Promoter engineering: Recent advances in controlling transcription at the most fundamental level

A Simple and Effective Strategy for the Development of Robust Promoter-Centric Gene Expression Tools

Promoter-centric genetic tools play a crucial role in controlling gene expression for various applications, such as strain engineering and synthetic biology studies. Hence, a critical need persists for the development of robust gene expression tools. Streptomyces are well-known prolific producers of natural products and exceptional surrogate hosts for the production of high-value chemical compounds and enzymes. In this study, we reported a straightforward and effective strategy for the creation of potent gene expression tools. This was primarily achieved by introducing an additional -35-like motif upstream of the original -35 region of the promoter, coupled with the integration of a palindromic cis-element into the 5'-UTR region. This approach has generated a collection of robust constitutive and inducible gene expression tools tailored for Streptomyces. Of particular note, the fully activated oxytetracycline-inducible gene expression system containing an engineered kasOp* promoter (OK) exhibited nearly an order of magnitude greater activity compared to the well-established high-strength promoter kasOp* under the tested conditions, establishing itself as a powerful gene expression system for Streptomyces. This strategy is expected to be applicable in modifying various other promoters to acquire robust gene expression tools, as evidenced by the enhancement observed in the other two promoters, PL and P21 in this study. Moreover, the effectiveness of these tools has been demonstrated through the augmented production of transglutaminase and daptomycin. The gene expression tools established in this study, alongside those anticipated in forthcoming research, are positioned to markedly advance pathway engineering and synthetic biology investigations in Streptomyces and other microbial strains.

CAPE: a deep learning framework with Chaos-Attention net for Promoter Evolution

Predicting the strength of promoters and guiding their directed evolution is a crucial task in synthetic biology. This approach significantly reduces the experimental costs in conventional promoter engineering. Previous studies employing machine learning or deep learning methods have shown some success in this task, but their outcomes were not satisfactory enough, primarily due to the neglect of evolutionary information. In this paper, we introduce the Chaos-Attention net for Promoter Evolution (CAPE) to address the limitations of existing methods. We comprehensively extract evolutionary information within promoters using merged chaos game representation and process the overall information with modified DenseNet and Transformer structures. Our model achieves state-of-the-art results on two kinds of distinct tasks related to prokaryotic promoter strength prediction. The incorporation of evolutionary information enhances the model's accuracy, with transfer learning further extending its adaptability. Furthermore, experimental results confirm CAPE's efficacy in simulating in silico directed evolution of promoters, marking a significant advancement in predictive modeling for prokaryotic promoter strength. Our paper also presents a user-friendly website for the practical implementation of in silico directed evolution on promoters. The source code implemented in this study and the instructions on accessing the website can be found in our GitHub repository https://github.com/BobYHY/CAPE.

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.

A flexible 'plug and play' bicistronic construct and its application in the screening of protein expression system in Escherichia coli

The bicistronic expression system that utilizes fluorescent reporters has been demonstrated to be a straightforward method for detecting recombinant protein expression levels, particularly when compared to polyacrylamide gel electrophoresis and immunoblot analysis, which are tedious and labor-intensive. However, existing bicistronic reporter systems are less capable of quantitative measurement due to the lag in reporter expression and its negative impact on target protein. In this work, a plug and play bicistronic construct using mCherry as reporter was applied in the screening of optimal replicon and promoter for Sortase expression in Escherichia coli (E. coli). The bicistronic construct allowed the reporter gene and target open reading frame (ORF) to be co-transcribed under the same promoter, resulting in a highly positive quantitative correlation between the expression titer of Sortase and the fluorescent intensity (R2 > 0.97). With the correlation model, the titer of target protein can be quantified by noninvasively measuring the fluorescent intensity. On top of this, the expression of reporter has no significant effect on the yield of target protein, thus favoring a plug and play design for removing reporter gene to generate a plain plasmid for industrial use.

Diffusion-Based Generative Network for de Novo Synthetic Promoter Design

Computer-aided promoter design is a major development trend in synthetic promoter engineering. Various deep learning models have been used to evaluate or screen synthetic promoters, but there have been few works on de novo promoter design. To explore the potential ability of generative models in promoter design, we established a diffusion-based generative model for promoter design in Escherichia coli. The model was completely driven by sequence data and could study the essential characteristics of natural promoters, thus generating synthetic promoters similar to natural promoters in structure and component. We also improved the calculation method of FID indicator, using a convolution layer to extract the feature matrix of the promoter sequence instead. As a result, we got an FID equal to 1.37, which meant synthetic promoters have a distribution similar to that of natural ones. Our work provides a fresh approach to de novo promoter design, indicating that a completely data-driven generative model is feasible for promoter design.

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

Essential factors, advanced strategies, challenges, and approaches involved for efficient expression of recombinant proteins in Escherichia coli

Producing recombinant proteins is a major accomplishment of biotechnology in the past century. Heterologous hosts, either eukaryotic or prokaryotic, are used for the production of these proteins. The utilization of microbial host systems continues to dominate as the most efficient and affordable method for biotherapeutics and food industry productions. Hence, it is crucial to analyze the limitations and advantages of microbial hosts to enhance the efficient production of recombinant proteins on a large scale. E. coli is widely used as a host for the production of recombinant proteins. Researchers have identified certain obstacles with this host, and given the growing demand for recombinant protein production, there is an immediate requirement to enhance this host. The following review discusses the elements contributing to the manifestation of recombinant protein. Subsequently, it sheds light on innovative approaches aimed at improving the expression of recombinant protein. Lastly, it delves into the obstacles and optimization methods associated with translation, mentioning both cis-optimization and trans-optimization, producing soluble recombinant protein, and engineering the metal ion transportation. In this context, a comprehensive description of the distinct features will be provided, and this knowledge could potentially enhance the expression of recombinant proteins in E. coli.

