Data for proteome analysis of Bacillus lehensis G1 in starch-containing medium

Bacillus lehensis G1 is a cyclodextrin glucanotransferase (CGTase) producer, which can degrade starch into cyclodextrin. Here, we present the proteomics data of B. lehensis cultured in starch-containing medium, which is related to the article “Proteome-based identification of signal peptides for improved secretion of recombinant cyclomaltodextrin glucanotransferase in Escherichia coli” (Ling et. al, in press). This dataset was generated to better understand the secretion of proteins involved in starch utilization for bacterial sustained growth. A 2-DE proteomic technique was used and the proteins were tryptically digested followed by detection using MALDI-TOF/TOF. Proteins were classified into functional groups using the information available in SubtiList webserver (http://genolist.pasteur.fr/SubtiList/)

Assessment of microwave-assisted pretreatments for enhancing pineapple waste delignification

Biological degradation of biomass for the production of fine chemicals is getting much interest nowadays. However, the complex and recalcitrance structure of the biomass hinders the success story of the degradation. Lignin is the main composition that impedes the bioconversion of biomass. Hence, an optimize delignification pretreatment need to be developed to enable the biological degradation process becomes much easier and thus higher production yield can be achieved afterwards. This study focuses on the assessment of pineapple waste (PW) delignification by applying microwave radiation on two different pretreated PW to facilitate the processes. The PW was initially pretreated with distilled water (dH2O) and peracetic acid (PAA) prior to the microwave radiation. Three main parameters (pretreatment time, min; temperature, °C; and microwave radiation power, W) were studied towards the effect of PW delignification. Lignin percentage before and after the pretreatments were compared and analysed. The results obtained revealed that the microwave-assisted PAA shows the best percentage of delignification compared to the microwave-assisted dH2O pretreatment. The best delignification process obtained in this study is a key indicator for a better biomass degradation to achieve higher yield of products in the future

Application of computational method in designing a unit cell of bone tissue engineering scaffold: a review

The design of a scaffold of bone tissue engineering plays an important role in ensuring cell viability and cell growth. Therefore, it is a necessity to produce an ideal scaffold by predicting and simulating the properties of the scaffold. Hence, the computational method should be adopted since it has a huge potential to be used in the implementation of the scaffold of bone tissue engineering. To explore the field of computational method in the area of bone tissue engineering, this paper provides an overview of the usage of a computational method in designing a unit cell of bone tissue engineering scaffold. In order to design a unit cell of the scaffold, we discussed two categories of unit cells that can be used to design a feasible scaffold, which are non-parametric and parametric designs. These designs were later described and being categorised into multiple types according to their characteristics, such as circular structures and Triply Periodic Minimal Surface (TPMS) structures. The advantages and disadvantages of these designs were discussed. Moreover, this paper also represents some software that was used in simulating and designing the bone tissue scaffold. The challenges and future work recommendations had also been included in this paper

Radio Location of Partial Discharge Sources: A Support Vector Regression Approach

Partial discharge (PD) can provide a useful forewarning of asset failure in electricity substations. A significant proportion of assets are susceptible to PD due to incipient weakness in their dielectrics. This paper examines a low cost approach for uninterrupted monitoring of PD using a network of inexpensive radio sensors to sample the spatial patterns of PD received signal strength. Machine learning techniques are proposed for localisation of PD sources. Specifically, two models based on Support Vector Machines (SVMs) are developed: Support Vector Regression (SVR) and Least-Squares Support Vector Regression (LSSVR). These models construct an explicit regression surface in a high dimensional feature space for function estimation. Their performance is compared to that of artificial neural network (ANN) models. The results show that both SVR and LSSVR methods are superior to ANNs in accuracy. LSSVR approach is particularly recommended as practical alternative for PD source localisation due to it low complexity

The Glaciozyma antarctica genome reveals an array of systems that provide sustained responses towards temperature variations in a persistently cold habitat

