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The aim of the present study was the characterisation of three true subtilisins and one phylogenetically intermediate subtilisin from halotolerant and halophilic microorganisms. Considering the currently growing enzyme market for efficient and novel biocatalysts, data mining is a promising source for novel, as yet uncharacterised enzymes, especially from halophilic or halotolerant Bacillaceae, which offer great potential to meet industrial needs. Both halophilic bacteria Pontibacillus marinus DSM 16465ᵀ and Alkalibacillus haloalkaliphilus DSM 5271ᵀ and both halotolerant bacteria Metabacillus indicus DSM 16189 and Litchfieldia alkalitelluris DSM 16976ᵀ served as a source for the four new subtilisins SPPM, SPAH, SPMI and SPLA. The protease genes were cloned and expressed in Bacillus subtilis DB104. Purification to apparent homogeneity was achieved by ethanol precipitation, desalting and ion-exchange chromatography. Enzyme activity could be observed between pH 5.0–12.0 with an optimum for SPPM, SPMI and SPLA around pH 9.0 and for SPAH at pH 10.0. The optimal temperature for SPMI and SPLA was 70 °C and for SPPM and SPAH 55 °C and 50 °C, respectively. All proteases showed high stability towards 5% (w/v) SDS and were active even at NaCl concentrations of 5 M. The four proteases demonstrate potential for future biotechnological applications.
Background
Aminoacylases are highly promising enzymes for the green synthesis of acyl-amino acids, potentially replacing the environmentally harmful Schotten-Baumann reaction. Long-chain acyl-amino acids can serve as strong surfactants and emulsifiers, with application in cosmetic industries. Heterologous expression of these enzymes, however, is often hampered, limiting their use in industrial processes.
Results
We identified a novel mycobacterial aminoacylase gene from Mycolicibacterium smegmatis MKD 8, cloned and expressed it in Escherichia coli and Vibrio natriegens using the T7 overexpression system. The recombinant enzyme was prone to aggregate as inclusion bodies, and while V. natriegens Vmax™ could produce soluble aminoacylase upon induction with isopropyl β-d-1-thiogalactopyranoside (IPTG), E. coli BL21 (DE3) needed autoinduction with lactose to produce soluble recombinant protein. We successfully conducted a chaperone co-expression study in both organisms to further enhance aminoacylase production and found that overexpression of chaperones GroEL/S enhanced aminoacylase activity in the cell-free extract 1.8-fold in V. natriegens and E. coli. Eventually, E. coli ArcticExpress™ (DE3), which co-expresses cold-adapted chaperonins Cpn60/10 from Oleispira antarctica, cultivated at 12 °C, rendered the most suitable expression system for this aminoacylase and exhibited twice the aminoacylase activity in the cell-free extract compared to E. coli BL21 (DE3) with GroEL/S co-expression at 20 °C. The purified aminoacylase was characterized based on hydrolytic activities, being most stable and active at pH 7.0, with a maximum activity at 70 °C, and stability at 40 °C and pH 7.0 for 5 days. The aminoacylase strongly prefers short-chain acyl-amino acids with smaller, hydrophobic amino acid residues. Several long-chain amino acids were fairly accepted in hydrolysis as well, especially N-lauroyl-L-methionine. To initially evaluate the relevance of this aminoacylase for the synthesis of N-acyl-amino acids, we demonstrated that lauroyl-methionine can be synthesized from lauric acid and methionine in an aqueous system.
Conclusion
Our results suggest that the recombinant enzyme is well suited for synthesis reactions and will thus be further investigated.
The number of electronic vehicles increase steadily while the space for extending the charging infrastructure is limited. In particular in urban areas, where parking spaces in attractive areas are famous, opportunities to setup new charging stations is very limited. This leads to an overload of some very attractive charging stations and an underutilization of less attractive ones. Against this background, the paper at hand presents the design of an e-vehicle reservation system that aims at distributing the utilization of the charging infrastructure, particularly in urban areas. By applying a design science approach, the requirements for a reservation-based utilization approach are elicited and a model for a suitable distribution approach and its instantiation are developed. The artefact is evaluated by simulating the distribution effects based on data of real charging station utilizations.
The present work aimed to study the mainstream feasibility of the deammonifying sludge of side stream of municipal wastewater treatment plant (MWWTP) in Kaster, Germany. For this purpose, the deammonifying sludge available at the side stream was investigated for nitrogen (N) removal with respect to the operational factors temperature (15–30°C), pH value (6.0–8.0) and chemical oxygen demand (COD)/N ratio (≤1.5–6.0). The highest and lowest N-removal rates of 0.13 and 0.045 kg/(m³ d) are achieved at 30 and 15°C, respectively. Different conditions of pH and COD/N ratios in the SBRs of Partial nitritation/anammox (PN/A) significantly influenced both the metabolic processes and associated N-removal rates. The scientific insights gained from the current work signifies the possibility of mainstream PN/A at WWTPs. The current study forms a solid basis of operational window for the upcoming semi-technical trails to be conducted prior to the full-scale mainstream PN/A at WWTP Kaster and WWTPs globally.
