Synergistic application of atmospheric and room temperature plasma mutagenesis and adaptive laboratory evolution improves the tolerance of Escherichia coli to L-cysteine.

L-Cysteine production through fermentation stands as a promising technology. However, excessive accumulation of L-cysteine poses a challenge due to the potential to inflict damage on cellular DNA. In this study, we employed a synergistic approach encompassing atmospheric and room temperature plasma mutagenesis (ARTP) and adaptive laboratory evolution (ALE) to improve L-cysteine tolerance in Escherichia coli. ARTP-treated populations obtained substantial enhancement in L-cysteine tolerance by ALE. Whole-genome sequencing, transcription analysis, and reverse engineering, revealed the pivotal role of an effective export mechanism mediated by gene eamB in augmenting L-cysteine resistance. The isolated tolerant strain, 60AP03/pTrc-cysEf , achieved a 2.2-fold increase in L-cysteine titer by overexpressing the critical gene cysEf during batch fermentation, underscoring its enormous potential for L-cysteine production. The production evaluations, supplemented with L-serine, further demonstrated the stability and superiority of tolerant strains in L-cysteine production. Overall, our work highlighted the substantial impact of the combined ARTP and ALE strategy in increasing the tolerance of E. coli to L-cysteine, providing valuable insights into improving L-cysteine overproduction, and further emphasized the potential of biotechnology in industrial production.

Combinatorial Metabolic Engineering of Escherichia coli for Enhanced L-Cysteine Production: Insights into Crucial Regulatory Modes and Optimization of Carbon-Sulfur Metabolism and Cofactor Availability.

Microbial production of valuable compounds can be enhanced by various metabolic strategies. This study proposed combinatorial metabolic engineering to develop an effective Escherichia coli cell factory dedicated to L-cysteine production. First, the crucial regulatory modes that control L-cysteine levels were investigated to guide metabolic modifications. A two-stage fermentation was achieved by employing multi-copy gene expression, improving the balance between production and growth. Subsequently, carbon flux distribution was further optimized by modifying the C1 unit metabolism and the glycolytic pathway. The modifications of sulfur assimilation demonstrated superior performance of thiosulfate utilization pathways in enhancing L-cysteine titer. Furthermore, the studies focusing on cofactor availability and preference emphasized the vital role of synergistic enhancement of sulfur-carbon metabolism in L-cysteine overproduction. In a 5 L bioreactor, the strain BW15-3/pED accumulated 12.6 g/L of L-cysteine. This work presented an effective metabolic engineering strategy for the development of L-cysteine-producing strains.

Spatiotemporal Gene Expression by a Genetic Circuit for Chemical Production in Escherichia coli.

Gene expression in spatiotemporal distribution improves the ability of cells to respond to changing environments. For microbial cell factories in artificial environments, reconstruction of the target compound's biosynthetic pathway in a new spatiotemporal dimension/scale promotes the production of chemicals. Here, a genetic circuit based on the Esa quorum sensing and lac operon was designed to achieve the dynamic temporal gene expression. Meanwhile, the pathway was regulated by an l-cysteine-specific sensor and relocalized to the plasma membrane for further flux enhancement to l-cysteine and toxicity reduction on a spatial scale. Finally, the integrated spatiotemporal regulation circuit for l-cysteine biosynthesis enabled a 14.16 g/L l-cysteine yield in Escherichia coli. Furthermore, this spatiotemporal regulation circuit was also applied in our previously constructed engineered strain for pantothenic acid, methionine, homoserine, and 2-aminobutyric acid production, and the titer increased by 29, 33, 28, and 41%, respectively. These results highlighted the applicability of our spatiotemporal regulation circuit to enhance the performance of microbial cell factories.

Application of Non-Aflatoxigenic Aspergillus flavus for the Biological Control of Aflatoxin Contamination in China.

