Advances in promoter engineering: novel applications and predefined transcriptional control

Generating information-dense promoter sequences with optimal string packing

Dense arrangements of binding sites within nucleotide sequences can collectively influence downstream transcription rates or initiate biomolecular interactions. For example, natural promoter regions can harbor many overlapping transcription factor binding sites that influence the rate of transcription initiation. Despite the prevalence of overlapping binding sites in nature, rapid design of nucleotide sequences with many overlapping sites remains a challenge. Here, we show that this is an NP-hard problem, coined here as the nucleotide String Packing Problem (SPP). We then introduce a computational technique that efficiently assembles sets of DNA-protein binding sites into dense, contiguous stretches of double-stranded DNA. For the efficient design of nucleotide sequences spanning hundreds of base pairs, we reduce the SPP to an Orienteering Problem with integer distances, and then leverage modern integer linear programming solvers. Our method optimally packs sets of 20-100 binding sites into dense nucleotide arrays of 50-300 base pairs in 0.05-10 seconds. Unlike approximation algorithms or meta-heuristics, our approach finds provably optimal solutions. We demonstrate how our method can generate large sets of diverse sequences suitable for library generation, where the frequency of binding site usage across the returned sequences can be controlled by modulating the objective function. As an example, we then show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The nucleotide string packing approach we present can accelerate the design of sequences with complex DNA-protein interactions. When used in combination with synthesis and high-throughput screening, this design strategy could help interrogate how complex binding site arrangements impact either gene expression or biomolecular mechanisms in varied cellular contexts.

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.

Recent Advances in Metabolic Engineering for the Biosynthesis of Phosphoenol Pyruvate-Oxaloacetate-Pyruvate-Derived Amino Acids

The phosphoenol pyruvate-oxaloacetate-pyruvate-derived amino acids (POP-AAs) comprise native intermediates in cellular metabolism, within which the phosphoenol pyruvate-oxaloacetate-pyruvate (POP) node is the switch point among the major metabolic pathways existing in most living organisms. POP-AAs have widespread applications in the nutrition, food, and pharmaceutical industries. These amino acids have been predominantly produced in Escherichia coli and Corynebacterium glutamicum through microbial fermentation. With the rapid increase in market requirements, along with the global food shortage situation, the industrial production capacity of these two bacteria has encountered two bottlenecks: low product conversion efficiency and high cost of raw materials. Aiming to push forward the update and upgrade of engineered strains with higher yield and productivity, this paper presents a comprehensive summarization of the fundamental strategy of metabolic engineering techniques around phosphoenol pyruvate-oxaloacetate-pyruvate node for POP-AA production, including L-tryptophan, L-tyrosine, L-phenylalanine, L-valine, L-lysine, L-threonine, and L-isoleucine. Novel heterologous routes and regulation methods regarding the carbon flux redistribution in the POP node and the formation of amino acids should be taken into consideration to improve POP-AA production to approach maximum theoretical values. Furthermore, an outlook for future strategies of low-cost feedstock and energy utilization for developing amino acid overproducers is proposed.

Metabolic Engineering of Corynebacterium glutamicum for the Production of Flavonoids and Stilbenoids

Flavonoids and stilbenoids, crucial secondary metabolites abundant in plants and fungi, display diverse biological and pharmaceutical activities, including potent antioxidant, anti-inflammatory, and antimicrobial effects. However, conventional production methods, such as chemical synthesis and plant extraction, face challenges in sustainability and yield. Hence, there is a notable shift towards biological production using microorganisms like Escherichia coli and yeast. Yet, the drawbacks of using E. coli and yeast as hosts for these compounds persist. For instance, yeast's complex glycosylation profile can lead to intricate protein production scenarios, including hyperglycosylation issues. Consequently, Corynebacterium glutamicum emerges as a promising alternative, given its adaptability and recent advances in metabolic engineering. Although extensively used in biotechnological applications, the potential production of flavonoid and stilbenoid in engineered C. glutamicum remains largely untapped compared to E. coli. This review explores the potential of metabolic engineering in C. glutamicum for biosynthesis, highlighting its versatility as a cell factory and assessing optimization strategies for these pathways. Additionally, various metabolic engineering methods, including genomic editing and biosensors, and cofactor regeneration are evaluated, with a focus on C. glutamicum. Through comprehensive discussion, the review offers insights into future perspectives in production, aiding researchers and industry professionals in the field.

Computationally guided AAV engineering for enhanced gene delivery

Gene delivery vehicles based on adeno-associated viruses (AAVs) are enabling increasing success in human clinical trials, and they offer the promise of treating a broad spectrum of both genetic and non-genetic disorders. However, delivery efficiency and targeting must be improved to enable safe and effective therapies. In recent years, considerable effort has been invested in creating AAV variants with improved delivery, and computational approaches have been increasingly harnessed for AAV engineering. In this review, we discuss how computationally designed AAV libraries are enabling directed evolution. Specifically, we highlight approaches that harness sequences outputted by next-generation sequencing (NGS) coupled with machine learning (ML) to generate new functional AAV capsids and related regulatory elements, pushing the frontier of what vector engineering and gene therapy may achieve.

