The modification of heme special importer to improve the production of active hemoglobins in Escherichia coli.

To enhance the import of heme for the production of active hemoproteins in Escherichia coli C41 (DE3) lacking the special heme import system, heme receptor ChuA from E. coli Nissle 1917 was modified through molecular docking and the other components (ChuTUV) for heme import was overexpressed, while heme import was tested through growth assay and heme sensor HS1 detection. A ChuA mutant G360K was selected, which could import 3.91 nM heme, compared with 2.92 nM of the wild-type ChuA. In addition, it presented that the expression of heme transporters ChuTUV was not necessary for heme import. Based on the modification of ChuA (G360K), the titer of human hemoglobin and the peroxidase activity of leghemoglobin reached 1.19 µg g-1 DCW and 24.16 103 U g-1 DCW, compared with 1.09 µg g-1 DCW and 21.56 103 U g-1 DCW of the wild-type ChuA, respectively. Heme import can be improved through the modification of heme receptor and the engineered strain with improved heme import has a potential to efficiently produce high-active hemoproteins.

Recent advances and prospects of Bacillus amyloliquefaciens as microbial cell factories: from rational design to industrial applications.

Bacillus amyloliquefaciens is one of the most characterized Gram-positive bacteria. This species has unique characteristics that are beneficial for industrial applications, including its utilization of: cheap carbon as a substrate, a transparent genetic background, and large-scale robustness in fermentation. Indeed, the productivity characteristics of B. amyloliquefaciens have been thoroughly analyzed and further optimized through systems biology and synthetic biology techniques. Following the analysis of multiple engineering design strategies, B. amyloliquefaciens is now considered an efficient cell factory capable of producing large quantities of multiple products from various raw materials. In this review, we discuss the significant potential advantages offered by B. amyloliquefaciens as a platform for metabolic engineering and industrial applications. In addition, we systematically summarize the recent laboratory research and industrial application of B. amyloliquefaciens, including: relevant advances in systems and synthetic biology, various strategies adopted to improve the cellular performances of synthetic chemicals, as well as the latest progress in the synthesis of certain important products by B. amyloliquefaciens. Finally, we propose the current challenges and essential strategies to usher in an era of broader B. amyloliquefaciens use as microbial cell factories.

Manipulation of fungal cell wall integrity to improve production of fungal natural products.

Fungi, as an important industrial microorganism, play an essential role in the production of natural products (NPs) due to their advantages of utilizing cheap raw materials as substrates and strong protein secretion ability. Although many metabolic engineering strategies have been adopted to enhance the biosynthetic pathway of NPs in fungi, the fungal cell wall as a natural barrier tissue is the final and key step that affects the efficiency of NPs synthesis. To date, many important progresses have been achieved in improving the synthesis of NPs by regulating the cell wall structure of fungi. In this review, we systematically summarize and discuss various strategies for modifying the cell wall structure of fungi to improve the synthesis of NPs. At first, the cell wall structure of different types of fungi is systematically described. Then, strategies to disrupt cell wall integrity (CWI) by regulating the synthesis of cell wall polysaccharides and binding proteins are summarized, which have been applied to improve the synthesis of NPs. In addition, we also summarize the studies on the regulation of CWI-related signaling pathway and the addition of exogenous components for regulating CWI to improve the synthesis of NPs. Finally, we propose the current challenges and essential strategies to usher in an era of more extensive manipulation of fungal CWI to improve the production of fungal NPs.

Visible-light organophotoredox-mediated intermolecular formal [4 + 2] cycloadditions of arylcyclobutylamines with olefins.

We have developed a visible-light-mediated formal [4 + 2] cycloaddition of arylcyclobutylamines with olefins, using QXPT-NPhCN as an organic photocatalyst. The corresponding cycloadducts could be obtained from electron-deficient olefins, aryl olefins and exocyclic olefins. We found that the addition of K3PO4 could significantly promote the cycloadditions. Using this method, 2-functionalized cyclohexylamines including the ones with spiro-skeletons can be expediently obtained. Based on the "3D-bioisostere" principle, we designed and synthesized three cyclohexylamine 2-sulfonylurea compounds.