Towards a rational approach to promoter engineering: understanding the complexity of transcription initiation in prokaryotes

Promoter sequences are important genetic control elements. Through their interaction with RNA polymerase they determine transcription strength and specificity, thereby regulating the first step in gene expression. Consequently, they can be targeted as elements to control predictability and tuneability of a genetic circuit, which is essential in applications such as the development of robust microbial cell factories. This review considers the promoter elements implicated in the three stages of transcription initiation, detailing the complex interplay of sequence-specific interactions that are involved, and highlighting that DNA sequence features beyond the core promoter elements work in a combinatorial manner to determine transcriptional strength. In particular, we emphasize that, aside from promoter recognition, transcription initiation is also defined by the kinetics of open complex formation and promoter escape, which are also known to be highly sequence specific. Significantly, we focus on how insights into these interactions can be manipulated to lay the foundation for a more rational approach to promoter engineering.

Nutrient limitation and oxidative stress induce the promoter of acetate operon in Salmonella Typhimurium

Glyoxylate shunt is an important pathway for microorganisms to survive under multiple stresses. One of its enzymes, malate synthase (encoded by aceB gene), has been widely speculated for its contribution to both the pathogenesis and virulence of various microorganisms. We have previously demonstrated that malate synthase (MS) is required for the growth of Salmonella Typhimurium (S. Typhimurium) under carbon starvation and survival under oxidative stress conditions. The aceB gene is encoded by the acetate operon in S. Typhimurium. We attempted to study the activity of acetate promoter under both the starvation and oxidative stress conditions in a heterologous system. The lac promoter of the pUC19 plasmid was substituted with the putative promoter sequence of the acetate operon of S. Typhimurium upstream to the lacZ gene and transformed the vector construct into E. coli NEBα cells. The transformed cells were subjected to the stress conditions mentioned above. We observed a fourfold increase in the β-galactosidase activity in these cells resulting from the upregulation of the lacZ gene in the stationary phase of cell growth (nutrient deprived) as compared to the mid-log phase. Following exposure of stationary phase cells to hypochlorite-induced oxidative stress, we further observed a 1.6-fold increase in β galactosidase activity. These data suggest the induction of promoter activity of the acetate operon under carbon starvation and oxidative stress conditions. Thus, these observations corroborate our previous findings regarding the upregulation of aceB expression under stressful environments.

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.

Synthetic Homoserine Lactone Sensors for Gram-Positive Bacillus subtilis Using LuxR-Type Regulators

A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that Gram-negative and Gram-positive bacteria generally communicate via homoserine lactones (HSLs) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for Gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using the statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors (≥20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a Gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.

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.

Fine-Tuning Gene Expression in Bacteria by Synthetic Promoters

Promoters are key genetic elements in the initiation and regulation of gene expression. A limited number of natural promoters has been described for the control of gene expression in synthetic biology applications. Therefore, synthetic promoters have been developed to fine-tune the transcription for the desired amount of gene product. Mostly, synthetic promoters are characterized using promoter libraries that are constructed via mutagenesis of promoter sequences. The strength of promoters in the library is determined according to the expression of a reporter gene such as gfp encoding green fluorescent protein. Gene expression can be controlled using inducers. The majority of the studies on gram-negative bacteria are conducted using the expression system of the model organism Escherichia coli while that of the model organism Bacillus subtilis is mostly used in the studies on gram-positive bacteria. Additionally, synthetic promoters for the cyanobacteria, which are phototrophic microorganisms, are evaluated, especially using the model cyanobacterium Synechocystis sp. PCC 6803. Moreover, a variety of algorithms based on machine learning methods were developed to characterize the features of promoter elements. Some of these in silico models were verified using in vitro or in vivo experiments. Identification of novel synthetic promoters with improved features compared to natural ones contributes much to the synthetic biology approaches in terms of fine-tuning gene expression.

CRISPR/Cas9-Mediated Promoter Engineering in Saccharopolyspora erythraea

In situ promoter engineering is an effective way to alter target gene expression without introducing excess DNA sequences. Recently, the CRISPR/Cas9 technologies have been proved to be efficient tools for genome editing in actinomycetes, making it easier and more efficient to perform gene insertion and substitution in actinomycetes in a scarless manner. In this chapter, we describe a routine protocol for CRISPR/Cas9-mediated promoter engineering in Saccharopolyspora erythraea NRRL 23338, which is the wild-type producer of erythromycin. This protocol can be adapted to CRISPR/Cas9-mediated gene editing, not limited to promoter engineering, in other actinomycetes, with modifications.

Synthetic Promoter Design and Functional Evaluation in Saccharomyces cerevisiae

Saccharomyces cerevisiae has become a key microbial cell factory for producing biofuels, recombinant proteins, and natural products. The development of efficient cell factories relies on the precise control and fine-tuning of gene expression, underscoring the pivotal role of promoters in pathway engineering. However, natural promoters often have limited transcriptional capacity and thus fall short of the metabolic engineering requirements. This chapter provides protocols and guidelines for constructing and evaluating synthetic promoters in S. cerevisiae. Moreover, these protocols are applicable for creating and testing various synthetic promoters in other host systems.

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.

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.

