Engineering NAD+ availability for Escherichia coli whole-cell biocatalysis: A case study for dihydroxyacetone production

Background: Whole-cell redox biocatalysis has been intensively explored for the production of valuable compounds because excellent selectivity is routinely achieved. Although the cellular cofactor level, redox state and the corresponding enzymatic activity are expected to have major effects on the performance of the biocatalysts, our ability remains limited to predict the outcome upon variation of those factors as well as the relationship among them. Results: In order to investigate the effects of cofactor availability on whole-cell redox biocatalysis, we devised recombinant Escherichia coli strains for the production of dihydroxyacetone (DHA) catalyzed by the NAD + -dependent glycerol dehydrogenase (GldA). In this model system, a water-forming NAD + oxidase (NOX) and a NAD + transporter (NTT4) were also co-expressed for cofactor regeneration and extracellular NAD + uptake, respectively. We found that cellular cofactor level, NAD + /NADH ratio and NOX activity were not only strain-dependent, but also growth condition-dependent, leading to significant differences in specific DHA titer among different whole-cell biocatalysts. The host E. coli DH5α had the highest DHA specific titer of 0.81\ua0g/g DCW with the highest NAD + /NADH ratio of 6.7 and NOX activity of 3900 U. The biocatalyst had a higher activity when induced with IPTG at 37\ub0C for 8\ua0h compared with those at 30\ub0C for 8\ua0h and 18\ua0h. When cells were transformed with the ntt4 gene, feeding NAD + during the cell culture stage increased cellular NAD(H) level by 1.44 fold and DHA specific titer by 1.58 fold to 2.13\ua0g/g DCW . Supplementing NAD + during the biotransformation stage was also beneficial to cellular NAD(H) level and DHA production, and the highest DHA productivity reached 0.76\ua0g/g DCW /h. Cellular NAD(H) level, NAD + /NADH ratio, and NOX and GldA activity dropped over time during the biotransformation process.Conclusions: High NAD + /NADH ratio driving by NOX was very important for DHA production. Once cofactor was efficiently cycled, high cellular NAD(H) level was also beneficial for whole-cell redox biocatalysis. Our results indicated that NAD + transporter could be applied to manipulate redox cofactor level for biocatalysis. Moreover, we suggested that genetically designed redox transformation should be carefully profiled for further optimizing whole-cell biocatalysis. \ua9 2013 Zhou et al.; licensee BioMed Central Ltd

Semitransparent Perovskite Solar Cells with an Evaporated Ultra-Thin Perovskite Absorber

Metal halide perovskites are of great interest for application in semitransparent solar cells due to their tunable bandgap and high performance. However, fabricating high-efficiency perovskite semitransparent devices with high average visible transmittance (AVT) is challenging because of their high absorption coefficient. Here, a co-evaporation process is adopted to fabricate ultra-thin CsPbI3 perovskite films. The smooth surface and orientated crystal growth of the evaporated perovskite films make it possible to achieve 10 nm thin films with compact and continuous morphology without pinholes. When integrated into a p-i-n device structure of glass/ITO/PTAA/perovskite/PCBM/BCP/Al/Ag with an optimized transparent electrode, these ultra-thin layers result in an impressive open-circuit voltage (VOC) of 1.08 V and a fill factor (FF) of 80%. Consequently, a power conversion efficiency (PCE) of 3.6% with an AVT above 50% is demonstrated, which is the first report for a perovskite device of a 10 nm active layer thickness with high VOC, FF and AVT. These findings demonstrate that deposition by thermal evaporation makes it possible to form compact ultra-thin perovskite films, which are of great interest for future smart windows, light-emitting diodes, and tandem device applications

A Lipoprotein Lipase–Promoting Agent, NO-1886, Improves Glucose and Lipid Metabolism in High Fat, High Sucrose–Fed New Zealand White Rabbits