Visible-Light Organophotoredox-Mediated [3 + 2] Cycloaddition of Arylcyclopropylamine with Structurally Diverse Olefins for the Construction of Cyclopentylamines and Spiro[4.n] Skeletons.

We developed a visible-light-mediated [3 + 2] cycloaddition of arylcyclopropylamine with structurally diverse olefins using QXPT-NPh as a highly efficient organic photoredox catalyst. We first achieved the use of various alkyl-substituted alkenes in intermolecular [3 + 2] cycloadditions with cyclopropylamine. We also developed a general and efficient strategy for the construction of structurally diverse cyclopentane-based spiro[4.n] skeletons with 1,3-difunctional groups, which broadly exist in natural products and synthetic molecules. Furthermore, we proposed a hydrogen-bond mode between the arylcyclopropylamine and the photocatalyst QXPT-NPh.

Enhancing isoprenoid synthesis in Yarrowia lipolytica by expressing the isopentenol utilization pathway and modulating intracellular hydrophobicity.

The abundant supply of biosynthetic precursors and product compatibility with the intracellular environment play important roles for microbial isoprenoid production. In this study, we tailor to both of these requirements by introducing the two-step isopentenol utilization pathway (IUP) to augment the native pathway in the oleaginous yeast Yarrowia lipolytica. With shortcut access to the common isoprenoid precursor, isopentenyl pyrophosphate (IPP) and its isomer dimethylallyl pyrophosphate (DMAPP), IUP is capable of elevating IPP + DMAPP levels by 15.7-fold compared to the mevalonate pathway alone. The increase in IPP + DMAPP levels can directly lead to better isoprenoid synthesis, which is illustrated using lycopene as a model compound. Moreover, we also demonstrate that higher lipid contents in the cells correlate with improved intracellular lycopene production, suggesting the importance of having a substantial hydrophobic environment to sequester isoprenoids. Combining these strategies with further genetic and fermentation optimizations, we achieved a final lycopene titer of 4.2 g/L. Overall, these strategies hold great potential for strengthening the synthesis of long-chain isoprenoids and fat-soluble natural products in microbes.

Enhanced pyruvate production in Candida glabrata by carrier engineering.

Pyruvate is an important organic acid that plays a key role in the central metabolic pathway. Manipulating transporters is an efficient strategy to enhance production of target organic acids and a means to understand the effects of altered intracellular pyruvate content on global metabolic networks. Efforts have been made to manipulate mitochondrial pyruvate carrier (MPC) to transport pyruvate into different subcellular compartments in Candida glabrata to demonstrate the effects of the subcellular distribution of pyruvate on central carbon metabolism. By increasing the mitochondrial pyruvate content through enhancing the rate of pyruvate transport into mitochondria, a high central carbon metabolism rate, specific growth rate and specific pyruvate production rate were obtained. Comparing the intracellular pyruvate content of engineered and control strains showed that higher intracellular pyruvate levels were not conducive to improving pyruvate productivity or central carbon metabolism. Plasma membrane expression of MPCs significantly increased the expression levels of key rate-limiting glycolytic enzymes. Moreover, pyruvate production of CGΔura3-Sp-MPC1, CGΔura3-Sp-MPC2, and CGΔura3-Sp-MPC1-Sp-MPC2 increased 134.4%, 120.3%, and 30.0%, respectively. In conclusion, lower intracellular pyruvate content enhanced central carbon metabolism and provided useful clues for improving the production of other organic acids in microorganisms.

Enhanced avermectin production by Streptomyces avermitilis ATCC 31267 using high-throughput screening aided by fluorescence-activated cell sorting.