Targeted mutagenesis and high-throughput screening of diversified gene and promoter libraries for isolating gain-of-function mutations

Targeted mutagenesis of a promoter or gene is essential for attaining new functions in microbial and protein engineering efforts. In the burgeoning field of synthetic biology, heterologous genes are expressed in new host organisms. Similarly, natural or designed proteins are mutagenized at targeted positions and screened for gain-of-function mutations. Here, we describe methods to attain complete randomization or controlled mutations in promoters or genes. Combinatorial libraries of one hundred thousands to tens of millions of variants can be created using commercially synthesized oligonucleotides, simply by performing two rounds of polymerase chain reactions. With a suitably engineered reporter in a whole cell, these libraries can be screened rapidly by performing fluorescence-activated cell sorting (FACS). Within a few rounds of positive and negative sorting based on the response from the reporter, the library can rapidly converge to a few optimal or extremely rare variants with desired phenotypes. Library construction, transformation and sequence verification takes 6-9 days and requires only basic molecular biology lab experience. Screening the library by FACS takes 3-5 days and requires training for the specific cytometer used. Further steps after sorting, including colony picking, sequencing, verification, and characterization of individual clones may take longer, depending on number of clones and required experiments.

Fungal strain improvement for efficient cellulase production and lignocellulosic biorefinery: Current status and future prospects

Lignocellulosic biomass (LCB) has been recognized as a valuable carbon source for the sustainable production of biofuels and value-added biochemicals. Crude enzymes produced by fungal cell factories benefit economic LCB degradation. However, high enzyme production cost remains a great challenge. Filamentous fungi have been widely used to produce cellulolytic enzymes. Metabolic engineering of fungi contributes to efficient cellulase production for LCB biorefinery. Here the latest progress in utilizing fungal cell factories for cellulase production was summarized, including developing genome engineering tools to improve the efficiency of fungal cell factories, manipulating promoters, and modulating transcription factors. Multi-omics analysis of fungi contributes to identifying novel genetic elements for enhancing cellulase production. Furthermore, the importance of translation regulation of cellulase production are emphasized. Efficient development of fungal cell factories based on integrative strain engineering would benefit the overall bioconversion efficacy of LCB for sustainable bioproduction.

Development of Terminator-Promoter Bifunctional Elements for Application in Saccharomyces cerevisiae Pathway Engineering

The construction of a genetic circuit requires the substitution and redesign of different promoters and terminators. The assembly efficiency of exogenous pathways will also decrease significantly when the number of regulatory elements and genes is increased. We speculated that a novel bifunctional element with promoter and terminator functions could be created via the fusion of a termination signal with a promoter sequence. In this study, the elements from a Saccharomyces cerevisiae promoter and terminator were employed to design a synthetic bifunctional element. The promoter strength of the synthetic element is apparently regulated through a spacer sequence and an upstream activating sequence (UAS) with a ~5-fold increase, and the terminator strength could be finely regulated by the efficiency element, with a ~5-fold increase. Furthermore, the use of a TATA box-like sequence resulted in the adequate execution of both functions of the TATA box and the efficiency element. By regulating the TATA box-like sequence, UAS, and spacer sequence, the strengths of the promoter-like and terminator-like bifunctional elements were optimally fine-tuned with ~8-fold and ~7-fold increases, respectively. The application of bifunctional elements in the lycopene biosynthetic pathway showed an improved pathway assembly efficiency and higher lycopene yield. The designed bifunctional elements effectively simplified pathway construction and can serve as a useful toolbox for yeast synthetic biology.

Overexpression of genes by stress-responsive promoters increases protein secretion in Saccharomyces cerevisiae

Recombinant proteins produced by cell factories are now widely used in various fields. Many efforts have been made to improve the secretion capacity of cell factories to meet the increasing demand for recombinant proteins. Recombinant protein production usually causes cell stress in the endoplasmic reticulum (ER). The overexpression of key genes possibly removes limitations in protein secretion. However, inappropriate gene expression may have negative effects. There is a need for dynamic control of genes adapted to cellular status. In this study, we constructed and characterized synthetic promoters that were inducible under ER stress conditions in Saccharomyces cerevisiae. The unfolded protein response element UPRE2, responding to stress with a wide dynamic range, was assembled with various promoter core regions, resulting in UPR-responsive promoters. Synthetic responsive promoters regulated gene expression by responding to stress level, which reflected the cellular status. The engineered strain using synthetic responsive promoters P_{4UPRE2 - TDH3} and P_{4UPRE2 - TEF1} for co-expression of ERO1 and SLY1 had 95% higher α-amylase production compared with the strain using the native promoters P_TDH3 and P_TEF1. This work showed that UPR-responsive promoters were useful in the metabolic engineering of yeast strains for tuning genes to support efficient protein production.

Factors involved in heterologous expression of proteins in E. coli host

The production of recombinant proteins is one of the most significant achievements of biotechnology in the last century. These proteins are produced in the eukaryotic or prokaryotic heterologous hosts. By increasing the omics data especially related to different heterologous hosts as well as the presence of new amenable genetic engineering tools, we can artificially engineer heterologous hosts to produce recombinant proteins in sufficient quantities. Numerous recombinant proteins have been produced and applied in various industries, and the global recombinant proteins market size is expected to be cast to reach USD 2.4 billion by 2027. Therefore, identifying the weakness and strengths of heterologous hosts is critical to optimize the large-scale biosynthesis of recombinant proteins. E. coli is one of the popular hosts to produce recombinant proteins. Scientists reported some bottlenecks in this host, and due to the increasing demand for the production of recombinant proteins, there is an urgent need to improve this host. In this review, we first provide general information about the E. coli host and compare it with other hosts. In the next step, we describe the factors involved in the expression of the recombinant proteins in E. coli. Successful expression of recombinant proteins in E. coli requires a complete elucidation of these factors. Here, the characteristics of each factor will be fully described, and this information can help to improve the heterologous expression of recombinant proteins in E. coli.

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.