Biological control through the application of competitive non-aflatoxigenic Aspergillus flavus (A. flavus) to the soil during peanut growth is a practical method for controlling aflatoxin contamination. However, appropriate materials need to be found to reduce the cost of biocontrol products. In this study, a two-year experiment was conducted under field conditions in China, using a native non-aflatoxigenic strain to explore its effect. After three months of storage under high humidity, aflatoxin levels remained low in peanuts from fields treated with the biocontrol agent. Three types of substrates were tested with the biocontrol agent: rice grains, peanut meal (peanut meal fertilizer) and peanut coating. Compared to untreated fields, these formulations resulted in reductions of 78.23%, 67.54% and 38.48%, respectively. Furthermore, the ratios of non-aflatoxigenic A. flavus recovered in the soils at harvest in the treated fields were between 41.11% and 96.67% higher than that in untreated fields (25.00%), indicating that the rice inoculum was the most effective, followed by the peanut meal fertilizer and peanut coating. In 2019, the mean aflatoxin content of freshly harvested peanuts in untreated fields was 19.35 µg/kg higher than that in the fields treated with 7.5 kg/ha rice inoculum, which was 1.37 µg/kg. Moreover, no aflatoxin was detected in the two other plots treated with 10 and 15 kg/ha rice inoculum. This study showed that the native Chinese non-aflatoxigenic strain of A. flavus (18PAsp-zy1) had the potential to reduce aflatoxin contamination in peanuts. In addition, peanut meal can be used as an alternative substrate to replace traditional grains, reducing the cost of biocontrol products.

Control Method for Continuous Grain Drying Based on Equivalent Accumulated Temperature Mechanism and Artificial Intelligence.

Grain drying is a complex heat and mass transfer process, which has the characteristics of a significant delay, multidisturbance, nonlinearity, strong coupling, and parameter uncertainty. Artificial intelligence (AI) control technology is suitable for solving such complex control problems. In this paper, the mechanism and data dual-drive with equivalent accumulated temperature (EAT) mutual-window AI-control method for continuous grain drying were proposed, and a control system was established. The experimental verification was carried out on the test platform of continuous grain drying. The results show that the method has the ability of implicit prediction, high accuracy, strong stability and self-adaptive ability, and the maximum control deviation of moisture at the outlet of the dryer is -0.58-0.3%.

[Construction of an l-cysteine hyper-producing strain of Escherichia coli based on a balanced carbon and sulfur module strategy].

l-cysteine is an important sulfur-containing α-amino acid. It exhibits multiple physiological functions with diverse applications in pharmaceutical cosmetics and food industry. Here, a strategy of coordinated gene expression between carbon and sulfur modules in Escherichia coli was proposed and conducted for the production of l-cysteine. Initially, the titer of l-cysteine was improved to (0.38±0.02) g/L from zero by enhancing the biosynthesis of l-serine module (serAf, serB and serCCg) and overexpression of CysB. Then, promotion of l-cysteine transporter, increased assimilation of sulfur, reduction or deletion of l-cysteine and l-serine degradation pathway and enhanced expression of cysEf (encoding serine acetyltransferase) and cysBSt (encoding transcriptional dual regulator CysB) were achieved, resulting in an improved l-cysteine titer (3.82±0.01) g/L. Subsequently, expressions of cysM, nrdH, cysK and cysIJ genes that were involved in sulfur module were regulated synergistically with carbon module combined with utilization of sulfate and thiosulfate, resulting in a strain producing (4.17±0.07) g/L l-cysteine in flask shake and (11.94±0.1) g/L l-cysteine in 2 L bioreactor. Our results indicated that efficient biosynthesis of l-cysteine could be achieved by a proportional supply of sulfur and carbon in vivo. This study would facilitate the commercial bioproduction of l-cysteine.

In vitro antitumor effect of cucurbitacin E on human lung cancer cell line and its molecular mechanism.

Cucurbitacin E (CuE) is previously reported to exhibit antitumor effect by several means. In this study, CuE acted as a tyrosine kinase inhibitor interfering with the epidermal growth factor receptor/mitogen-activated protein kinase (EGFR/MAPK) signaling pathway and subsequently induced apoptosis and cell cycle arrest in non-small-cell lung cancer (NSCLC) cell line A549. The apoptosis regulators, cleaved Caspases-3 and Caspases-9, were observed to be increased with the treatment of CuE. The activated transcription factor STAT3 and the apoptosis inhibitor protein survivin were also observed to be reduced. The cell cycle regulators, CyclinA2, cylinB1, CyclinD1 and CyclinE, were also investigated and the results suggested that the cell cycle was arrested at G1/G0 phase. Treatment of CuE also altered the existence status of most of the participants in the EGFR/MAPK signaling. Phosphorylation of EGFR enhanced significantly, leading to the alteration of members downstream, either total amount or phosphorylation level, notably, MEK1/2 and ERK1/2. Moreover, the results of molecular simulation brought an insight on the interaction mechanism between CuE and EGFR. In summary, CuE exhibited anti-proliferative effect against A549 cells by targeting the EGFR/MAPK signaling pathway.

