A Novel Process for Cadaverine Bio-Production Using a Consortium of Two Engineered Escherichia coli

Bio-production of cadaverine from cheap carbon sources for synthesizing bio-based polyamides is becoming more common. Here, a novel fermentation process for cadaverine bio-production from glucose was implemented by using a microbial consortium of two engineered Escherichia coli strains to relieve the toxic effect of cadaverine on fermentation efficiency. To achieve controllable growth of strains in the microbial consortium, two engineered E. coli strains grown separately on different carbon sources were first constructed. The strains were, an L-lysine-producing E. coli NT1004 with glucose as carbon source, and a cadaverine-producing E. coli CAD03 with glucose metabolism deficiency generated by modifying the PTSGlc system with CRISPR-Cas9 technology and inactivating cadaverine degradation pathways. Co-culturing these two engineered E. coli strains with a mixture of glucose and glycerol led to successful production of cadaverine. After optimizing cultivation conditions, a cadaverine titer of 28.5 g/L was achieved with a multi-stage constant-speed feeding strategy

Impeded Nedd4-1-Mediated Ras Degradation Underlies Ras-Driven Tumorigenesis

RAS genes are among the most frequently mutated proto-oncogenes in cancer. However, how Ras stability is regulated remains largely unknown. Here, we report a regulatory loop involving the E3 ligase Nedd4-1, Ras, and PTEN. We found that Ras signaling stimulates the expression of Nedd4-1, which in turn acts as an E3 ubiquitin ligase that regulates Ras levels. Importantly, Ras activation, either by oncogenic mutations or by epidermal growth factor (EGF) signaling, prevents Nedd4-1-mediated Ras ubiquitination. This leads to Ras-induced Nedd4-1 overexpression, and subsequent degradation of the tumor suppressor PTEN in both human cancer samples and cancer cells. Our study thus unravels the molecular mechanisms underlying the interplay of Ras, Nedd4-1, and PTEN and suggests a basis for the high prevalence of Ras-activating mutations and EGF hypersignaling in cancer. © 2014 The Authors

Synthesis of zirconolite-2M ceramics for immobilisation of neptunium

Praseodymium-doped zirconolite ceramics targeting nominal composition Ca1-xPrxZrTi2-5x/3Al5x/3O7 (x ≤ 0.20, Δx = 0.05) were fabricated by a mixed oxide solid state reaction, at 1350 °C in air for 20 h. Praseodymium (Pr) was employed as a surrogate for neptunium (Np), with Al3+ co-accommodated to provide charge balance. High-resolution transmission electron microscopy and electron diffraction analyses confirmed that zirconolite crystallised as the 2 M monoclinic polytype throughout the phase evolution, with no evidence of transformation to other polytype structures. Phase assemblage and microstructural data were consistent with zirconolite occupying a high fraction of the phase assemblage (>ca. 93 wt %), alongside a minor secondary perovskite phase at all levels of targeted Pr incorporation. Despite this, it was demonstrated near theoretical density formed through a solid-state fabrication route, and we therefore propose that, through analogy with the corresponding Pr solid solution, zirconolite may be a suitable candidate for the immobilisation of Np-bearing wastes

A Surrogate Model Based Multi-Objective Optimization Method for Optical Imaging System

An optimization model for the optical imaging system was established in this paper. It combined the modern design of experiments (DOE) method known as Latin hypercube sampling (LHS), Kriging surrogate model training, and the multi-objective optimization algorithm NSGA-III into the optimization of a triplet optical system. Compared with the methods that rely mainly on optical system simulation, this surrogate model-based multi-objective optimization method can achieve a high-accuracy result with significantly improved optimization efficiency. Using this model, case studies were carried out for two-objective optimizations of a Cooke triplet optical system. The results showed that the weighted geometric spot diagram and the maximum field curvature were reduced 5.32% and 11.59%, respectively, in the first case. In the second case, where the initial parameters were already optimized by Code-V, this model further reduced the weighted geometric spot diagram and the maximum field curvature by another 3.53% and 4.33%, respectively. The imaging quality in both cases was considerably improved compared with the initial design, indicating that the model is suitable for the optimal design of an optical system