Engineering Modular and Highly Sensitive Cell-Based Biosensors for Aromatic Contaminant Monitoring and High-Throughput Enzyme Screening

Although a variety of whole-cell-based biosensors have been developed for different applications in recent years, most cannot meet practical requirements due to insufficient sensing performance. Here, we constructed two sets of modular genetic circuits by serial and parallel modes capable of significantly amplifying the input/output signal in Escherichia coli. The biosensors are engineered using σ⁵⁴-dependent phenol-responsive regulator DmpR as a sensor and enhanced green fluorescent protein as a reporter. Cells harboring serial and parallel genetic circuits displayed nearly 9- and 16-fold higher sensitivity than the general circuit. The genetic circuits enabled rapid detection of six phenolic contaminants in 12 h and showed the low limit of detection of 2.5 and 2.2 ppb for benzopyrene (BaP) and tetracycline (Tet), with a broad detection range of 0.01-1 and 0.005-5 μM, respectively. Furthermore, the positive rate was as high as 73% when the biosensor was applied to screen intracellular enzymes with ester-hydrolysis activity from soil metagenomic libraries using phenyl acetate as a phenolic substrate. Several novel enzymes were isolated, identified, and biochemically characterized, including serine peptidases and alkaline phosphatase family protein/metalloenzyme. Consequently, this study provides a new signal amplification method for cell-based biosensors that can be widely applied to environmental contaminant assessment and screening of intracellular enzymes.

Metabolic engineering for sustainability and health

Bio-based production of chemicals and materials has attracted much attention due to the urgent need to establish sustainability and enhance human health. Metabolic engineering (ME) allows purposeful modification of cellular metabolic, regulatory, and signaling networks to achieve enhanced production of desired chemicals and degradation of environmentally harmful chemicals. ME has significantly progressed over the past 30 years through further integration of the strategies of synthetic biology, systems biology, evolutionary engineering, and data science aided by artificial intelligence. Here we review the field of ME from its emergence to the current state-of-the-art, highlighting its contribution to sustainable production of chemicals, health, and the environment through representative examples. Future challenges of ME and perspectives are also discussed.

CRISPR/Cas9-Mediated Multi-Locus Promoter Engineering in ery Cluster to Improve Erythromycin Production in Saccharopolyspora erythraea

Erythromycins are a group of macrolide antibiotics produced by Saccharopolyspora erythraea. Erythromycin biosynthesis, which is a long pathway composed of a series of biochemical reactions, is precisely controlled by the type I polyketide synthases and accessary tailoring enzymes encoded by ery cluster. In the previous work, we have characterized that six genes representing extremely low transcription levels, SACE_0716-SACE_0720 and SACE_0731, played important roles in limiting erythromycin biosynthesis in the wild-type strain S. erythraea NRRL 23338. In this study, to relieve the potential bottlenecks of erythromycin biosynthesis, we fine-tuned the expression of each key limiting ery gene by CRISPR/Cas9-mediated multi-locus promoter engineering. The native promoters were replaced with different heterologous ones of various strengths, generating ten engineered strains, whose erythromycin productions were 2.8- to 6.0-fold improved compared with that of the wild-type strain. Additionally, the optimal expression pattern of multiple rate-limiting genes and preferred engineering strategies of each locus for maximizing erythromycin yield were also summarized. Collectively, our work lays a foundation for the overall engineering of ery cluster to further improve erythromycin production. The experience of balancing multiple rate-limiting factors within a cluster is also promising to be applied in other actinomycetes to efficiently produce value-added natural products.

Making small molecules in plants: A chassis for synthetic biology-based production of plant natural products

Plant natural products have been extensively exploited in food, medicine, flavor, cosmetic, renewable fuel, and other industrial sectors. Synthetic biology has recently emerged as a promising means for the cost-effective and sustainable production of natural products. Compared with engineering microbes for the production of plant natural products, the potential of plants as chassis for producing these compounds is underestimated, largely due to challenges encountered in engineering plants. Knowledge in plant engineering is instrumental for enabling the effective and efficient production of valuable phytochemicals in plants, and also paves the way for a more sustainable future agriculture. In this manuscript, we briefly recap the biosynthesis of plant natural products, focusing primarily on industrially important terpenoids, alkaloids, and phenylpropanoids. We further summarize the plant hosts and strategies that have been used to engineer the production of natural products. The challenges and opportunities of using plant synthetic biology to achieve rapid and scalable production of high-value plant natural products are also discussed.

Accuracy and data efficiency in deep learning models of protein expression

Synthetic biology often involves engineering microbial strains to express high-value proteins. Thanks to progress in rapid DNA synthesis and sequencing, deep learning has emerged as a promising approach to build sequence-to-expression models for strain optimization. But such models need large and costly training data that create steep entry barriers for many laboratories. Here we study the relation between accuracy and data efficiency in an atlas of machine learning models trained on datasets of varied size and sequence diversity. We show that deep learning can achieve good prediction accuracy with much smaller datasets than previously thought. We demonstrate that controlled sequence diversity leads to substantial gains in data efficiency and employed Explainable AI to show that convolutional neural networks can finely discriminate between input DNA sequences. Our results provide guidelines for designing genotype-phenotype screens that balance cost and quality of training data, thus helping promote the wider adoption of deep learning in the biotechnology sector.

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.

Plasmids for Controlled and Tunable High-Level Expression in E. coli

Genetic systems for protein overexpression are required tools in microbiological and biochemical research. Ideally, these systems include standardized genetic parts with predictable behavior, enabling the construction of stable expression systems in the host organism.