Enhancement of the d-Allulose 3-Epimerase Expression in Bacillus subtilis through Both Transcriptional and Translational Regulations

d-Allulose, a functional bulk sweetener, has recently attracted increasing attention because of its low-caloric-ness properties and diverse health effects. d-Allulose is industrially produced by the enzymatic epimerization of d-fructose, which is catalyzed by ketose 3-epimerase (KEase). In this study, the food-grade expression of KEase was studied using Bacillus subtills as the host. Clostridium sp. d-allulose 3-epimerase (Clsp-DAEase) was screened from nine d-allulose-producing KEases, showing better potential for expression in B. subtills WB600. Promoter-based transcriptional regulation and N-terminal coding sequence (NCS)-based translational regulation were studied to enhance the DAEase expression level. In addition, the synergistic effect of promoter and NCS on the Clsp-DAEase expression was studied. Finally, the strain with the combination of a PHapII promoter and gln A-Up NCS was selected as the best Clsp-DAEase-producing strain. It efficiently produced Clsp-DAEase with a total activity of 333.2 and 1860.6 U/mL by shake-flask and fed-batch cultivations, respectively.

Transcriptome analysis of Kluyveromyces marxianus under succinic acid stress and development of robust strains

Kluyveromyces marxianus has become an attractive non-conventional yeast cell factory due to its advantageous properties such as high thermal tolerance and rapid growth. Succinic acid (SA) is an important platform molecule that has been applied in various industries such as food, material, cosmetics, and pharmaceuticals. SA bioproduction may be compromised by its toxicity. Besides, metabolite-responsive promoters are known to be important for dynamic control of gene transcription. Therefore, studies on global gene transcription under various SA concentrations are of great importance. Here, comparative transcriptome changes of K. marxianus exposed to various concentrations of SA were analyzed. Enrichment and analysis of gene clusters revealed repression of the tricarboxylic acid cycle and glyoxylate cycle, also activation of the glycolysis pathway and genes related to ergosterol synthesis. Based on the analyses, potential SA-responsive promoters were investigated, among which the promoter strength of IMTCP2 and KLMA_50231 increased 43.4% and 154.7% in response to 15 g/L SA. In addition, overexpression of the transcription factors Gcr1, Upc2, and Ndt80 significantly increased growth under SA stress. Our results benefit understanding SA toxicity mechanisms and the development of robust yeast for organic acid production. KEY POINTS: • Global gene transcription of K. marxianus is changed by succinic acid (SA) • Promoter activities of IMTCP2 and KLMA_50123 are regulated by SA • Overexpression of Gcr1, Upc2, and Ndt80 enhanced SA tolerance.

Synthetic transcription factor engineering for cell and gene therapy

Synthetic transcription factors (synTFs) that control beneficial transgene expression are an important method to increase the safety and efficacy of cell and gene therapy. Reliance on synTF components from non-human sources has slowed progress in the field because of concerns about immunogenicity and inducer drug properties. Recent advances in human-derived DNA-binding domains (DBDs) and transcriptional activation domains (TADs) paired with novel control modules responsive to clinically approved small molecules have poised the synTF field to overcome these hurdles. Advances include controllers inducible by autonomous signaling inputs and more complex, multi-input synTF circuits. Demonstrations of advanced control strategies with human-derived transcription factor components in clinically relevant vectors and in vivo models will facilitate progression into the clinic.

Model-guided metabolic rewiring to bypass pyruvate oxidation for pyruvate derivative synthesis by minimizing carbon loss

Engineering microbial hosts to synthesize pyruvate derivatives depends on blocking pyruvate oxidation, thereby causing severe growth defects in aerobic glucose-based bioprocesses. To decouple pyruvate metabolism from cell growth to improve pyruvate availability, a genome-scale metabolic model combined with constraint-based flux balance analysis, geometric flux balance analysis, and flux variable analysis was used to identify genetic targets for strain design. Using translation elements from a ~3,000 cistronic library to modulate fxpK expression in a bicistronic cassette, a bifido shunt pathway was introduced to generate three molecules of non-pyruvate-derived acetyl-CoA from one molecule of glucose, bypassing pyruvate oxidation and carbon dioxide generation. The dynamic control of flux distribution by T7 RNAP-mediated synthetic small RNA decoupled pyruvate catabolism from cell growth. Adaptive laboratory evolution and multi-omics analysis revealed that a mutated isocitrate dehydrogenase functioned as a metabolic switch to activate the glyoxylate shunt as the only C4 anaplerotic pathway to generate malate from two molecules of acetyl-CoA input and bypass two decarboxylation reactions in the tricarboxylic acid cycle. A chassis strain for pyruvate derivative synthesis was constructed to reduce carbon loss by using the glyoxylate shunt as the only C4 anaplerotic pathway and the bifido shunt as a non-pyruvate-derived acetyl-CoA synthetic pathway and produced 22.46, 27.62, and 6.28 g/L of l-leucine, l-alanine, and l-valine by a controlled small RNA switch, respectively. Our study establishes a novel metabolic pattern of glucose-grown bacteria to minimize carbon loss under aerobic conditions and provides valuable insights into cell design for manufacturing pyruvate-derived products.IMPORTANCEBio-manufacturing from biomass-derived carbon sources using microbes as a cell factory provides an eco-friendly alternative to petrochemical-based processes. Pyruvate serves as a crucial building block for the biosynthesis of industrial chemicals; however, it is different to improve pyruvate availability in vivo due to the coupling of pyruvate-derived acetyl-CoA with microbial growth and energy metabolism via the oxidative tricarboxylic acid cycle. A genome-scale metabolic model combined with three algorithm analyses was used for strain design. Carbon metabolism was reprogrammed using two genetic control tools to fine-tune gene expression. Adaptive laboratory evolution and multi-omics analysis screened the growth-related regulatory targets beyond rational design. A novel metabolic pattern of glucose-grown bacteria is established to maintain growth fitness and minimize carbon loss under aerobic conditions for the synthesis of pyruvate-derived products. This study provides valuable insights into the design of a microbial cell factory for synthetic biology to produce industrial bio-products of interest.

