional nucleic acid elements, designing and optimizing sequences with quantified functions, and elucidating the operating mechanisms of these elements. In recent years, AI has significantly accelerated the progress in biomanufacturing by reducing experimental workloads through the design and optimization of promoters, ribosome-binding sites, terminators, and their combinations. Despite these advancements, the application of AI in biomanufacturing remains limited due to the complexity of biological systems and the lack of highly quantified training data. This review summarizes the various nucleic acid elements utilized in biomanufacturing, the tools developed for predicting and designing these elements based on AI algorithms, and the case studies showcasing the applications of AI in biomanufacturing. By integrating AI with synthetic biology and high-throughput techniques, we anticipate the development of more efficient tools for designing nucleic acid elements and accelerating the application of AI in biomanufacturing.
Artificial Intelligence ; Synthetic Biology ; Nucleic Acids/genetics* ; Algorithms ; Gene Editing ; Promoter Regions, Genetic ; Biotechnology/methods*

In this study, high-throughput promoter screening was employed to optimize the heterologous expression of Mesorhizobium loti carbonic anhydrase (MlCA) in order to reduce the costs associated with carbon capture and storage (CCS). To simplify the complexity of traditional vectors, a fusion protein expression system was constructed using superfolder green fluorescent protein (sfGFP) and MlCA. The synthetic promoter library in Escherichia coli was utilized for efficient one-step screening. Based on fluorescence intensity on agar plates, a total of 143 monoclonal colonies were identified, forming a library with varying expression levels. The top four recombinants with the highest fluorescence intensity were selected, among which MlCA driven by the promoter 342042/+ exhibited the highest enzymatic activity, with a specific activity of the 34.6 Wilbur-Anderson units (WAU)/mg. Optimization experiments revealed that MlCA exhibited the best performance when cultured for 4 days under pH 7.0 and 40 ℃ conditions. The Michaelis constant (K_m·hdy) and maximum reaction rate (V_max·hdy) for CO₂ hydration were determined to be 62.46 mmol/L and 0.164 mmol/(s·L), respectively. For esterase hydrolysis, MlCA showed the K_m and V_max of 639.8 mmol/L and 0.035 mmol/(s·L), respectively. MlCA accelerated the CO₂ hydration process, promoting CO₂ mineralized into CaCO₃ within 9 min at low pH and room temperature conditions. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses confirmed that the precipitated product was calcite. This study provides a low-cost and environmentally friendly alternative for future CCS applications.
Carbonic Anhydrases/biosynthesis* ; Promoter Regions, Genetic/genetics* ; Escherichia coli/metabolism* ; Carbon Sequestration ; Carbon Dioxide/metabolism* ; Green Fluorescent Proteins/metabolism*

Flowering and bolting are important agronomic traits in cruciferous crops such as Brassica juncea. Timely flowering can ensure the crop organ yield and quality, as well as seed propagation. The WRKY family plays an important role in regulating plant bolting and flowering, while the function and mechanism of WRKY12 in B. juncea remain unknown. To explore its function and mechanism in bolting and flowering of B. juncea, we cloned and characterized the BjuWRKY12 gene in B. juncea and found that its expression levels were significantly higher in flowers and inflorescences than in leaves. BjuWRKY12 belonged to the Ⅱc subfamily of the WRKY family, and subcellular localization indicated that the protein was located in the nucleus. Ectopic overexpression of BjuWRKY12 in transgenic lines promoted bolting and flowering, leading to significant increases in the expression levels of flowering integrators SOC1 and FUL. Furthermore, yeast one-hybrid and dual luciferase reporter system assays confirmed that BjuWRKY12 directly bound to the promoters of BjuSOC1 and BjuFUL, undergoing protein-DNA interactions. This discovery gives new insights into the regulation network and molecular mechanisms of BjuWRKY12, laying a theoretical foundation for the breeding of high-yield and high-quality varieties of B. juncea.
Mustard Plant/metabolism* ; Flowers/growth & development* ; Plant Proteins/physiology* ; Promoter Regions, Genetic/genetics* ; Gene Expression Regulation, Plant ; Plants, Genetically Modified/genetics* ; Transcription Factors/metabolism* ; MADS Domain Proteins/metabolism*