Development of a Glycerol-Inducible Expression System for High-Yield Heterologous Protein Production in Bacillus subtilis

The development of efficient, low-cost, and robust expression systems is important for the mass production of proteins and natural products in large amounts using cell factories. Glycerol is an ideal carbon source for large-scale fermentation due to its low cost and favorable maintenance of the fermentation process. Here, we used the antiterminator protein GlpP and its target promoter P_glpD to construct a highly efficient glycerol-inducible expression system (GIES) in Bacillus subtilis. This system was able to express heterologous genes in an autoinducible manner based on the sequential utilization of glucose and glycerol under the regulation of carbon catabolite repression. In such a system, the concentration of glycerol regulated the strength of gene expression, and the concentration of glucose affected both the timing of induction and the strength of gene expression. By enhancing GlpP, the GIES was further strengthened for high-level intracellular expression of aspartase and secretory expression of nattokinase. High yields of nattokinase in a 5-L fermenter through batch and fed-batch fermentation demonstrated the potential to apply the GIES for large-scale enzyme production. Through the evolution of the -10 box of P_glpD, mutants with gradient activities were obtained. In addition, hybrid glycerol-inducible promoters were successfully constructed by combining the constitutive promoters and the 5' untranslated region of P_glpD. Collectively, this study developed a GIES to obtain high-value products from inexpensive glycerol. More importantly, the great potential of the pair of inherent terminator and antiterminator protein as a portable biological tool for various purposes in synthetic biology is proposed. IMPORTANCE In this study, a GIES was constructed in B. subtilis by employing the antiterminator protein GlpP and the GlpP-regulated promoter P_glpD. Based on the sequential utilization of glucose and glycerol by B. subtilis, the GIES was able to express genes in an autoinducible manner. The amounts and ratio of glucose and glycerol can regulate the gene induction timing and expression strength. The GIES was further applied for high yields of nattokinase, and its robustness in production scale-up was confirmed in a 5-L fermenter. The high-level expression of heterologous proteins demonstrated the huge application potential of the GIES. Furthermore, mutants of P_glpD with gradient activities and hybrid glycerol-inducible promoters were obtained through the evolution of the -10 box of P_glpD and the combination of the constitutive promoters and the 5' untranslated region of P_glpD, respectively. These results demonstrated the use of the antiterminator protein as a regulator for various purposes in synthetic biology.

Yeast transcriptional device libraries enable precise synthesis of value-added chemicals from methanol

Natural methylotrophs are attractive methanol utilization hosts, but lack flexible expression tools. In this study, we developed yeast transcriptional device libraries for precise synthesis of value-added chemicals from methanol. We synthesized transcriptional devices by fusing bacterial DNA-binding proteins (DBPs) with yeast transactivation domains, and linking bacterial binding sequences (BSs) with the yeast core promoter. Three DBP–BS pairs showed good activity when working with transactivation domains and the core promoter of P_AOX1 in the methylotrophic yeast, Pichia pastoris. Fine-tuning of the tandem BSs, spacers and differentiated input promoters further enabled a constitutive transcriptional device library (cTRDL) composed of 126 transcriptional devices with an expression strength of 16–520% and an inducible TRDL (iTRDL) composed of 162 methanol-inducible transcriptional devices with an expression strength of 30–500%, compared with P_AOX1. Selected devices from iTRDL were adapted to the dihydromonacolin L biosynthetic pathway by orthogonal experimental design, reaching 5.5-fold the production from the P_AOX1-driven pathway. The full factorial design of the selected devices from the cTRDL was adapted to the downstream pathway of dihydromonacolin L to monacolin J. Monacolin J production from methanol reached 3.0-fold the production from the P_AOX1-driven pathway. Our engineered toolsets ensured multilevel pathway control of chemical synthesis in methylotrophic yeasts.

Controlling gene expression with deep generative design of regulatory DNA

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Using mutagenesis typically requires screening sizable random DNA libraries, which limits the designs to span merely a short section of the promoter and restricts their control of gene expression. Here, we prototype a deep learning strategy based on generative adversarial networks (GAN) by learning directly from genomic and transcriptomic data. Our ExpressionGAN can traverse the entire regulatory sequence-expression landscape in a gene-specific manner, generating regulatory DNA with prespecified target mRNA levels spanning the whole gene regulatory structure including coding and adjacent non-coding regions. Despite high sequence divergence from natural DNA, in vivo measurements show that 57% of the highly-expressed synthetic sequences surpass the expression levels of highly-expressed natural controls. This demonstrates the applicability and relevance of deep generative design to expand our knowledge and control of gene expression regulation in any desired organism, condition or tissue.

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Here the authors present EspressionGAN, a generative adversarial network that uses genomic and transcriptomic data to generate regulatory sequences.

Secretion of collagenases by Saccharomyces cerevisiae for collagen degradation

Background

The production and processing of animal-based products generates many collagen-rich by-products, which have received attention both for exploitation to increase their added value and to reduce their negative environmental impact. The collagen-rich by-products can be hydrolyzed by collagenases for further utilization. Therefore, collagenases are of benefit for efficient collagen materials processing. An alternative and safe way to produce secreted collagenases is needed.

Results

Two collagenases from Hathewaya histolytica, ColG and ColH, were successfully secreted by the yeast Saccharomyces cerevisiae. Compared with the native signal peptide of collagenase, the α-factor leader is more efficient in guiding collagenase secretion. Collagenase secretion was significantly increased in YPD medium by supplementing with calcium and zinc ions. Recombinant collagenase titers reached 68 U/mL and 55 U/mL for ColG and ColH, respectively. Collagenase expression imposed metabolic perturbations on yeast cells; substrate consumption, metabolites production and intracellular cofactor levels changed in engineered strains. Both recombinant collagenases from yeast could hydrolyze soluble and insoluble collagen materials. Recombinant ColG and ColH showed a synergistic effect on efficient collagen digestion.