Engineering and application of LacI mutants with stringent expressions

Optimal transcriptional regulatory circuits are expected to exhibit stringent control, maintaining silence in the absence of inducers while exhibiting a broad induction dynamic range upon the addition of effectors. In the Plac /LacI pair, the promoter of the lac operon in Escherichia coli is characterized by its leakiness, attributed to the moderate affinity of LacI for its operator target. In response to this limitation, the LacI regulatory protein underwent engineering to enhance its regulatory properties. The M7 mutant, carrying I79T and N246S mutations, resulted in the lac promoter displaying approximately 95% less leaky expression and a broader induction dynamic range compared to the wild-type LacI. An in-depth analysis of each mutation revealed distinct regulatory profiles. In contrast to the wild-type LacI, the M7 mutant exhibited a tighter binding to the operator sequence, as evidenced by surface plasmon resonance studies. Leveraging the capabilities of the M7 mutant, a high-value sugar biosensor was constructed. This biosensor facilitated the selection of mutant galactosidases with approximately a seven-fold improvement in specific activity for transgalactosylation. Consequently, this advancement enabled enhanced biosynthesis of galacto-oligosaccharides (GOS).

Sustainable valorizing high-protein feather waste utilization through solid-state fermentation by keratinase-enhanced Streptomyces sp. SCUT-3 using a novel promoter

Feather waste, a rich source of proteins, has traditionally been processed through high-temperature puffing and acid-base hydrolysis, contributing to generation of greenhouse gases and H2S. To address this issue, we employed circular economy techniques to recover the nutritional value of feather waste. Streptomyces sp. SCUT-3, an efficient proteolytic and chitinolytic bacterium, was isolated for feather degradation previously. This study aimed to valorize feather waste for feed purposes by enhancing its feather transformation ability through promoter optimization. Seven promoters were identified through omics analysis and compared to a common Streptomyces promoter ermE*p. The strongest promoter, p24880, effectively enhanced the expression of three candidate keratinases (Sep39, Sep40, and Sep53). The expression efficiency of double-, triple-p24880 and sandwich p24880-sep39-p24880 promoters were further verified. The co-overexpression strain SCUT-3-p24880-sep39-p24880-sep40 exhibited a 16.21-fold increase in keratinase activity compared to the wild-type. Using this strain, a solid-state fermentation process was established that increased the feather/water ratio (w/w) to 1:1.5, shortened the fermentation time to 2.5 days, and increased soluble peptide and free amino acid yields to 0.41 g/g and 0.14 g/g, respectively. The resulting has high protein content (90.49 %), with high in vitro digestibility (94.20 %). This method has the potential to revolutionize the feather waste processing industry.

Generating information-dense promoter sequences with optimal string packing

Dense arrangements of binding sites within nucleotide sequences can collectively influence downstream transcription rates or initiate biomolecular interactions. For example, natural promoter regions can harbor many overlapping transcription factor binding sites that influence the rate of transcription initiation. Despite the prevalence of overlapping binding sites in nature, rapid design of nucleotide sequences with many overlapping sites remains a challenge. Here, we show that this is an NP-hard problem, coined here as the nucleotide String Packing Problem (SPP). We then introduce a computational technique that efficiently assembles sets of DNA-protein binding sites into dense, contiguous stretches of double-stranded DNA. For the efficient design of nucleotide sequences spanning hundreds of base pairs, we reduce the SPP to an Orienteering Problem with integer distances, and then leverage modern integer linear programming solvers. Our method optimally packs libraries of 20-100 binding sites into dense nucleotide arrays of 50-300 base pairs in 0.05-10 seconds. Unlike approximation algorithms or meta-heuristics, our approach finds provably optimal solutions. We demonstrate how our method can generate large sets of diverse sequences suitable for library generation, where the frequency of binding site usage across the returned sequences can be controlled by modulating the objective function. As an example, we then show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The nucleotide string packing approach we present can accelerate the design of sequences with complex DNA-protein interactions. When used in combination with synthesis and high-throughput screening, this design strategy could help interrogate how complex binding site arrangements impact either gene expression or biomolecular mechanisms in varied cellular contexts.

Author Summary

The way protein binding sites are arranged on DNA can control the regulation and transcription of downstream genes. Areas with a high concentration of binding sites can enable complex interplay between transcription factors, a feature that is exploited by natural promoters. However, designing synthetic promoters that contain dense arrangements of binding sites is a challenge. The task involves overlapping many binding sites, each typically about 10 nucleotides long, within a constrained sequence area, which becomes increasingly difficult as sequence length decreases, and binding site variety increases. We introduce an approach to design nucleotide sequences with optimally packed protein binding sites, which we call the nucleotide String Packing Problem (SPP). We show that the SPP can be solved efficiently using integer linear programming to identify the densest arrangements of binding sites for a specified sequence length. We show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The presented approach enables the rapid design and study of nucleotide sequences with complex, dense binding site architectures.