The PIF7 gene is a member of the bHLH family, playing a pivotal role in plant germination. However, its roles in tea plants (Camellia sinensis) remain largely unexplored. In this study, we cloned the phytochrome-interacting factor gene CsPIF7 to elucidate its role in the germination of tea plants. Subcellular localization analysis demonstrated that CsPIF7 was localized in the nucleus. Yeast one-hybrid and dual-luciferase reporter assays demonstrated that CsPIF7 directly bound to a specific region (7-321 bp) of the CsEXP promoter, thereby repressing the expression of CsEXP. These findings suggest that CsPIF7 may modulate the germination of tea plants by inhibiting the expression of CsEXP. Quantitative real-time PCR results showed that both CsPIF7 and CsEXP exhibited high expression levels in tea buds, with different expression patterns in response to abscisic acid (ABA) treatment. Furthermore, both CsPIF7 and CsEXP were upregulated under cold stress at 4 ℃, indicating their involvement in the cold response of tea plants. Taken together, these results suggest that CsPIF7 regulates CsEXP expression in an ABA-dependent manner, thereby influencing the germination of tea plants. This study provides both theoretical and experimental insights into the molecular mechanisms governing the germination of tea plants, laying the groundwork for further exploring the role of PIF7 in plant development and stress responses.
Camellia sinensis/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Abscisic Acid/pharmacology* ; Germination/genetics* ; Basic Helix-Loop-Helix Transcription Factors/metabolism* ; Promoter Regions, Genetic ; Cold Temperature

To construct stress-responsive promoters, we mined the transcriptome data of the industrial strain A223 under stress. The transcription factor CIN5 showed significantly increased expression under stress but exhibited limited resistance. Further analysis of CIN5-interacting genes revealed that the binding motif "TTACGTAATC" (named CIN5BS) of CIN5 displayed transcription-enhancing activity. Four artificially enhanced promoters TCIN5B(3-6) were created by insertion of CIN5BS as a cis-element into different sites of the promoter TEF1, achieving 15.25-fold transcriptional enhancement. Five cis-elements (CIN5B4-1-CIN5B4-5) were designed through G+C content optimization, generating five stronger artificially enhanced promoters (TCIN5B4-1-TCIN5B4-5). For example, TCIN5B4-1 demonstrated 4.71 times higher transcriptional activity than the control at 37 ℃. This study established a technical framework of transcription factor mining-cis-element design-promoter reconstruction, providing a reference strategy for yeast cell factories to stably produce natural compounds under high-temperature stress conditions.
Promoter Regions, Genetic/genetics* ; Transcription Factors/genetics* ; Saccharomyces cerevisiae/metabolism* ; Stress, Physiological/genetics* ; Saccharomyces cerevisiae Proteins/genetics*

Synthetic promoters are novel promoters artificially designed and do not exist in nature. They can initiate the expression of target genes with specific regulatory modes, offering advantages such as high expression efficiency, precise regulation, and modularity. These features endow synthetic promoters with significant application potential in fields such as industrial production, environmental monitoring, and disease diagnosis and treatment. This paper reviews the basic structures, functions, and classification of promoters, discusses various regulatory elements that influence promoter functions, including enhancers, signal response elements, and transcription factors. Additionally, the conventional and deep learning-based strategies for designing synthetic promoters are summarized. Finally, the theoretical significance of synthetic promoters is emphasized, which is followed by an overview of their current applications, along with a rational discussion on the challenges and future development directions of synthetic promoters. Given the critical role of promoters in gene regulation, this article provides a review and outlook on the research progress of synthetic promoters, which holds reference value for the design of cellular gene circuits.
Promoter Regions, Genetic/genetics* ; Transcription Factors/genetics* ; Synthetic Biology/methods* ; Gene Expression Regulation ; Humans ; Deep Learning