Conclusions

Sufficient calcium and zinc ions are essential for active collagenase production by yeast. Collagenase secretion was increased by optimization of expression cassettes. Collagenase expression imposed metabolic burden and cofactor perturbations on yeast cells, which could be improved through metabolic engineering. Our work provides a useful way to produce collagenases for collagen resource utilization.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02186-y.

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.

Efficient extracellular production of recombinant proteins in E. coli via enhancing expression of dacA on the genome

D, D-carboxypeptidase DacA plays an important role in the synthesis and stabilization of Escherichia coli cell wall peptidoglycan. The production level of extracellular recombinant proteins in E. coli can be enhanced by high D, D-carboxypeptidase activity. Construction of expression systems under optimal promoters is one of the main strategies to realize high protein production in E. coli. In this study, the promoter P_dacA-3 from DacA on the genome of E. coli BL21 (DE3) was verified to be efficient for recombinant green fluorescent protein using the plasmid mutant pET28a-P_dacA with P_dacA-3. Meanwhile, the promoter P_dacA-3 was engineered to increase the production level of proteins via inserting one or two Shine–Dalgarno (SD) sequences between the promoter P_dacA-3 and the target genes. The expression level of dacA on the genome was increased by the improved transcription of the engineered promoters (especially after inserting one additional SD sequence). The engineered promoters increased cell membrane permeabilities to significantly enhance the secretion production of extracellular recombinant proteins in E. coli. Among them, the extracellular recombinant amylase activities in E. coli BL21::1SD-pET28a-amyK and E. coli BL21::2SD-pET28a-amyK were increased by 2.0- and 1.6-fold that of the control (E. coli BL21-pET28a-amyK), respectively. Promoter engineering also affected the morphology and growth of the E. coli mutants. It was indicated that the engineered promoters enhanced the expression of dacA on the genome to disturb the synthesis and structural stability of cell wall peptidoglycans.

Functional analysis of PagNAC045 transcription factor that improves salt and ABA tolerance in transgenic tobacco

BACKGROUND

Salt stress causes inhibition of plant growth and development, and always leads to an increasing threat to plant agriculture. Transcription factors regulate the expression of various genes for stress response and adaptation. It's crucial to reveal the regulatory mechanisms of transcription factors in the response to salt stress.

RESULTS

A salt-inducible NAC transcription factor gene PagNAC045 was isolated from Populus alba×P. glandulosa. The PagNAC045 had a high sequence similarity with NAC045 (Potri.007G099400.1) in P. trichocarpa, and they both contained the same conserved motifs 1 and 2, which constitute the highly conserved NAM domain at the N-terminus. Protein-protein interaction (PPI) prediction showed that PagNAC045 potentially interacts with many proteins involved in plant hormone signaling, DNA-binding and transcriptional regulation. The results of subcellular localization and transient expression in tobacco leaves confirmed the nuclear localization of PagNAC045. Yeast two-hybrid revealed that PagNAC045 protein exhibits transcriptional activation property and the activation domain located in its C-terminus. In addition, the 1063 bp promoter of PagNAC045 was able to drive GUS gene expression in the leaves and roots. In poplar leaves and roots, PagNAC045 expression increased significantly by salt and ABA treatments. Tobacco seedlings overexpressing PagNAC045 exhibited enhanced tolerance to NaCl and ABA compared to the wild-type (WT). Yeast one-hybrid assay demonstrated that a bHLH104-like transcription factor can bind to the promoter sequence of PagNAC045.

CONCLUSION

The PagNAC045 functions as positive regulator in plant responses to NaCl and ABA-mediated stresses.

Programmable Synthetic Upstream Activating Sequence Library for Fine-Tuning Gene Expression Levels in Saccharomyces cerevisiae

A wide dynamic range of promoters is necessary for fine-tuning transcription levels. However, weak intensity and narrow dynamic range limit transcriptional regulation via constitutive promoters. The upstream activation sequence (UAS) located upstream of the core promoter is a crucial region that could obviously enhance promoter strength. Herein, we created a random mutagenesis library consisting of 330 different variants based on the UAS of the TDH3 promoter with an ∼37-fold dynamic range by error-prone polymerase chain reaction (PCR) and obtained strong intensity mutant UAS, which was ∼12-fold greater than the wild-type UAS_TDH3. Analysis of the mutant library revealed 15 strength-enhancing sites and their corresponding bases of the UAS_TDH3 regions, which provided the impetus for a synthetic library. The resulting 32 768 mutant UAS library was constructed by permutation and combination of the bases of the 15 enhancing sites. To characterize the library, a strength prediction model was built by correlating DNA structural features and UAS strength, which provided a model between UAS sequence and intensity. Following characterization, the UAS library was applied to precisely regulate gene expression in the production of β-carotene, proving that the UAS library would be a useful tool for gene tuning in metabolic engineering. In summary, we designed, constructed, and characterized a UAS library that facilitated precise tuning of transcription levels of target proteins.

Advancing Yarrowia lipolytica as a superior biomanufacturing platform by tuning gene expression using promoter engineering

Yarrowia lipolytica is recognized as an excellent non-conventional yeast in the field of biomanufacturing, where it is used as a host to produce oleochemicals, terpenes, organic acids, polyols and recombinant proteins. Consequently, metabolic engineering of this yeast is becoming increasingly popular to advance it as a superior biomanufacturing platform, of which promoters are the most basic elements for tuning gene expression. Endogenous promoters of Yarrowia lipolytica were reviewed, which are the basis for promoter engineering. The engineering strategies, such as hybrid promoter engineering, intron enhancement promoter engineering, and transcription factor-based inducible promoter engineering are described. Additionally, the applications of Yarrowia lipolytica promoter engineering to rationally reconstruct biosynthetic gene clusters and improve the genome-editing efficiency of the CRISPR-Cas systems were reviewed. Finally, research needs and future directions for promoter engineering are also discussed in this review.