Highly efficient production of rhamnolipid in P. putida using a novel sacB-based system and mixed carbon source

Pseudomonas putida KT2440, a GRAS strain, has been used for synthesizing bulk and fine chemicals. However, the gene editing tool to metabolically engineer KT2440 showed low efficiency. In this study, a novel sacB-based system pK51mobsacB was established to improve the efficiency for marker-free gene disruption. Then the rhamnolipid synthetic pathway was introduced in KT2440 and genes of the competitive pathways were deleted to lower the metabolic burden based on pK51mobsacB. A series of endogenous and synthetic promoters were used for fine tuning rhlAB expression. The limited supply of dTDP-L-rhamnose was enhanced by heterologous rmlBDAC expression. Cell growth and rhamnolipid production were well balanced by using glucose/glycerol as mixed carbon sources. The final strain produced 3.64 g/L at shake-flask and 19.77 g/L rhamnolipid in a 5 L fermenter, the highest obtained among metabolically engineered KT2440, which implied the potential of KT2440 as a promising microbial cell factory for industrial rhamnolipid production.

Engineering CREB-activated promoters for adenosine-induced gene expression

Accumulation of the ribonucleoside, adenosine (ADO), triggers a cAMP response element binding protein (CREB)-mediated signaling pathway to suppress the function of immune cells in tumors. Here, we describe a collection of CREB-activated promoters that allow for strong and tunable ADO-induced gene expression in human cells. By optimizing number of CREB transcription factor binding sites and altering the core promoter region of CREB-based hybrid promoters, we created synthetic constructs that drive gene expression to higher levels than strong, endogenous mammalian promoters in the presence of ADO. These synthetic promoters are induced up to 47-fold by ADO, with minimal expression in their "off" state. We further determine that our CREB-based promoters are activated by other compounds that act as signaling analogs, and that combinatorial addition of ADO and these compounds has a synergistic impact on gene expression. Surprisingly, we also detail how background ADO degradation caused by the common cell culture media additive, fetal bovine serum (FBS), confounds experiments designed to determine ADO dose-responsiveness. We show that only after long-term heat deactivation of FBS can our synthetic promoters enable gene expression induction at physiologically relevant levels of ADO. Finally, we demonstrate that the strength of a CREB-based promoter is enhanced by incorporating other transcription factor binding sites.

Expanding the genetic programmability of Lactiplantibacillus plantarum

Lactobacilli are ubiquitous in nature and symbiotically provide health benefits for countless organisms including humans, animals and plants. They are vital for the fermented food industry and are being extensively explored for healthcare applications. For all these reasons, there is considerable interest in enhancing and controlling their capabilities through the engineering of genetic modules and circuits. One of the most robust and reliable microbial chassis for these synthetic biology applications is the widely used Lactiplantibacillus plantarum species. However, the genetic toolkit needed to advance its applicability remains poorly equipped. This mini-review highlights the genetic parts that have been discovered to achieve food-grade recombinant protein production and speculates on lessons learned from these studies for L. plantarum engineering. Furthermore, strategies to identify, create and optimize genetic parts for real-time regulation of gene expression and enhancement of biosafety are also suggested.

Available strategies for improving the biosynthesis of surfactin: a review

Surfactin is an excellent biosurfactant with a wide range of application prospects in many industrial fields. However, its low productivity and high cost have largely limited its commercial applications. In this review, the pathways for surfactin synthesis in Bacillus strains are summarized and discussed. Further, the latest strategies for improving surfactin production, including: medium optimization, genome engineering methods (rational genetic engineering, genome reduction, and genome shuffling), heterologous synthesis, and the use of synthetic biology combined with metabolic engineering approaches to construct high-quality artificial cells for surfactin production using xylose, are described. Finally, the prospects for improving surfactin synthesis are discussed in detail.

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.

Deep flanking sequence engineering for efficient promoter design using DeepSEED

Designing promoters with desirable properties is essential in synthetic biology. Human experts are skilled at identifying strong explicit patterns in small samples, while deep learning models excel at detecting implicit weak patterns in large datasets. Biologists have described the sequence patterns of promoters via transcription factor binding sites (TFBSs). However, the flanking sequences of cis-regulatory elements, have long been overlooked and often arbitrarily decided in promoter design. To address this limitation, we introduce DeepSEED, an AI-aided framework that efficiently designs synthetic promoters by combining expert knowledge with deep learning techniques. DeepSEED has demonstrated success in improving the properties of Escherichia coli constitutive, IPTG-inducible, and mammalian cell doxycycline (Dox)-inducible promoters. Furthermore, our results show that DeepSEED captures the implicit features in flanking sequences, such as k-mer frequencies and DNA shape features, which are crucial for determining promoter properties.

Post-transcriptional and translational regulation of plant gene expression by transposons

Transposons are mobile DNA sequences that can move within the genome and integrate in new genomic locations. They are widespread in eukaryotes and prokaryotes and can influence gene expression when landing within or nearby a gene. Although transposon-induced regulation of gene expression at the transcriptional level has been extensively studied, there has been less focus on regulation at the post-transcriptional and translational levels. Recent studies in maize (Zea mays) and other plant species suggest that transposon insertions can affect RNA processing, RNA stability, protein translation and protein stability. We will describe the diverse mechanisms by which transposons can influence gene expression at the post-transcriptional and translational levels, and discuss the interactions between these mechanisms.