The synthetic compound NO-1886 is a lipoprotein lipase activator that lowers plasma triglycerides and elevates high-density lipoprotein cholesterol (HDL-C). Recently, the authors found that NO-1886 also had an action of reducing plasma glucose in high-fat/high-sucrose diet–induced diabetic rabbits. In the current study, we investigated the effects of NO-1886 on insulin resistance and β-cell function in rabbits. Our results showed that high-fat/high-sucrose feeding increased plasma triglyceride, free fatty acid (FFA), and glucose levels and decreased HDL-C level. This diet also induced insulin resistance and impairment of acute insulin response to glucose loading. Supplementing 1% NO-1886 into the high-fat/high-sucrose diet resulted in decreased plasma triglyceride, FFA, and glucose levels and increased HDL-C level. The authors also found a clear increased glucose clearance and a protected acute insulin response to intravenous glucose loading by NO-1886 supplementation. These data suggest that NO-1886 suppresses the elevation of blood glucose in rabbits induced by feeding a high-fat/high-sucrose diet, probably through controlling lipid metabolism and improving insulin resistance

Modularly engineering Rhodotorula toruloides for α-terpineol production

α-Terpineol is a monoterpenoid alcohol that has been widely used in the flavor, fragrance, and pharmaceutical industries because of its sensory and biological properties. However, few studies have focused on the microbial production of α-terpineol. The oleaginous yeast Rhodotorula toruloides is endowed with a natural mevalonate pathway and is a promising host in synthetic biology and biorefinery. The primary objective of this work was to engineer R. toruloides for the direct biosynthesis of α-terpineol. The improvement in monoterpenoid production was achieved through the implementation of modular engineering strategies, which included the enhancement of precursor supply, blocking of downstream pathways, and disruption of competing pathways. The results of these three methods showed varying degrees of favorable outcomes in enhancing α-terpineol production. The engineered strain 5L6HE5, with competitive pathway disruption and increased substrate supply, reached the highest product titer of 1.5 mg/L, indicating that reducing lipid accumulation is an efficient method in R. toruloides engineering for terpenoid synthesis. This study reveals the potential of R. toruloides as a host platform for the synthesis of α-terpineol as well as other monoterpenoid compounds

Amine-responsive bilayer films with improved illumination stability and electrochemical writing property for visual monitoring of meat spoilage

Amine-responsive bilayer films were developed by using agar (AG), anthocyanins (AN), gellan gum (GG) and TiO2 nanoparticles for visual monitoring of meat spoilage. The AG-AN layer worked as the sensing layer to volatile amines, while GG-TiO2 layer served as the light barrier layer and simultaneously the conducting layer to improve the illumination stability and electrochemical writing ability of the AG-AN layer, respectively. The Scanning electron microscopy (SEM) images and X-ray diffraction (XRD) spectra indicated the successful fabrication of bilayer films. Illumination experiments showed that the incorporation of TiO2 in the GG-TiO2 layer significantly improved the illumination stability of AN in the AG-AN layer. Meanwhile, electrochemical writing process could be easily conducted on the AG-AN layer in the presence of GG-TiO2 layer, indicating the feasibility of ink-free printing on bilayer biopolymer films. The AG-AN/GG-2%TiO2 film presented a limit of detection of 0.018 mM to trimethylamine (TMA), a typical basic gas generated during meat spoilage. Based on its good illumination stability and sensing ability to basic gases, the AG-AN/GG-2%TiO2 film exhibited rose red-to-green color changes along with the spoilage of pork and silver carp, indicating its great potential for monitoring meat spoilage in intelligent food packaging

Prediction of stability coefficient of open-pit mine slope based on artificial intelligence deep learning algorithm

Abstract The mining of open pit mines is widespread in China, and there are many cases of landslide accidents. Therefore, the problem of slope stability is highlighted. The stability of the slope is a factor that directly affects the mining efficiency and the safety of the entire mining process. According to the statistics, there is a 15 percent chance of finding landslide risk in China’s large-scale mines. And due to the expansion of the mining scale of the enterprise, the problem of slope stability has become increasingly obvious, which has become a major subject in the study of open-pit mine engineering. In order to better predict the slope stability coefficient, this study takes a mine in China as a case to deeply discuss the accuracy of different algorithms in the stability calculation, and then uses a deep learning algorithm to study the stability under rainfall conditions. The change of the coefficient and the change of the stability coefficient before and after the slope treatment are experimentally studied with the displacement of the monitoring point. The result shows that the safety coefficient calculated by the algorithm in this paper is about 7% lower than that of the traditional algorithm. In the slope stability analysis before treatment, the safety factor calculated by the algorithm in this paper is 1.086, and the algorithm in this paper is closer to reality. In the stability analysis of the slope after treatment, the safety factor calculated by the algorithm in this paper is 1.227, and the stability factor meets the requirements of the specification. It also shows that the deep learning algorithm effectively improves the efficiency of the slope stability factor prediction and improves security during project development