Extremely low temperatures present various challenges to life that include ice formation and effects on metabolic capacity. Psyhcrophilic microorganisms typically have an array of mechanisms to enable survival in cold temperatures. In this study, we sequenced and analysed the genome of a psychrophilic yeast isolated in the Antarctic region, Glaciozyma antarctica. The genome annotation identified 7857 protein coding sequences. From the genome sequence analysis we were able to identify genes that encoded for proteins known to be associated with cold survival, in addition to annotating genes that are unique to G. antarctica. For genes that are known to be involved in cold adaptation such as anti-freeze proteins (AFPs), our gene expression analysis revealed that they were differentially transcribed over time and in response to different temperatures. This indicated the presence of an array of adaptation systems that can respond to a changing but persistent cold environment. We were also able to validate the activity of all the AFPs annotated where the recombinant AFPs demonstrated anti-freeze capacity. This work is an important foundation for further collective exploration into psychrophilic microbiology where among other potential, the genes unique to this species may represent a pool of novel mechanisms for cold survival

Overexpression, purification and characterization of the Aspergillus niger endoglucanase, EglA, in Pichia pastoris

Cellulases are industrially important hydrolytic enzymes applicable in the bioconversion of cellulosic biomass to simple sugars. In this work, an endoglucanase from Aspergillus niger ATCC 10574, EglA, was expressed in the methylotrophic yeast Pichia pastoris and the properties of the recombinant protein were characterized. The full length cDNA of eglA has been cloned into a pPICZaC expression vector and expressed extracellularly as a ~30 kDa recombinant protein in P. pastoris X-33. Pure EglA displayed optimum activity at 50°C and was stable between 30 and 55°C. The pH stability of this enzyme was shown to be in the range of pH 2+.0 to 7.0 and optimum at pH 4.0. EglA showed the highest affinity toward ß-glucan followed by carboxymethyl cellulose (CMC) with a specific activity of 63.83 and 9.47 U/mg, respectively. Very low or no detectable hydrolysis of cellobiose, laminarin, filter paper and avicel were observed. Metal ions such as Mn 2+, Co 2+, Zn 2+, Mg 2+, Ba 2+, Fe 2+, Ca 2+ and K + showed significant augmentation of endoglucanase activity, with manganese ions causing the highest increase in activity to about 2+.7 fold when compared with the control assay, whereas Pd 2+, Cu 2+, SDS and EDTA showed inhibition of EglA activity

Partial Discharge Modelling in a Spherical Cavity within a Dielectric Insulation Material as a Function of Frequency

The measurement of partial discharge (PD) is used in the performance assessment of an insulation system in high voltage components. Through modeling the discharge process a better understanding of the phenomena may be attained. This paper is an extension from previous works by the same authors which have considered the modeling of PD activity from a spherical cavity by using Finite Element Analysis (FEA) method. However, this paper describes the development of an improved model for a spherical cavity within a homogeneous dielectric material. The model developed has been used to study the influence of applied frequency on PD activity. The model has also been used to simulate the PD measurement results. Therefore, parameters in the model that are affecting PD frequency dependent behavior can be identified through comparison between experimental measurement and simulation results

Modelling of Partial Discharge Activity in Different Spherical Cavity Sizes and Locations within a Dielectric Insulation Material

The pattern of partial discharge (PD) occurrence at a defect site within a solid dielectric material is influenced by the conditions of the defect site. This is because the defect conditions, mainly its size and location determine the electric field distributions at the defect site which influence the patterns of PD occurrence. A model for a spherical cavity within a homogeneous dielectric material has been developed by using Finite Element Analysis (FEA) software. The model is used to study the influence of different conditions of the cavity on the electric field distribution in the cavity and the PD activity. In addition, experimental measurements of PD in spherical cavities of different size within a dielectric material have been undertaken. The obtained results show that PD activity depends on the size of the cavity within the dielectric material

Modelling of Cycle to Cycle Behaviour for Partial Discharge Events within a Spherical Cavity in a Solid Dielectric Material by Using Finite Element Analysis

A partial discharge (PD) analysis method that can be used to observe cycle to cycle behaviour of PD activity is to plot PD charge magnitude and voltage of PD occurrence against phase angle for certain numbers of cycles of the applied voltage. The advantage of this method is it gives a better picture of PD activity behaviour in terms of the sequence of discharge events. In this paper, the cycle to cycle behaviour of experimental measurements of PD in a spherical cavity within a solid dielectric material has been obtained and compared with simulation results from a PD model. The paper includes the description of the development of the model using the Finite Element Analysis (FEA) method. The model can effectively reproduce the PD cycle to cycle behaviour of the experiment. Through analyzing the cycle to cycle behaviour of PD events, understanding of the physical mechanisms involved in PD activity can be obtained, such as the effects of initial electron generation rate, charge decay and temperature change between consecutive discharges