Regulation of transcriptome networks that mediate ginsenoside biosynthesis by essential ecological factors

Ginseng, a valuable Chinese medicinal herb, is renowned worldwide for its effectiveness in alleviating certain conditions and promoting overall health. In this study, we performed weighted gene co-expression network analysis (WGCNA) on the accumulation of essential saponins under the influence of 13 essential environmental factors (including air temperature, air bottom temperature, surface mean temperature, soil temperature, surface shortwave radiation, soil moisture, soil water content, rainfall, total precipitation, elevation, soil type, soil pH, and soil water potential). We identified a total of 40 transcript modules associated with typical environmental factors and the accumulation of essential saponins. Among these, 18 modules were closely related to the influence of typical environmental factors, whereas 22 modules were closely related to the accumulation of essential saponins. These results were verified by examining the transcriptome, saponin contents, environmental factor information and the published data and revealed the regulatory basis of saponin accumulation at the transcriptome level under the influence of essential environmental factors. We proposed a working model of saponin accumulation mediated by the transcriptional regulatory network that is affected by typical environmental factors. An isomorphic white-box neural network was constructed based on this model and the predicted results of the white-box neural network correlated with saponin accumulation. The effectiveness of our correlation-directed graph in predicting saponin contents was verified by bioinformatics analysis based on results obtained in this study and transcripts known to affect the biosynthesis of saponin Rb1. The directed graph represents a useful tool for manipulating saponin biosynthesis while considering the influence of essential environmental factors in ginseng and other medicinal plants.

An Efficient Prephenate Dehydrogenase Gene for the Biosynthesis of L-tyrosine: Gene Mining, Sequence Analysis, and Expression Optimization

L-tyrosine is a key precursor for synthesis of various functional substances, but the microbial production of L-tyrosine faces huge challenges. The development of new microbial chassis cell and gene resource is especially important for the biosynthesis of L-tyrosine. In this study, the optimal host strain Bacillus amyloliquefaciens HZ-12 was firstly selected by detecting the production capacity of L-tyrosine. Subsequently, the recombinant expression of 15 prephenate dehydrogenase genes led to the discovery of the best gene, Bao-tyrA from B. amyloliquefaciens HZ-12. After the overexpression of Bao-tyrA, the L-tyrosine yield of the recombinant strain HZ/P43-Bao-tyrA reach 411 mg/L, increased by 42% compared with the control strain (HZ/pHY300PLK). Moreover, the nucleic acid sequence and deduced amino acid sequence of the gene Bao-tyrA were analyzed, and their conservative sites and catalytic mechanisms were proposed. Finally, the expression of Bao-tyrA was regulated through a promoter and 5'-UTR sequence to obtain the optimal expression elements. Thereby, the maximum L-tyrosine yield of 475 mg/L was obtained from HZ/P43-UTR3-Bao-tyrA. B. amyloliquefaciens was applied for the first time to produce L-tyrosine, and the optimal prephenate dehydrogenase gene Bao-tyrA and corresponding expression elements were obtained. This study provides new microbial host and gene resource for the construction of efficient L-tyrosine chassis cells, and also lays a solid foundation for the production of various functional tyrosine derivatives.

Hosts engineering and in vitro enzymatic synthesis for the discovery of novel natural products and their derivatives

Novel natural products (NPs) and their derivatives are important sources for drug discovery, which have been broadly applied in the fields of agriculture, livestock, and medicine, making the synthesis of NPs and their derivatives necessarily important. In recent years, biosynthesis technology has received increasing attention due to its high efficiency in the synthesis of high value-added novel products and its advantages of green, environmental protection, and controllability. In this review, the technological advances of biosynthesis strategies in the discovery of novel NPs and their derivatives are outlined, with an emphasis on two areas of host engineering and in vitro enzymatic synthesis. In terms of hosts engineering, multiple microorganisms, including Streptomyces, Aspergillus, and Penicillium, have been used as the biosynthetic gene clusters (BGCs) provider and host strain for the expression of BGCs to discover new compounds over the past years. In addition, the use of in vitro enzymatic synthesis strategy to generate novel compounds such as triterpenoid saponins and flavonoids is also hereby described.

EVMP: enhancing machine learning models for synthetic promoter strength prediction by Extended Vision Mutant Priority framework

Introduction

In metabolic engineering and synthetic biology applications, promoters with appropriate strengths are critical. However, it is time-consuming and laborious to annotate promoter strength by experiments. Nowadays, constructing mutation-based synthetic promoter libraries that span multiple orders of magnitude of promoter strength is receiving increasing attention. A number of machine learning (ML) methods are applied to synthetic promoter strength prediction, but existing models are limited by the excessive proximity between synthetic promoters.

Methods

In order to enhance ML models to better predict the synthetic promoter strength, we propose EVMP(Extended Vision Mutant Priority), a universal framework which utilize mutation information more effectively. In EVMP, synthetic promoters are equivalently transformed into base promoter and corresponding k-mer mutations, which are input into BaseEncoder and VarEncoder, respectively. EVMP also provides optional data augmentation, which generates multiple copies of the data by selecting different base promoters for the same synthetic promoter.

Results

In Trc synthetic promoter library, EVMP was applied to multiple ML models and the model effect was enhanced to varying extents, up to 61.30% (MAE), while the SOTA(state-of-the-art) record was improved by 15.25% (MAE) and 4.03% (R²). Data augmentation based on multiple base promoters further improved the model performance by 17.95% (MAE) and 7.25% (R²) compared with non-EVMP SOTA record.

Discussion

In further study, extended vision (or k-mer) is shown to be essential for EVMP. We also found that EVMP can alleviate the over-smoothing phenomenon, which may contributes to its effectiveness. Our work suggests that EVMP can highlight the mutation information of synthetic promoters and significantly improve the prediction accuracy of strength. The source code is publicly available on GitHub: https://github.com/Tiny-Snow/EVMP.