Avermectins, produced by Streptomyces avermitilis, are important antiparasitic agents. The use of traditional microbial breeding methods for this organism has been limited by the low-throughput shake flask-based screening process. The unique growth cycle of actinomycetes makes the establishment of a reliable high-throughput screening (HTS) process difficult. To enhance the efficiency of screening strains with high yields of avermectin, a HTS process aided by fluorescence-activated cell sorting (FACS) was established. Four different spore solutions were investigated for maintaining a relatively high viability of spores. Propidium iodide (PI) and fluorescein diacetate (FDA) were used to discriminate between dead and live spores using the FACS system. Spores stained with 7-µg/mL PI and 15-µg/mL FDA at 4 °C in the dark for 30 min resulted in optimum sorting. Spores were treated by atmospheric and room temperature plasma (ARTP). Single live spores were sorted and sprayed into 96-well microtiter plates containing 50 µL of solid agar culture medium. Solid-liquid combinatorial microculture was used for high-throughput avermectin culture. A high-titer avermectin producer (G9) was obtained from 5760 mutants after mutagenesis and HTS. Compared with the original strain, the titer was improved by 18.9% on flask culture and 20.6% on fermenter, respectively. The HTS process established in this study could easily be transferred to other similar target products produced by actinomycetes.

Identification of a polysaccharide produced by the pyruvate overproducer Candida glabrata CCTCC M202019.

Candida glabrata has great potential for the accumulation of pyruvate as a preferred strain in pyruvate production by fermentation. However, its substrate conversion rate is relatively low. In this study, a novel polysaccharide containing α-1,4-glucosidic bonds was observed accidentally in screening a high-titer pyruvate strain by atmospheric and room temperature plasma mutagenesis of C. glabrata. Chemical analysis of the partially purified polysaccharide S4-C10 showed the main components were 1.2% (w/w) protein and 94.2% (w/w) total sugar. Fourier transform infrared and molecular mass distribution analysis indicated that the main component (PSG-2) of S4-C10 was a small molecular homogeneous protein-bound polysaccharide. Monosaccharide analysis of PSG-2 showed it consisted of glucose, mannose, and fructose. By optimizing the vitamin mix content, 77.6 g L-1 S4-C10 polysaccharide could be obtained after 72 h fermentation at 30 °C in 500-mL flasks. RT-qPCR analysis showed that transcriptional level of some key genes related to polysaccharide biosynthesis was upregulated compared to that of wild-type strain. By knocking out two most significantly upregulated genes, CAGL0H02695g and CAGL0K10626g, in the wild-type strain, the pyruvate consumption rate was significantly reduced in late pyruvate fermentation phase, while the titer of polysaccharides was reduced by 18.0%. Besides the potential applications of the novel identified polysaccharide, this study provided clues for increasing the conversion ratio of glucose to pyruvate in C. glabrata by further decreasing the accumulation of polysaccharides.

A high-throughput screening procedure for enhancing pyruvate production in Candida glabrata by random mutagenesis.

Candida glabrata is one of the most promising pyruvate producers. A series of experiments was conducted to enhance pyruvate production by C. glabrata via metabolic and genetic engineering. Here, a novel screening strategy, which combined atmospheric and room temperature plasma-based random mutagenesis and high-throughput screening (HTS), was used to screen for high pyruvate-producing mutants that could use cheap industrial raw materials as nitrogen sources. A high-titer pyruvate producer (H6) was obtained form 30,000 mutants after 30 rounds of mutagenesis and HTS. Compared with a wild-type strain, pyruvate production by the H6 mutant was 32.2 and 35.4% higher in 500-mL shake flasks and 3-L fermenter, respectively, when cheap peptone was used as the nitrogen source in the seed culture stage. The HTS process significantly improved the screening efficiency and reduced fermentation cost. This procedure could also easily be applied to screen for strains that produce high titers of similar organic acids.

Optimization of vanillin biosynthesis in Escherichia coli K12 MG1655 through metabolic engineering.

Vanillin is an important flavouring agent applied in food, spices, pharmaceutical industries and other fields. Microbial biosynthesis of vanillin is considered a sustainable and economically feasible alternative to traditional chemical synthesis. In this study, Escherichia coli K12 MG1655 was used for the de novo synthesis of VAN by screening highly active carboxylic acid reductases and catechol O-methyltransferases, optimising the protocatechuic acid pathway, and regulating competitive metabolic pathways. Additionally, major alcohol by-products were identified and decreased by deleting three endogenous aldo-keto reductases and three alcohol dehydrogenases. Finally, a highest VAN titer was achieved to 481.2 mg/L in a 5 L fermenter from glucose. This work provides a valuable example of pathway engineering and screens several enzyme variants for the first time in E. coli.