Adaptive step-size forward advection method for aerosol process simulation

Outdoor aerosol processes are often associated with disasters and diseases, which threaten human life and health. Outdoor aerosols are a fluid system affected by meteorological conditions and three-dimensional complex terrain. Their variable wind speed and direction and complex terrain boundary conditions make simulating advection processes difficult. Based on incompressible flow conditions, we designed an adaptive time step algorithm for forward advection for the rapid simulation of aerosol processes. The method is based on the first-order forward semi-Lagrangian advection method with unconditional mass conservation. The first-order truncated error coefficient function theory generates an adaptive time step to control the accuracy of forward advection. Smoke aerosol simulation experiments in two small outdoor scenes were designed, and the effects of the traditional backward advection and forward fixed step methods were compared with the algorithm in this study. The proposed simulation method showed improved accuracy compared with the other two methods in experimental scenarios; moreover, compared with those of the traditional backward method, the computation time was significantly reduced and the conservation of mass was significantly improved. Thus, the proposed method is a fast simulation method for outdoor aerosol numerical prediction

A novel phenol and ammonia recovery process for coal gasification wastewater altering the bacterial community and increasing pollutants removal in anaerobic/anoxic/aerobic system

Coal gasification wastewater (CGWW) is a typical toxic and refractory industrial wastewater. Here, a novel phenol and ammonia recovery process (IPE) was employed for CGWWpretreatment, and the coupled system assemble by the IPE process with A(2)/O system (IPE-A(2)/O) were operated to enhance the treatment performance of CGWW. The results showed that the IPE pre-treated effluent had a higher BOD5/COD ratio and lower refractory compounds compared to a typical process (MIBK). Subsequent A(2)/O biological treatment indicated that the A(2)/O-p system (A(2)/O system followed IPE process) obtained a higher average COD removal of 92% compared to 87.7% of the control (A(2)/O-m, A(2)/O system followed MIBK). The GC-MS analysis suggested that the content of alkanes in the IPE-A(2)/O effluent was lower than that of the MIBK-A(2)/O. The high-throughput sequencing revealed Levilinea, Alcaligenes, Acinetobacter, Thauera and Thiobacillus were the core genera in A(2)/O system. The genera Alcaligenes, Acinetobacter, Thauera and Thiobacillus in the degrading consortium were enriched in the A(2)/O-p system, leading to increased removals of organic pollutants and TN. These results suggested that the IPE process was a feasible pretreatment method, and the coupled IPE-A(2)/O system was an alternative technique for treating CGWW. (C) 2019 Published by Elsevier B.V

Metagenomic insights into the microbiota profiles and bioaugmentation mechanism of organics removal in coal gasification wastewater in an anaerobic/anoxic/oxic system by methanol

Coal gasification wastewater is a typical high phenol-containing, toxic and refractory industrial wastewater. Here, lab-scale anaerobic-anoxic-oxic system was employed to treat real coal gasification wastewater, and methanol was added to oxic tank as the co-substrate to enhance the removal of refractory organic pollutants. The results showed that the average COD removal in oxic effluent increased from 24.9% to 36.0% by adding methanol, the total phenols concentration decreased from 54.4 to 44.9 mg/L. GC-MS analysis revealed that contents of phenolic components and polycyclic aromatic hydrocarbons (PAHs) were decreased compared to the control and their degradation intermediates were observed. Microbial community revealed that methanol increased the abundance of phenolics and PAHs degraders such as Comamonas, Burkholderia and Sphingopyxis. Moreover, functional analysis revealed the relative abundance of functional genes associated with toluene, benzoate and PAHs degradation pathways was higher than that of control based on KEGG database