Microbial production of hyaluronic acid: current state, challenges, and perspectives

Hyaluronic acid (HA) is a natural and linear polymer composed of repeating disaccharide units of β-1, 3-N-acetyl glucosamine and β-1, 4-glucuronic acid with a molecular weight up to 6 million Daltons. With excellent viscoelasticity, high moisture retention capacity, and high biocompatibility, HA finds a wide-range of applications in medicine, cosmetics, and nutraceuticals

Heterologous expression, biochemical characterization, and overproduction of alkaline α-amylase from Bacillus alcalophilus in Bacillus subtilis

<p>Abstract</p> <p>Background</p> <p>Alkaline α-amylases have potential applications for hydrolyzing starch under high pH conditions in the starch and textile industries and as ingredients in detergents for automatic dishwashers and laundries. While the alkaline α-amylase gains increased industrial interest, the yield of alkaline α-amylases from wild-type microbes is low, and the combination of genetic engineering and process optimization is necessary to achieve the overproduction of alkaline α-amylase.</p> <p>Results</p> <p>The alkaline α-amylase gene from <it>Bacillus alcalophilus </it>JN21 (CCTCC NO. M 2011229) was cloned and expressed in <it>Bacillus subtilis </it>strain WB600 with vector pMA5. The recombinant alkaline α-amylase was stable at pH from 7.0 to 11.0 and temperature below 40°C. The optimum pH and temperature of alkaline α-amylase was 9.0 and 50°C, respectively. Using soluble starch as the substrate, the <it>K</it>_mand <it>V</it>_maxof alkaline α-amylase were 9.64 g/L and 0.80 g/(L·min), respectively. The effects of medium compositions (starch, peptone, and soybean meal) and temperature on the recombinant production of alkaline α-amylase in <it>B. subtilis </it>were investigated. Under the optimal conditions (starch concentration 0.6% (w/v), peptone concentration 1.45% (w/v), soybean meal concentration 1.3% (w/v), and temperature 37°C), the highest yield of alkaline α-amylase reached 415 U/mL. The yield of alkaline α-amylase in a 3-L fermentor reached 441 U/mL, which was 79 times that of native alkaline α-amylase from <it>B. alcalophilus </it>JN21.</p> <p>Conclusions</p> <p>This is the first report concerning the heterologous expression of alkaline α-amylase in <it>B. subtilis</it>, and the obtained results make it feasible to achieve the industrial production of alkaline α-amylase with the recombinant <it>B. subtilis</it>.</p

A Web Cache Replacement Strategy for Safety-Critical Systems

A Safety-Critical System (SCS), such as a spacecraft, is usually a complex system. It produces a large amount of test data during a comprehensive testing process. The large amount of data is often managed by a comprehensive test data query system. The primary factor affecting the management experience of a comprehensive test data query system is the performance of querying the test data. It is a big challenge to manage and maintain the huge and complex testing data.To address this challenge, a web cache replacement algorithm which can effectively improve the query performance and reduce the network latency is needed. However, a general-purpose web cache replacement algorithm usually cannot be directly applied to this type of system due to the low hit rate and low byte hit rate. In order to improve the hit rate and byte hit rate, a data stream mining technology is introduced, and a new web cache algorithm GDSF-DST (Greedy Dual-Size Frequency with Data Stream Technology) for the Safety-Critical System (SCS) is proposed based on the original GDSF algorithm. The experimental results show that compared with state of the art traditional algorithms, GDSF-DST achieves competitive performance and improves the hit rate and byte hit rate by about 20%

Coenzyme Q deficiency may predispose to sudden unexplained death via an increased risk of cardiac arrhythmia