Design of an intelligent controller for a grain dryer: A support vector machines for regression inverse model proportional-integral-derivative controller.

Grain drying control is a challenging task owing to the complex heat and mass exchange process. To precisely control the outlet grain moisture content (MC) of a continuous mixed-flow grain dryer, in this paper, we proposed a genetically optimized inverse model proportional-integral-derivative (PID) controller based on support vector machines for regression algorithm which is named the GO-SVR-IMCPID controller. The structure of the GO-SVR-IMCPID controller consists of a genetic optimization algorithm, an indirect inverse model predictive controller, and a PID controller. In addition, to verify the control performances of the proposed controller in the simulation study, we have established a nonlinear mathematical model for the mixed-flow grain dryer to represent the nonlinear grain drying process. Finally, the control performance and the robustness of the GO-SVR-IMCPID controller were simulated and compared with the other controllers. By the simulation results, it is shown that this proposed algorithm can track the target value precisely and has fewer steady errors and strong ability of anti-interference. Furthermore, it has further confirmed the superiority of the proposed grain drying controller by comparing it with the other controllers.

Thermosensitive Hydrogel for Encapsulation and Controlled Release of Biocontrol Agents to Prevent Peanut Aflatoxin Contamination.

Starch, alginate, and poly(N-isopropylacrylamide) (PNIPAAm) were combined to prepare a semi-interpenetrating network (IPN) hydrogel with temperature sensitivity. Calcium chloride was used as cross-linking agent, the non-toxigenic Aspergillus flavus spores were successfully encapsulated as biocontrol agents by the method of ionic gelation. Characterization of the hydrogel was performed by Fourier-transform infrared spectroscopy (FTIR), scanning electron micrograph (SEM), and thermogravimetry analysis (TGA). Formulation characteristics, such as entrapment efficiency, beads size, swelling behavior, and rheological properties were evaluated. The optical and rheological measurements indicated that the lower critical solution temperature (LCST) of the samples was about 29-30 °C. TGA results demonstrated that the addition of kaolin could improve the thermal stability of the semi-IPN hydrogel. Morphological analysis showed a porous honeycomb structure on the surface of the beads. According to the release properties of the beads, the semi-IPN hydrogel beads containing kaolin not only have the effect of slow release before peanut flowering, but they also can rapidly release biocontrol agents after flowering begins. The early flowering stage of the peanut is the critical moment to apply biocontrol agents. Temperature-sensitive hydrogel beads containing kaolin could be considered as carriers of biocontrol agents for the control of aflatoxin in peanuts.

A Novel, Portable and Fast Moisture Content Measuring Method for Grains Based on an Ultra-Wideband (UWB) Radar Module and the Mode Matching Method.

To perform fast and portable grain moisture measurements under field conditions, a novel moisture sensor was designed, which consisted of a coaxial waveguide, a circular waveguide, and an isolation layer. The electromagnetic characteristics of the sensor were simulated and measured. The analytical model, which represented the relationship between the reflection coefficient of the sensor and the complex permittivity of grain, was established by using the mode matching method. The reflection coefficient of the sensor was measured by using an ultra-wideband (UWB) radar module, and the moisture content of grains was calculated from the complex permittivity by using density-independent model. To verify the performance of the proposed method, wheat, rough rice, and barley were taken as examples. The measured results in the range from 1.0% to 26.0%, wet basis, agreed well with the reference values (R2 was more than 0.99), and the maximum absolute errors for wheat, rough rice, and barley were 1.1%, 1.0%, and 1.4%, respectively. In addition, the effect of isolation layer was discussed. Both the simulation results and the experimental results showed that the isolation layer improved the stability of sensor.

Controlled Release of Biological Control Agents for Preventing Aflatoxin Contamination from Starch⁻Alginate Beads.