Nucleophilic Trapping Nitrilimine Generated by Photolysis of Diaryltetrazole in Aqueous Phase

Nitrilimine generated by photolysis of diaryltetrazole in aqueous phase under mild conditions was trapped by nucleophiles including amines and thioalcohols. The representative products were characterized, while products with all 20 natural amino acids and a peptide were observed by MALDI-TOF mass spectroscopy. Competitive studies showed that this reaction also occurred in the presence of acrylamide. These results provided new information for understanding the potential side reactions when tetrazole-alkene pairs were used as a bioorthogonal reaction in labeling proteins and related studies in buffered systems

Enhancing building energy efficiency using a random forest model: a hybrid prediction approach

The building envelope considerably influences building energy consumption. To enhance the energy efficiency of buildings, this paper proposes an approach to predict building energy consumption based on the design of the building envelope. The design parameters of the building envelope include the comprehensive heat transfer coefficient and solar radiation absorption coefficient of exterior walls, comprehensive heat transfer coefficient and solar radiation absorption coefficient of the roof, comprehensive heat transfer coefficient of outer windows, and window-wall ratio. The approach is applied to optimize the design parameters of the building envelope structure of a university teaching building in northern China. First, a building information model of a teaching building is established in Revit and imported into DesignBuilder energy consumption analysis software. Subsequently, a data set of the abovementioned 6 parameters is obtained by performing orthogonal testing and energy consumption simulations. On this basis, an RF model is used to predict building energy consumption and rank the importance of each parameter, and the Pearson function is used to evaluate the corresponding correlations. The results show that the most important parameters with the highest correlations to building energy consumption are the comprehensive heat transfer coefficients of the exterior walls and outer windows and the window-wall ratio. Finally, the RF prediction results are compared to the prediction results of a BP artificial neural network (BP-ANN) and support vector machine (SVM). The findings indicate that the RF model exhibits notable advantages in building energy consumption prediction and is the optimal prediction model among the compared models.Published versionThis work was supported by the Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund, Project CXPY2020013, the Construction of Science and Technology Plan Project of Hubei Province (Grant No. 202041), and the National Natural Science Foundation of China (Grant No. 72031009)

Investigation of Micro-Bending of Sheet Metal Laminates by Laser-Driven Soft Punch in Warm Conditions

Microscale laser dynamic flexible forming (µLDFF) is a novel ultrahigh strain rate manufacturing technology with high efficiency and low cost. However, the µLDFF is just confined to single-layer foil at present. In this work, sheet metal laminates (Cu/Ni) were selected as the experimental material for its excellent mechanical and functional properties, and a new micro-bending method of sheet metal laminates by laser-driven soft punch was proposed in warm conditions. The micro-mold and warm platform were designed to investigate the effects of temperature and energy on formability, which were characterized by forming accuracy, surface quality, element diffusion, and so on. The experimental results show that the forming accuracy and quality increased first and then decreased with laser energy, but the hardness increased consistently. In warm conditions, the fluidity of material was improved. The forming depth and accuracy increased for the relieved springback, and the surface quality increased first and then decreased. The tensile fracture disappeared with temperature for the decreased hardness and thinning ratio, and the element diffusion occurred. Overall, this study indicates that the formability can be improved in warm conditions and provides a basis for the investigation of micro-bending of sheet metal laminates by µLDFF in warm conditions

PCR-based strategy for construction of multi-site-saturation mutagenic expression library

There is an increasing demand for efficient and effective methods to engineer protein variants for industrial applications, structural biology and drug development. We describe a PCR-based strategy that produces multi-site-saturation mutagenic expression library using a circular plasmid carrying the wild-type gene. This restriction digestion- and ligation-independent method involves three steps: 1) synthesis of the degenerate oligonucleotide primers, 2) incorporation of the mutations through PCR, 3) transformation into the expression host. Our strategy is demonstrated through successful construction of an E coli K12 malic enzyme expression library that contains members with simultaneous mutations on amino acid residues G311, D345 and G397. This method is in principle compatible with any circular vector that can be propagated with a dam(+) E. coli host to generate protein variant library with multiple changes, including mutation, short sequence deletion and insertion, or any mix of them. (c) 2007 Elsevier B.V All rights reserved