A programmable high-expression yeast platform responsive to user-defined signals

Rapidly growing yeasts with appropriate posttranslational modifications are favored hosts for protein production in the biopharmaceutical industry. However, limited production capacity and intricate transcription regulation restrict their application and adaptability. Here, we describe a programmable high-expression yeast platform, SynPic-X, which responds to defined signals and is broadly applicable. We demonstrated that a synthetic improved transcriptional signal amplification device (iTSAD) with a bacterial-yeast transactivator and bacterial-yeast promoter markedly increased expression capacity in Pichia pastoris. CRISPR activation and interference devices were designed to strictly regulate iTSAD in response to defined signals. Engineered switches were then constructed to exemplify the response of SynPic-X to exogenous signals. Expression of α-amylase by SynPic-R, a specific SynPic-X, in a bioreactor proved a methanol-free high-production process of recombinant protein. Our SynPic-X platform provides opportunities for protein production in customizable yeast hosts with high expression and regulatory flexibility.

Making Use of Plant uORFs to Control Transgene Translation in Response to Pathogen Attack

Reducing crop loss to diseases is urgently needed to meet increasing food production challenges caused by the expanding world population and the negative impact of climate change on crop productivity. Disease-resistant crops can be created by expressing endogenous or exogenous genes of interest through transgenic technology. Nevertheless, enhanced resistance by overexpressing resistance-produced genes often results in adverse developmental affects. Upstream open reading frames (uORFs) are translational control elements located in the 5' untranslated region (UTR) of eukaryotic mRNAs and may repress the translation of downstream genes. To investigate the function of three uORFs from the 5' -UTR of ACCELERATED CELL 11 (uORFsACD11), we develop a fluorescent reporter system and find uORFsACD11 function in repressing downstream gene translation. Individual or simultaneous mutations of the three uORFsACD11 lead to repression of downstream translation efficiency at different levels. Importantly, uORFsACD11-mediated translational inhibition is impaired upon recognition of pathogen attack of plant leaves. When coupled with the PATHOGENESIS-RELATED GENE 1 (PR1) promoter, the uORFsACD11 cassettes can upregulate accumulation of Arabidopsis thaliana LECTIN RECEPTOR KINASE-VI.2 (AtLecRK-VI.2) during pathogen attack and enhance plant resistance to Phytophthora capsici. These findings indicate that the uORFsACD11 cassettes can be a useful toolkit that enables a high level of protein expression during pathogen attack, while for ensuring lower levels of protein expression at normal conditions.

Cheating the Cheater: Suppressing False-Positive Enrichment during Biosensor-Guided Biocatalyst Engineering

Transcription factor (TF)-based biosensors are very desirable reagents for high-throughput enzyme and strain engineering campaigns. Despite their potential, they are often difficult to deploy effectively as the small molecules being detected can leak out of high-producer cells, into low-producer cells, and activate the biosensor therein. This crosstalk leads to the overrepresentation of false-positive/cheater cells in the enriched population. While the host cell can be engineered to minimize crosstalk (e.g., by deleting responsible transporters), this is not easily applicable to all molecules of interest, particularly those that can diffuse passively. One such biosensor recently reported for trans-cinnamic acid (tCA) suffers from crosstalk when used for phenylalanine ammonia-lyase (PAL) enzyme engineering by directed evolution. We report that desensitizing the biosensor (i.e., increasing the limit of detection) suppresses cheater population enrichment. Furthermore, we show that, if we couple the biosensor-based screen with an orthogonal prescreen that eliminates a large fraction of true negatives, we can successfully reduce the cheater population during the fluorescence-activated cell sorting. Using the approach developed here, we were successfully able to isolate PAL variants with ∼70% higher k_cat after a single sort. These mutants have tremendous potential in phenylketonuria (PKU) treatment and flavonoid production.

Trade-Offs in Biosensor Optimization for Dynamic Pathway Engineering

Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to its ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase the titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy, and pharmaceutical sectors.

Precise Prediction of Promoter Strength Based on a De Novo Synthetic Promoter Library Coupled with Machine Learning

Promoters are one of the most critical regulatory elements controlling metabolic pathways. However, the fast and accurate prediction of promoter strength remains challenging, leading to time- and labor-consuming promoter construction and characterization processes. This dilemma is caused by the lack of a big promoter library that has gradient strengths, broad dynamic ranges, and clear sequence profiles that can be used to train an artificial intelligence model of promoter strength prediction. To overcome this challenge, we constructed and characterized a mutant library of Trc promoters (P_trc) using 83 rounds of mutation-construction-screening-characterization engineering cycles. After excluding invalid mutation sites, we established a synthetic promoter library that consisted of 3665 different variants, displaying an intensity range of more than two orders of magnitude. The strongest variant was ∼69-fold stronger than the original P_trc and 1.52-fold stronger than a 1 mM isopropyl-β-d-thiogalactoside-driven P_T7 promoter, with an ∼454-fold difference between the strongest and weakest expression levels. Using this synthetic promoter library, different machine learning models were built and optimized to explore the relationships between promoter sequences and transcriptional strength. Finally, our XgBoost model exhibited optimal performance, and we utilized this approach to precisely predict the strength of artificially designed promoter sequences (R² = 0.88, mean absolute error = 0.15, and Pearson correlation coefficient = 0.94). Our work provides a powerful platform that enables the predictable tuning of promoters to achieve optimal transcriptional strength.