De Novo Biosynthesis of Lutein in Yarrowia lipolytica.

Lutein is a high-value tetraterpenoid carotenoid that is widely used in feed, cosmetics, food, and drugs. Microbial synthesis of lutein is an important method for green and sustainable production, serving as an alternative to plant extraction methods. However, an inadequate precursor supply and low catalytic efficiency of key pathway enzymes are the main reasons for the low efficacy of microbial synthesis of lutein. In this study, some strategies, such as enhancing the MVA pathway and localizing α-carotene synthase OluLCY within the subcellular organelles in Yarrowia lipolytica, were adopted to enhance the synthesis of precursor α-carotene, which resulted in a 10.50-fold increase in α-carotene titer, reaching 38.50 mg/L. Subsequently, by improving hydroxylase activity with truncated N-terminal transport peptide and locating hydroxylases to subcellular organelles, the final strain L9 producing 75.25 mg/L lutein was obtained. Eventually, a lutein titer of 675.40 mg/L (6.13 mg/g DCW) was achieved in a 5 L bioreactor by adding the antioxidant 2,6-ditert-butyl-4-methylphenol. This study realizes de novo synthesis of lutein in Y. lipolytica for the first time and achieves the highest lutein titer reported so far.

Highly Efficient Biosynthesis of Rebaudioside M8 through Structure-Guided Engineering of Glycosyltransferase UGT94E13.

Given the low-calorie, high-sweetness characteristics of steviol glycosides (SGs), developing SGs with improved taste profiles is a key focus. Rebaudioside M8 (Reb M8), a novel non-natural SG derivative obtained through glycosylation at the C-13 position of rebaudioside D (Reb D) using glycosyltransferase UGT94E13, holds promise for further development due to its enhanced sweetness. However, the low catalytic activity of UGT94E13 hampers further research and commercialization. This study aimed to improve the enzymatic activity of UGT94E13 through semirational design, and a variant UGT94E13-F169G/I185G was obtained with the catalytic activity improved by 13.90 times. A cascade reaction involving UGT94E13-F169G/I185G and sucrose synthase AtSuSy was established to recycle uridine diphosphate glucose, resulting in an efficient preparation of Reb M8 with a yield of 98%. Moreover, according to the analysis of the distances between the substrate Reb D and enzymes as well as between Reb D and the glucose donor through molecular dynamics simulations, it is found that the positive effect of shortening the distance on glycosylation reaction activity accounts for the improved catalytic activity of UGT94E13-F169G/I185G. Therefore, this study addresses the bottleneck in the efficient production of Reb M8 and provides a foundation for its widespread application in the food industry.

Modular assembly of an artificially concise biocatalytic cascade for the manufacture of phenethylisoquinoline alkaloids.

Plant-derived alkaloids are an important class of pharmaceuticals. However, they still rely on phytoextraction to meet their diverse market demands. Since multistep biocatalytic cascades have begun to revolutionize the manufacture of natural or unnatural products, to address the synthetic challenges of alkaloids, herein we establish an artificially concise four-enzyme biocatalytic cascade with avoiding plant-derived P450 modification for synthesizing phenethylisoquinoline alkaloids (PEIAs) after enzyme discovery and enzyme engineering. Efficient biosynthesis of diverse natural and unnatural PEIAs is realized from readily available substrates. Most importantly, the scale-up preparation of the colchicine precursor (S)-autumnaline with a high titer is achieved after replacing the rate-limiting O-methylation by the plug-and-play strategy. This study not only streamlines future engineering endeavors for colchicine biosynthesis, but also provides a paradigm for constructing more artificial biocatalytic cascades for the manufacture of diverse alkaloids through synthetic biology.