Companies often build their businesses based on product information and therefore try to automate the process of information extraction (IE). Since the information source is usually heterogeneous and non-standardized, classic extract, transform, load techniques reach their limits. Hence, companies must implement the newest findings from research to tackle the challenges of process automation. They require a flexible and robust system that is extendable and ensures the optimal processing of the different document types. This paper provides a distributed microservice architecture pattern that enables the automated generation of IE pipelines. Since their optimal design is individual for each input document, the system ensures the ad-hoc generation of pipelines depending on specific document characteristics at runtime. Furthermore, it introduces the automated quality determination of each available pipeline and controls the integration of new microservices based on their impact on the business value. The introduced system enables fast prototyping of the newest approaches from research and supports companies in automating their IE processes. Based on the automated quality determination, it ensures that the generated pipelines always meet defined business requirements when they come into productive use.
In comparison to single-analyte devices, multiplexed systems for a multianalyte detection offer a reduced assay time and sample volume, low cost, and high throughput. Herein, a multiplexing platform for an automated quasi-simultaneous characterization of multiple (up to 16) capacitive field-effect sensors by the capacitive–voltage (C–V) and the constant-capacitance (ConCap) mode is presented. The sensors are mounted in a newly designed multicell arrangement with one common reference electrode and are electrically connected to the impedance analyzer via the base station. A Python script for the automated characterization of the sensors executes the user-defined measurement protocol. The developed multiplexing system is tested for pH measurements and the label-free detection of ligand-stabilized, charged gold nanoparticles.
Amino acid-based surfactants are valuable compounds for cosmetic formulations. The chemical synthesis of acyl-amino acids is conventionally performed by the Schotten-Baumann reaction using fatty acyl chlorides, but aminoacylases have also been investigated for use in biocatalytic synthesis with free fatty acids. Aminoacylases and their properties are diverse; they belong to different peptidase families and show differences in substrate specificity and biocatalytic potential. Bacterial aminoacylases capable of synthesis have been isolated from Burkholderia, Mycolicibacterium, and Streptomyces. Although several proteases and peptidases from S. griseus have been described, no aminoacylases from this species have been identified yet. In this study, we investigated two novel enzymes produced by S. griseus DSM 40236ᵀ . We identified and cloned the respective genes and recombinantly expressed an α-aminoacylase (EC 3.5.1.14), designated SgAA, and an ε-lysine acylase (EC 3.5.1.17), designated SgELA, in S. lividans TK23. The purified aminoacylase SgAA was biochemically characterized, focusing on its hydrolytic activity to determine temperature- and pH optima and stabilities. The aminoacylase could hydrolyze various acetyl-amino acids at the Nα -position with a broad specificity regarding the sidechain. Substrates with longer acyl chains, like lauroyl-amino acids, were hydrolyzed to a lesser extent. Purified aminoacylase SgELA specific for the hydrolysis of Nε -acetyl-L-lysine was unstable and lost its enzymatic activity upon storage for a longer period but could initially be characterized. The pH optimum of SgELA was pH 8.0. While synthesis of acyl-amino acids was not observed with SgELA, SgAA catalyzed the synthesis of lauroyl-methionine.
This article describes an Internet of things (IoT) sensing device with a wireless interface which is powered by the energy-harvesting method of the Wiegand effect. The Wiegand effect, in contrast to continuous sources like photovoltaic or thermal harvesters, provides small amounts of energy discontinuously in pulsed mode. To enable an energy-self-sufficient operation of the sensing device with this pulsed energy source, the output energy of the Wiegand generator is maximized. This energy is used to power up the system and to acquire and process data like position, temperature or other resistively measurable quantities as well as transmit these data via an ultra-low-power ultra-wideband (UWB) data transmitter. A proof-of-concept system was built to prove the feasibility of the approach. The energy consumption of the system during start-up was analysed, traced back in detail to the individual components, compared to the generated energy and processed to identify further optimization options. Based on the proof of concept, an application prototype was developed.
This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub.
A method for detecting and approximating fault lines or surfaces, respectively, or decision curves in two and three dimensions with guaranteed accuracy is presented. Reformulated as a classification problem, our method starts from a set of scattered points along with the corresponding classification algorithm to construct a representation of a decision curve by points with prescribed maximal distance to the true decision curve. Hereby, our algorithm ensures that the representing point set covers the decision curve in its entire extent and features local refinement based on the geometric properties of the decision curve. We demonstrate applications of our method to problems related to the detection of faults, to multi-criteria decision aid and, in combination with Kirsch’s factorization method, to solving an inverse acoustic scattering problem. In all applications we considered in this work, our method requires significantly less pointwise classifications than previously employed algorithms.