Characterizing and engineering promoters for metabolic engineering of Ogataea polymorpha

Bio-manufacturing via microbial cell factory requires large promoter library for fine-tuned metabolic engineering. Ogataea polymorpha, one of the methylotrophic yeasts, possesses advantages in broad substrate spectrum, thermal-tolerance, and capacity to achieve high-density fermentation. However, a limited number of available promoters hinders the engineering of O. polymorpha for bio-productions. Here, we systematically characterized native promoters in O. polymorpha by both GFP fluorescence and fatty alcohol biosynthesis. Ten constitutive promoters (P_PDH, P_PYK, P_FBA, P_PGM, P_GLK, P_TRI, P_GPI, P_ADH1, P_TEF1 and P_GCW14) were obtained with the activity range of 13%–130% of the common promoter P_GAP (the promoter of glyceraldehyde-3-phosphate dehydrogenase), among which P_PDH and P_GCW14 were further verified by biosynthesis of fatty alcohol. Furthermore, the inducible promoters, including ethanol-induced P_ICL1, rhamnose-induced P_LRA3 and P_LRA4, and a bidirectional promoter (P_Mal-P_Per) that is strongly induced by sucrose, further expanded the promoter toolbox in O. polymorpha. Finally, a series of hybrid promoters were constructed via engineering upstream activation sequence (UAS), which increased the activity of native promoter P_LRA3 by 4.7–10.4 times without obvious leakage expression. Therefore, this study provided a group of constitutive, inducible, and hybrid promoters for metabolic engineering of O. polymorpha, and also a feasible strategy for rationally regulating the promoter strength.

Engineering of Promoters for Gene Expression in Pichia pastoris

The availability of exceptionally strong and tightly regulated promoters is a key feature of Komagataella phaffii (syn. Pichia pastoris), a widely applied yeast expression system for heterologous protein production. Most commonly, the methanol-inducible promoter of the alcohol oxidase 1 gene (P_AOX1) and the constitutive promoter of the glyceraldehyde 3 phosphate dehydrogenase gene (P_GAP) have been used. Recently, also promising novel constitutive (P_GCW14), regulated (P_GTH1, P_CAT1), and bidirectional promoters (histone promoters and synthetic hybrid variants) have been reported.As natural promoters showed so far limited tunability of expression levels and regulatory profiles, various promoter engineering efforts have been undertaken for P. pastoris . P_AOX1, P_DAS2, P_GAP, and P_GCW14 have been engineered by systematic deletion studies or random mutagenesis of upstream regulatory sequences. New engineering strategies have focused on P_AOX1 core promoter modifications by random or rational approaches and transcriptional regulatory circuits to render P_AOX1 independent of methanol induction. These promoter engineering efforts in P. pastoris have resulted in improved, sequence-diversified synthetic promoter variants allowing coordinated fine-tuning of gene expression for a multitude of biotechnological applications.

Metabolic engineering of Bacillus subtilis with an endopolygalacturonase gene isolated from Pectobacterium. carotovorum; a plant pathogenic bacterial strain

Pectinolytic enzymes or pectinases are synthesized naturally by numerous microbes and plants. These enzymes degrade various kinds of pectin which exist as the major component of the cell wall in plants. A pectinase gene encoding endo-polygalacturonase (endo-PGase) enzyme was isolated from Pectobacterium carotovorum a plant pathogenic strain of bacteria and successfully cloned into a secretion vector pHT43 having σA-dependent promoter for heterologous expression in Bacillus subtilis (WB800N).The desired PCR product was 1209bp which encoded an open reading frame of 402 amino acids. Recombinant proteins showed an estimated molecular weight of 48 kDa confirmed by sodium dodecyl sulphate-polyacrylamide-gel electrophoresis. Transformed B. subtilis competent cells harbouring the engineered pHT43 vector with the foreign endo-PGase gene were cultured in 2X-yeast extract tryptone medium and subsequently screened for enzyme activity at various temperatures and pH ranges. Optimal activity of recombinant endo-PGase was found at 40°C and pH 5.0. To assay the catalytic effect of metal ions, the recombinant enzyme was incubated with 1 mM concentration of various metal ions. Potassium chloride increased the enzyme activity while EDTA, Zn++ and Ca++, strongly inhibited the activity. The chromatographic analysis of enzymatic hydrolysates of polygalacturonic acid (PGA) and pectin substrates using HPLC and TLC revealed tri and tetra-galacturonates as the end products of recombinant endo-PGase hydrolysis. Conclusively, endo-PGase gene from the plant pathogenic strain was successfully expressed in Bacillus subtilis for the first time using pHT43 expression vector and could be assessed for enzyme production using a very simple medium with IPTG induction. These findings proposed that the Bacillus expression system might be safer to escape endotoxins for commercial enzyme production as compared to yeast and fungi. Additionally, the hydrolysis products generated by the recombinant endo-PGase activity offer their useful applications in food and beverage industry for quality products.

Improving the Intensity of Integrated Expression for Microbial Production

Chromosomal integration of exogenous genes is preferred for industrially related fermentation, as plasmid-mediated fermentation leads to extra metabolic burden and genetic instability. Moreover, with the development and advancement of genome engineering and gene editing technologies, inserting genes into chromosomes has become more convenient; integration expression is extensively utilized in microorganisms for industrial bioproduction and expected to become the trend of recombinant protein expression. However, in actual research and application, it is important to enhance the expression of heterologous genes at the host genome level. Herein, we summarized the basic principles and characteristics of genomic integration; furthermore, we highlighted strategies to improve the expression of chromosomal integration of genes and pathways in host strains from three aspects, including chassis cell optimization, regulation of expression elements in gene expression cassettes, optimization of gene dose level and integration sites on chromosomes. Moreover, we reviewed and summarized the relevant studies on the application of integrated expression in the exploration of gene function and the various types of industrial microorganism production. Consequently, this review would serve as a reference for the better application of integrated expression.