Transcriptional bursting: stochasticity in deterministic development

The transcription of DNA by RNA polymerase occurs as a discontinuous process described as transcriptional bursting. This bursting behavior is observed across species and has been quantified using various stochastic modeling approaches. There is a large body of evidence that suggests the bursts are actively modulated by transcriptional machinery and play a role in regulating developmental processes. Under a commonly used two-state model of transcription, various enhancer-, promoter- and chromatin microenvironment-associated features are found to differentially influence the size and frequency of bursting events - key parameters of the two-state model. Advancement of modeling and analysis tools has revealed that the simple two-state model and associated parameters may not sufficiently characterize the complex relationship between these features. The majority of experimental and modeling findings support the view of bursting as an evolutionarily conserved transcriptional control feature rather than an unintended byproduct of the transcription process. Stochastic transcriptional patterns contribute to enhanced cellular fitness and execution of proper development programs, which posit this mode of transcription as an important feature in developmental gene regulation. In this Review, we present compelling examples of the role of transcriptional bursting in development and explore the question of how stochastic transcription leads to deterministic organism development.

Design and application of artificial rare L-lysine codons in Corynebacterium glutamicum

Background: L-lysine is widely used in the feed, food, and pharmaceutical industries, and screening for high L-lysine-producing strains has become a key goal for the industry. Methods: We constructed the rare L-lysine codon AAA by corresponding tRNA promoter replacement in C. glutamicum. Additionally, a screening marker related to the intracellular L-lysine content was constructed by converting all L-lysine codons of enhanced green fluorescent protein (EGFP) into the artificial rare codon AAA. The artificial EGFP was then ligated into pEC-XK99E and transformed into competent Corynebacterium glutamicum 23604 cells with the rare L-lysine codon. After atmospheric and room-temperature plasma mutation and induction culture, 55 mutants (0.01% of total cells) with stronger fluorescence were sorted using flow cytometry, and further screened by fermentation in a 96-deep-well plate and 500 mL shaker. Results: The fermentation results showed that the L-lysine production was increased by up to 9.7% in the mutant strains with higher fluorescence intensities, and that the highest screening positive rate was 69%, compared with that in the wild-type strain. Conclusion: The application of artificially constructed rare codons in this study represents an efficient, accurate, and simple method for screening other amino acid-producing microorganisms.

Characterizing and utilizing oxygen-dependent promoters for efficient dynamic metabolic engineering

Promoters adjust cellular gene expression in response to internal or external signals and are key elements for implementing dynamic metabolic engineering concepts in fermentation processes. One useful signal is the dissolved oxygen content of the culture medium, since production phases often proceed in anaerobic conditions. Although several oxygen-dependent promoters have been described, a comprehensive and comparative study is missing. The goal of this work is to systematically test and characterize 15 promoter candidates that have been previously reported to be induced upon oxygen depletion in Escherichia coli. For this purpose, we developed a microtiter plate-level screening using an algal oxygen-independent flavin-based fluorescent protein and additionally employed flow cytometry analysis for verification. Various expression levels and dynamic ranges could be observed, and six promoters (nar-strong, nar-medium, nar-weak, nirB-m, yfiD-m, and fnrF8) appear particularly suited for dynamic metabolic engineering applications. We demonstrate applicability of these candidates for dynamic induction of enforced ATP wasting, a metabolic engineering approach to increase productivity of microbial strains that requires a narrow level of ATPase expression for optimal function. The selected candidates exhibited sufficient tightness under aerobic conditions while, under complete anaerobiosis, driving expression of the cytosolic F₁-subunit of the ATPase from E. coli to levels that resulted in unprecedented specific glucose uptake rates. We finally utilized the nirB-m promoter to demonstrate the optimization of a two-stage lactate production process by dynamically enforcing ATP wasting, which is automatically turned on in the anaerobic (growth-arrested) production phase to boost the volumetric productivity. Our results are valuable for implementing metabolic control and bioprocess design concepts that use oxygen as signal for regulation and induction.

A novel hybrid promoter capable of continuously producing proteins in high yield

The establishment of cell lines with a high protein production is the most crucial objective in the field of biopharmaceuticals. To this end, efforts have been made to increase transgene expression through promoter improvement, but the efficiency or stability of protein production was insufficient for use in commercial production. Here, we developed a novel strategy to increase the efficiency and stability of protein production by hybridizing a promoter that exhibits higher expression levels at the transient level with a promoter that exhibits higher stability at the stable level. Expression levels of transgenes by each promoter were measured at transient and stable levels for five single promoters: Rous sarcoma virus (RSV), cytomegalovirus (CMV), human phosphoglycerate kinase (hPGK), simian virus 40 (SV40), and zebrafish ubiquitin B (Ubb). The hPGK promoter enabled high-yield transgene expression at transient levels and the SV40 promoter enabled sustained expression at stable levels. Therefore, hPGK and SV40 promoters were selected as candidates for establishing hybrid promoters and two hybrid promoters were constructed; one hybrid promoter in which the SV40 promoter is added before the hPGK promoter (a.k.a. SKYI) and the other hybrid promoter in which the SV40 promoter is added after the hPGK promoter (a.k.a. SKYII). Of the two hybrid promoters, the hybrid promoter SKYII promoted high-yield transgene expression at both transient and stable levels compared to single hPGK and SV40. Together, our findings open new doors in the field of biopharmaceuticals by presenting a novel promoter platform that can be used for high-yield and sustained protein production.