Research on predicting the diffusion of toxic heavy gas sulfur dioxide by applying a hybrid deep learning model to real case data.

Toxic heavy gas sulfur dioxide (SO2) is a specific life and environmental hazard. Predicting the diffusion of SO2 has become a research focus in fields such as environmental and safety studies. However, traditional methods, such as kinetic models, cannot balance precision and time. Thus, they do not meet the needs of emergency decision-making. Deep learning (DL) models are emerging as a highly regarded solution, providing faster and more accurate predictions of gas concentrations. To this end, this study proposes an innovative hybrid DL model, the parallel-connected convolutional neural network-gated recurrent unit (PC CNN-GRU). This model utilizes two CNNs connected in parallel to process gas release and meteorological datasets, enabling the automatic extraction of high-dimensional data features and handling of long-term temporal dependencies through the GRU. The proposed model demonstrates good performance (RMSE, MAE, and R2 of 20.1658, 10.9158, and 0.9288, respectively) with real data from the Project Prairie Grass (PPG) case. Meanwhile, to address the issue of limited availability of raw data, in this study, time series generative adversarial network (TimeGAN) are introduced for SO2 diffusion studies for the first time, and their effectiveness is verified. To enhance the practicality of the research, the contribution of drivers to SO2 diffusion is quantified through the utilization of the permutation importance (PIMP) and Sobol' method. Additionally, the maximum safe distance downwind under various conditions is visualized based on the SO2 toxicity endpoint concentration. The results of the analyses can provide a scientific basis for relevant decisions and measures.

Investigation of the Solubility of Elemental Sulfur (S) in Sulfur-Containing Natural Gas with Machine Learning Methods.

Some natural gases are toxic because they contain hydrogen sulfide (H2S). The solubility pattern of elemental sulfur (S) in toxic natural gas needs to be studied for environmental protection and life safety. Some methods (e.g., experiments) may pose safety risks. Measuring sulfur solubility using a machine learning (ML) method is fast and accurate. Considering the limited experimental data on sulfur solubility, this study used consensus nested cross-validation (cnCV) to obtain more information. The global search capability and learning efficiency of random forest (RF) and weighted least squares support vector machine (WLSSVM) models were enhanced via a whale optimization-genetic algorithm (WOA-GA). Hence, the WOA-GA-RF and WOA-GA-WLSSVM models were developed to accurately predict the solubility of sulfur and reveal its variation pattern. WOA-GA-RF outperformed six other similar models (e.g., RF model) and six other published studies (e.g., the model designed by Roberts et al.). Using the generic positional oligomer importance matrix (gPOIM), this study visualized the contribution of variables affecting sulfur solubility. The results show that temperature, pressure, and H2S content all have positive effects on sulfur solubility. Sulfur solubility significantly increases when the H2S content exceeds 10%, and other conditions (temperature, pressure) remain the same.

Intelligent identification of natural gas pipeline defects based on improved pollination algorithm.

As a natural gas pipeline approaches the end of its service life, the integrity of the pipeline starts failing because of corrosion or cracks. These and other defects affect the normal production and operation of the pipeline. Therefore, the identification of pipeline defects is critical to ensure the normal, safe, and efficient operation of these pipelines. In this study, a combination of adaptive adjustment based on conversion probability and Gaussian mutation strategy was used to improve the flower pollination algorithm (FPA) and enhance the search ability of traditional flower pollination. The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. A Gaussian mutation strategy was integrated with IFPA to optimise the initial input weights and thresholds of the extreme learning machine (ELM), improve the balance and exploration ability of the algorithm, and increase the efficiency and accuracy for identifying pipeline defects. The proposed IFPA-ELM model for pipeline defect identification effectively overcomes the tendency of FPA to converge to local optima and that of ELM to engage in overfitting, which cause poor recognition accuracy. The identification rates of various pipeline defects by the IFPA-ELM algorithm are 97% and 96%, which are 34% and 13% higher, respectively, than those of FPA and FPA-ELM. The IFPA-ELM model may be used in the intelligent diagnosis of pipeline defects to solve practical engineering problems. Additionally, IFPA could be further optimised with respect to the time dimension, parameter settings, and general adaptation for application to complex engineering optimisation problems in various fields.