For the wise use of fungal biocontrol and metalaxyl fungicide, starch-alginate-based formulations have been developed by encapsulating metalaxyl and non-toxigenic Aspergillus flavus spores simultaneously in the form of microspheres using calcium chloride as a cross-linking agent. The formulations were characterized by Fourier transform infrared spectroscopy (FTIR), a scanning electron micrograph (SEM), and thermogravimetry (TGA). Formulation characteristics, including the bead size, entrapment efficiency, swelling ratio of the beads, and rheological properties, were analyzed. The release behavior of beads with different formulations was evaluated. The addition of kaolin and rice husk powder in starch-alginate beads retarded the release profile of spores and metalaxyl. The release of the active ingredient from starch-alginate-kaolin beads and starch-alginate-rice husk powder beads occurred in both a controlled and sustained manner. Additionally, the release rate decreased with the increase of kaolin or rice husk powder content. The beads added with kaolin were slower than the release of rice husk powder. In comparison, spores released slower and lasted longer than metalaxyl. The starch-alginate-kaolin formulations could be used as controlled release material in the field of biocontrol and reduce the harm of fungicides to the environment.

Optimization and validation of the protocol used to analyze the taste of traditional Chinese medicines using an electronic tongue.

Tools to define the active ingredients and flavors of Traditional Chinese Medicines (TCMs) are limited by long analysis times, complex sample preparation and a lack of multiplexed analysis. The aim of the present study was to optimize and validate an electronic tongue (E-tongue) methodology to analyze the bitterness of TCMs. To test the protocol, 35 different TCM concoctions were measured using an E-tongue, and seven replicate measurements of each sample were taken to evaluate reproducibility and precision. E-tongue sensor information was identified and classified using analysis approaches including least squares support vector machine (LS-SVM), support vector machine (SVM), discriminant analysis (DA) and partial least squares (PLS). A benefit of this analytical protocol was that the analysis of a single sample took <15 min for all seven sensors. The results identified that the LS-SVM approach provided the best bitterness classification accuracy (binary classification accuracy, 100%; ternary classification accuracy, 89.66%). The E-tongue protocol developed showed good reproducibility and high precision within a 6 h measurement cycle. To the best of our knowledge, this is the first study of an E-tongue being applied to assay the bitterness of TCMs. This approach could be applied in the classification of the taste of TCMs, and serve important roles in other fields, including foods and beverages.

Evaluation of the Bitterness of Traditional Chinese Medicines using an E-Tongue Coupled with a Robust Partial Least Squares Regression Method.

To accurately, safely, and efficiently evaluate the bitterness of Traditional Chinese Medicines (TCMs), a robust predictor was developed using robust partial least squares (RPLS) regression method based on data obtained from an electronic tongue (e-tongue) system. The data quality was verified by the Grubb's test. Moreover, potential outliers were detected based on both the standardized residual and score distance calculated for each sample. The performance of RPLS on the dataset before and after outlier detection was compared to other state-of-the-art methods including multivariate linear regression, least squares support vector machine, and the plain partial least squares regression. Both R² and root-mean-squares error (RMSE) of cross-validation (CV) were recorded for each model. With four latent variables, a robust RMSECV value of 0.3916 with bitterness values ranging from 0.63 to 4.78 were obtained for the RPLS model that was constructed based on the dataset including outliers. Meanwhile, the RMSECV, which was calculated using the models constructed by other methods, was larger than that of the RPLS model. After six outliers were excluded, the performance of all benchmark methods markedly improved, but the difference between the RPLS model constructed before and after outlier exclusion was negligible. In conclusion, the bitterness of TCM decoctions can be accurately evaluated with the RPLS model constructed using e-tongue data.

Degradation of ochratoxin A by Bacillus amyloliquefaciens ASAG1.

Ochratoxin A (OTA) is widely found in food and feed products as a mycotoxin contaminant. It is produced by Penicillium species and several Aspergillus species. The identification OTA detoxification microorganisms is believed to be the best approach for decontamination. In this study, we isolated ASAG1, a bacterium with the ability to degrade OTA effectively, from grain depot-stored maize. A 16S rDNA sequencing approach was used to identify this strain as Bacillus amyloliquefaciens ASAG1. The degradation of OTA was detected in both medium and cell-free extracts after incubation with a culture of B. amyloliquefaciens ASAG1 cells. Subsequently, a hydrolysed enzyme (carboxypeptidase) related to the enzymatic conversion of OTA was cloned from the B. amyloliquefaciens ASAG1 genome. Using the Escherichia coli Expression System, we successfully expressed and purified this carboxypeptidase. When this enzyme was incubated with the engineered recombinant E. coli cells, the concentration of OTA was dramatically degraded. Our data therefore indicate that the carboxypeptidase produced by B. amyloliquefaciens ASAG1 is likely responsible for the biodegradation of OTA.