Development and Perspective of Rhodotorula toruloides as an Efficient Cell Factory

Rhodotorula toruloides is receiving significant attention as a novel cell factory because of its high production of lipids and carotenoids, fast growth and high cell density, as well as the ability to utilize a wide variety of substrates. These attractive traits of R. toruloides make it possible to become a low-cost producer that can be engineered for the production of various fuels and chemicals. However, the lack of understanding and genetic engineering tools impedes its metabolic engineering applications. A number of research efforts have been devoted to filling these gaps. This review focuses on recent developments in genetic engineering tools, advances in systems biology for improved understandings, and emerging engineered strains for metabolic engineering applications. Finally, future trends and barriers in developing R. toruloides as a cell factory are also discussed.

Establishment, optimization, and application of genetic technology in Aspergillus spp

Aspergillus is widely distributed in nature and occupies a crucial ecological niche, which has complex and diverse metabolic pathways and can produce a variety of metabolites. With the deepening of genomics exploration, more Aspergillus genomic informations have been elucidated, which not only help us understand the basic mechanism of various life activities, but also further realize the ideal functional transformation. Available genetic engineering tools include homologous recombinant systems, specific nuclease based systems, and RNA techniques, combined with transformation methods, and screening based on selective labeling. Precise editing of target genes can not only prevent and control the production of mycotoxin pollutants, but also realize the construction of economical and efficient fungal cell factories. This paper reviewed the establishment and optimization process of genome technologies, hoping to provide the theoretical basis of experiments, and summarized the recent progress and application in genetic technology, analyzes the challenges and the possibility of future development with regard to Aspergillus.

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.

Transcription regulation strategies in methylotrophs: progress and challenges

As a promising industrial microorganism, methylotroph is capable of using methane or methanol as the sole carbon source natively, which has been utilized in the biosynthesis of various bioproducts. However, the relatively low efficiency of carbon conversion has become a limiting factor throughout the development of methanotrophic cell factories due to the unclear genetic background. To better highlight their advantages in methane or methanol-based biomanufacturing, some metabolic engineering strategies, including upstream transcription regulation projects, are being popularized in methylotrophs. In this review, several strategies of transcription regulations applied in methylotrophs are summarized and their applications are discussed and prospected.

Genetic engineering for enhanced production of a novel alkaline protease BSP-1 in Bacillus amyloliquefaciens

Alkaline protease has been widely applied in food, medicine, environmental protection and other industrial fields. However, the current activity and yield of alkaline protease cannot meet the demand. Therefore, it is important to identify new alkaline proteases with high activity. In this study, we cloned a potential alkaline protease gene bsp-1 from a Bacillus subtilis strain isolated in our laboratory. BSP-1 shows the highest sequence similarity to subtilisin NAT (S51909) from B. subtilis natto. Then, we expressed BSP-1 in Bacillus amyloliquefaciens BAX-9 and analyzed the protein expression level under a collection of promoters. The results show that the P43 promoter resulted in the highest transcription level, protein level and enzyme activity. Finally, we obtained a maximum activity of 524.12 U/mL using the P43 promoter after fermentation medium optimization. In conclusion, this study identified an alkaline protease gene bsp-1 from B. subtilis and provided a new method for high-efficiency alkaline protease expression in B. amyloliquefaciens.

Towards green biomanufacturing of high-value recombinant proteins using promising cell factory: Chlamydomonas reinhardtii chloroplast

Microalgae are cosmopolitan organisms in nature with short life cycles, playing a tremendous role in reducing the pressure of industrial carbon emissions. Besides, microalgae have the unique advantages of being photoautotrophic and harboring both prokaryotic and eukaryotic expression systems, becoming a popular host for recombinant proteins. Currently, numerous advanced molecular tools related to microalgal transgenesis have been explored and established, especially for the model species Chlamydomonas reinhardtii (C. reinhardtii hereafter). The development of genetic tools and the emergence of new strategies further increase the feasibility of developing C. reinhardtii chloroplasts as green factories, and the strong genetic operability of C. reinhardtii endows it with enormous potential as a synthetic biology platform. At present, C. reinhardtii chloroplasts could successfully produce plenty of recombinant proteins, including antigens, antibodies, antimicrobial peptides, protein hormones and enzymes. However, additional techniques and toolkits for chloroplasts need to be developed to achieve efficient and markerless editing of plastid genomes. Mining novel genetic elements and selectable markers will be more intensively studied in the future, and more factors affecting protein expression are urged to be explored. This review focuses on the latest technological progress of selectable markers for Chlamydomonas chloroplast genetic engineering and the factors that affect the efficiency of chloroplast protein expression. Furthermore, urgent challenges and prospects for future development are pointed out.

Plant Flavonoid Production in Bacteria and Yeasts

Flavonoids, a major group of secondary metabolites in plants, are promising for use as pharmaceuticals and food supplements due to their health-promoting biological activities. Industrial flavonoid production primarily depends on isolation from plants or organic synthesis, but neither is a cost-effective or sustainable process. In contrast, recombinant microorganisms have significant potential for the cost-effective, sustainable, environmentally friendly, and selective industrial production of flavonoids, making this an attractive alternative to plant-based production or chemical synthesis. Structurally and functionally diverse flavonoids are derived from flavanones such as naringenin, pinocembrin and eriodictyol, the major basic skeletons for flavonoids, by various modifications. The establishment of flavanone-producing microorganisms can therefore be used as a platform for producing various flavonoids. This review summarizes metabolic engineering and synthetic biology strategies for the microbial production of flavanones. In addition, we describe directed evolution strategies based on recently-developed high-throughput screening technologies for the further improvement of flavanone production. We also describe recent progress in the microbial production of structurally and functionally complicated flavonoids via the flavanone modifications. Strategies based on synthetic biology will aid more sophisticated and controlled microbial production of various flavonoids.