Cardiac arrhythmia is currently considered to be the direct cause of death in a majority of sudden unexplained death (SUD) cases, yet the genetic predisposition and corresponding endophenotypes contributing to SUD remain incompletely understood. In this study, we aimed to investigate the involvement of Coenzyme Q (CoQ) deficiency in SUD. First, we re-analyzed the exome sequencing data of 45 SUD and 151 sudden infant death syndrome (SIDS) cases from our previous studies, focusing on previously overlooked genetic variants in 44 human CoQ deficiency-related genes. A considerable proportion of the SUD (38%) and SIDS (37%) cases were found to harbor rare variants with likely functional effects. Subsequent burden testing, including all rare exonic and untranslated region variants identified in our case cohorts, further confirmed the existence of significant genetic burden. Based on the genetic findings, the influence of CoQ deficiency on electrophysiological and morphological properties was further examined in a mouse model. A significantly prolonged PR interval and an increased occurrence of atrioventricular block were observed in the 4-nitrobenzoate induced CoQ deficiency mouse group, suggesting that CoQ deficiency may predispose individuals to sudden death through an increased risk of cardiac arrhythmia. Overall, our findings suggest that CoQ deficiency-related genes should also be considered in the molecular autopsy of SUD

Research on key architecture and model of coal mine water hazard intelligent early warning system

In order to ensure the safe production of mine threatened by water hazard, speed up the intelligent process of mine water hazard prediction and early warning technology, and improve the effect of mine water hazard prediction and early warning, based on the research status of water hazard mechanism and monitoring and early warning at home and abroad, four types of key technical issues for constructing water hazard monitoring and intelligent early warning systems are analyzed. The complexity of early warning requirements and data access standards, the classification and spatio-temporal matching of multi-source heterogeneous big data information, the intelligent processing and analysis of water hazard big data information, and the timeliness of early warning and intelligent decision information release are discussed in detail. From the perspective of early warning system resource integration and data drive, water hazard warning resources are divided into information collection resources and computing resources, water hazard warning big data information is divided into static source information and dynamic monitoring information, and data processing is divided into basic geological model data processing, numerical processing and Computational simulation and information fusion data processing divide coal mine disaster early warning into primary monitoring parameter early warning, intermediate index grading early warning, and advanced intelligent model early warning. The key technical architecture of an intelligent warning system for coal mine water hazards is proposed and analyzed. A software service architecture that meets the technical requirements is proposed, including infrastructure layer, data resource layer, application support layer, business application layer, and user presentation layer. Based on the water hazard warning construction process, a Gated Recurrent Unit algorithm warning model for water hazard monitoring data is proposed, and the network structure of the warning model is given. The forward calculation, backward propagation calculation, and weight gradient calculation methods of the warning model are studied. The classification of different types of perception data access, storage, encoding, models, construction and testing of intelligent deep learning models, and technical paths for warning information release are analyzed. It provides a reference for the intelligent construction of coal mine water hazard early warning

Chemokine receptor CX3CR1 contributes to macrophage survival in tumor metastasis

Chinese Ministry of Science and Technology [2009CB522205, 2012CB945104]; National Science Foundation of China [81170120, 31090363]; Beijing Nova Program [Z121107002512041]Background: Macrophages, the key component of the tumor microenvironment, are differentiated mononuclear phagocyte lineage cells that are characterized by specific phenotypic characteristics that have been implicated in tumor growth, angiogenesis, and invasion. CX3CR1, the chemoattractant cytokine CX3CL1 receptor, plays an important role in modulating inflammatory responses, including monocyte homeostasis and macrophage phenotype and function. However, the role of CX3CR1 in the regulation of the tumor inflammatory microenvironment is not fully understood. Methods: Using in vivo hepatic metastasis model, human colon carcinoma specimens, immunohistochemical staining, TUNEL staining, flow cytometry analysis, Western blotting assay and co-culture in three-dimensional peptide gel, we determined the effects of CX3CR1 on angiogenic macrophage survival and tumor metastasis. Results: In this study, we found that CX3CR1 was expressed in human colon carcinomas in a histologic grade-and stage-dependent manner, and CX3CR1 upregulation in TAMs was correlated with poor prognosis. Furthermore, we showed that in a microenvironment lacking CX3CR1, the liver metastasis of colon cancer cells was significantly inhibited. The underlying mechanism is associated with decrease accumulation of angiogenic macrophages that can be partly attributed to increased apoptosis in the tumor microenvironment, thus leading to impaired tumor angiogenesis in the liver and suppressed tumor metastasis. Conclusions: Our results suggest a role of CX3CR1 in angiogenic macrophage survival in the tumor microenvironment contributing to tumor metastasis