Kluyveromyces as promising yeast cell factories for industrial bioproduction: From bio-functional design to applications.

As the two most widely used Kluyveromyces yeast, Kluyveromyces marxianus and K. lactis have gained increasing attention as microbial chassis in biocatalysts, biomanufacturing and the utilization of low-cost raw materials owing to their high suitability to these applications. However, due to slow progress in the development of molecular genetic manipulation tools and synthetic biology strategies, Kluyveromyces yeast cell factories as biological manufacturing platforms have not been fully developed. In this review, we provide a comprehensive overview of the attractive characteristics and applications of Kluyveromyces cell factories, with special emphasis on the development of molecular genetic manipulation tools and systems engineering strategies for synthetic biology. In addition, future avenues in the development of Kluyveromyces cell factories for the utilization of simple carbon compounds as substrates, the dynamic regulation of metabolic pathways, and for rapid directed evolution of robust strains are proposed. We expect that more synthetic systems, synthetic biology tools and metabolic engineering strategies will adapt to and optimize for Kluyveromyces cell factories to achieve green biofabrication of multiple products with higher efficiency.

Based on abnormal fluctuations in user-side flow simulation analysis of low- and medium-pressure gas pipeline leakage monitoring.

Due to the weak monitoring equipment for low- and medium-pressure gas pipelines, it is not easy to identify small flow leaks. The detection methods are mostly traditional manual inspections or night pressure-maintaining leak detection methods, which cannot be automatically monitored and sensed immediately. The abnormal fluctuations in client traffic caused by pipeline leaks studied in this paper can locate and detect leak locations more effectively. This paper analyzes the theoretical formula of leakage location based on flow data and finds out how to use the abnormal fluctuation of user-side flow to detect and locate gas pipeline leakage. First of all, this article uses the simulation software Pipeline Studio to construct the medium and low-pressure pipeline model. On this basis, 6 sets of leakage conditions were designed and simulated dynamically. Finally, the simulation results are analyzed, and the results show that: 1) The advisable monitoring period for monitoring abnormal fluctuations of user-side traffic is 10s. 2) There are two relationships between abnormal flow fluctuations and leakage position. They are: when the leakage point is at the first 40% of the relative distance from the gas source, the disturbance amplitude first increases and then decreases, and at the last 60%, it continues to decrease.; The closer the leak is to the user end, the more significant the abnormal flow fluctuations will be. On the contrary, the smaller the abnormal flow fluctuations will be; 3) No matter where the leakage occurs, the abnormal flow fluctuations in the 2nd and 3rd seconds after the leak occurs tend to be consistent. The proposal of the advisable monitoring period and the relationship between abnormal fluctuations of flow and the location of leakage provides a theoretical basis for the use of abnormal fluctuations of user-side flow for gas pipeline leakage detection and location.

Systematic engineering of Bacillus amyloliquefaciens for efficient production of poly-γ-glutamic acid from crude glycerol.

Microbial production of poly-γ-glutamic acid (γ-PGA) from non-food raw materials is a promising alternative to food feedstocks-based biosynthesis. A superior cell factory of Bacillus amyloliquefaciens for the efficient synthesis of γ-PGA from crude glycerol was constructed through systematic metabolic engineering. Firstly, some phase-dependent promoters were screened from B. amyloliquefaciens, which can be used for fine regulation of subsequent metabolic pathways. Secondly, the glycerol utilization pathway and the γ-PGA synthesis pathway were co-optimized utilizing the above-screened promoters, which increased the titer of γ-PGA by 1.75-fold. Then, the titer of γ-PGA increased to 15.6 g/L by engineering transcription factors degU and blocking competitive pathways. Finally, combining these strategies with an optimized fermentation process, 26.4 g/L γ-PGA was obtained from crude glycerol as a single carbon source (a 3.72-fold improvement over the initial strain). Overall, these strategies will have great potential for synthesizing other products from crude glycerol in B. amyloliquefaciens.