De Novo Design of the ArsR Regulated Pars Promoter Enables a Highly Sensitive Whole-Cell Biosensor for Arsenic Contamination

Whole-cell biosensors for arsenic contamination are typically designed based on natural bacterial sensing systems, which are often limited by their poor performance for precisely tuning the genetic response to environmental stimuli. Promoter design remains one of the most important approaches to address such issues. Here, we use the arsenic-responsive ArsR-P_ars regulation system from Escherichia coli MG1655 as the sensing element and coupled gfp or lacZ as the reporter gene to construct the genetic circuit for characterizing the refactored promoters. We first analyzed the ArsR binding site and a library of RNA polymerase binding sites to mine potential promoter sequences. A set of tightly regulated P_ars promoters by ArsR was designed by placing the ArsR binding sites into the promoter's core region, and a novel promoter with maximal repression efficiency and optimal fold change was obtained. The fluorescence sensor P_lacV-P_arsOC2 constructed with the optimized P_arsOC2 promoter showed a fold change of up to 63.80-fold (with green fluorescence visible to the naked eye) at 9.38 ppb arsenic, and the limit of detection was as low as 0.24 ppb. Further, the optimized colorimetric sensor P_lacV-P_arsOC2-lacZ with a linear response between 0 and 5 ppb was used to perform colorimetric reactions in 24-well plates combined with a smartphone application for the quantification of the arsenic level in groundwater. This study offers a new approach to improve the performance of bacterial sensing promoters and will facilitate the on-site application of arsenic whole-cell biosensors.

Expanding the promoter toolbox for metabolic engineering of methylotrophic yeasts

Methylotrophic yeasts have been widely recognized as a promising host for production of recombinant proteins and value-added chemicals. Promoters for controlled gene expression are critical for construction of efficient methylotrophic yeasts cell factories. Here, we summarized recent advances in characterizing and engineering promoters in methylotrophic yeasts, such as Komagataella phaffii and Ogataea polymorpha. Constitutive and inducible promoters controlled by methanol or other inducers/repressors were introduced to demonstrate their applications in production of proteins and chemicals. Furthermore, efforts of promoter engineering, including site-directed mutagenesis, hybrid promoter, and transcription factor regulation to expand the promoter toolbox were also summarized. This mini-review also provides useful information on promoters for the application of metabolic engineering in methylotrophic yeasts. KEY POINTS: • The characteristics of six methylotrophic yeasts and their promoters are described. • The applications of Komagataella phaffii and Ogataea polymorpha in metabolic engineeringare expounded. • Three promoter engineering strategies are introduced in order to expand the promoter toolbox.

Engineered Escherichia coli Nissle 1917 with urate oxidase and an oxygen-recycling system for hyperuricemia treatment

Hyperuricemia is the second most prevalent metabolic disease to human health after diabetes. Only a few clinical drugs are available, and most of them have serious side effects. The human body does not have urate oxidase, and uric acid is secreted via the kidney or the intestine. Reduction through kidney secretion is often the cause of hyperuricemia. We hypothesized that the intestine secretion could be enhanced when a recombinant urate-degrading bacterium was introduced into the gut. We engineered an Escherichia coli Nissle 1917 strain with a plasmid containing a gene cassette that encoded two proteins PucL and PucM for urate metabolism from Bacillus subtilis, the urate importer YgfU and catalase KatG from E. coli, and the bacterial hemoglobin Vhb from Vitreoscilla sp. The recombinant E. coli strain effectively degraded uric acid under hypoxic conditions. A new method to induce hyperuricemia in mice was developed by intravenously injecting uric acid. The engineered Escherichia coli strain significantly lowered the serum uric acid when introduced into the gut or directly injected into the blood vessel. The results support the use of urate-degrading bacteria in the gut to treat hyperuricemia. Direct injecting bacteria into blood vessels to treat metabolic diseases is proof of concept, and it has been tried to treat solid tumors.

Elucidation of Sequence-Function Relationships for an Improved Biobutanol In Vivo Biosensor in E. coli

Transcription factor (TF)–promoter pairs have been repurposed from native hosts to provide tools to measure intracellular biochemical production titer and dynamically control gene expression. Most often, native TF–promoter systems require rigorous screening to obtain desirable characteristics optimized for biotechnological applications. High-throughput techniques may provide a rational and less labor-intensive strategy to engineer user-defined TF–promoter pairs using fluorescence-activated cell sorting and deep sequencing methods (sort-seq). Based on the designed promoter library’s distribution characteristics, we elucidate sequence–function interactions between the TF and DNA. In this work, we use the sort-seq method to study the sequence–function relationship of a σ⁵⁴-dependent, butanol-responsive TF–promoter pair, BmoR-P_BMO derived from Thauera butanivorans, at the nucleotide level to improve biosensor characteristics, specifically an improved dynamic range. Activities of promoters from a mutagenized P_BMO library were sorted based on gfp expression and subsequently deep sequenced to correlate site-specific sequences with changes in dynamic range. We identified site-specific mutations that increase the sensor output. Double mutant and a single mutant, CA(129,130)TC and G(205)A, in P_BMO promoter increased dynamic ranges of 4-fold and 1.65-fold compared with the native system, respectively. In addition, sort-seq identified essential sites required for the proper function of the σ⁵⁴-dependent promoter biosensor in the context of the host. This work can enable high-throughput screening methods for strain development.