Significance of bio-treatment by acid washing for enlargement of arsenic desorption in indigenous arsenic-resistant bacteria from gold mine

Mining activities can lead to the generation of large quantities of heavy metal, specifically arsenic which is released from a gold mine, causing widespread contamination of the ecosystem. Removal of carcinogenic and toxic arsenic from wastewater is essential for the safety of water that may be used for irrigation or drinking. In this study, three different of indigenous arsenic resistant bacterial strains were isolated from gold mine environment, Bacillus thuringiensis strain WS3, Pseudomonas stutzeri strain WS9, and Micrococcus yunnanensis strain WS11. WS9, WS3, and WS11 reached stationary phase after eight, ten, and seven hours, respectively, at 37 °C when grown in LB with arsenic. Gram staining showed WS9 as gram-negative rods, WS3 as grampositive rods, and WS11 as gram-positive cocci. From the Silver nitrate test, WS3 and WS11 reduced As (V) to As (III) while WS9 oxidized As (III) to As (V). The desorption of arsenic using acid washing and parameters affecting the desorption of arsenic such as acid concentration, time, adsorbent dosage, and different volume of acid solution were investigated. The batch experiments were carried out using bacterial biomass cultured in LB with 2 mM arsenite (III) and 5 mM arsenate (V). Optimum conditions for desorption arsenic were determined, being 1 M acid concentration at 37 °C and 2 hours of contact with (50 mg) bacterial biomass in 100 ml acid solution. The removal of arsenite and arsenate increased after acid washing of bacterial biomass of the three strains. Consequently, desorption of arsenic using acid washing is essential for biomass regeneration

Reading Habits and Attitudes Among University Students: A Review

Reading is the core element in the learning process. Reading habits and attitudes towards reading is one of the primary concerns in the field of education. A pattern of low reading habits and attitudes among university students is reported by researchers. This paper aims to review the latest literature on reading habits and attitudes among university students. The scope of this literature review was extracted from journal articles and electronic media on the subject of reading habits and attitude

Comparison of culture-independent and dependent approaches for identification of native arsenic-resistant bacteria and their potential use for arsenic bioremediation

Arsenic is a common contaminant in gold mine soil and tailings. Microbes present an opportunity for bio-treatment of arsenic, since it is a sustainable and cost-effective approach to remove arsenic from water. However, the development of existing bio-treatment approaches depends on isolation of arsenic-resistant microbes from arsenic contaminated samples. Microbial cultures are commonly used in bio-treatment; however, it is not established whether the structure of the cultured isolates resembles the native microbial community from arsenic-contaminated soil. In this milieu, a culture-independent approach using Illumina sequencing technology was used to profile the microbial community in situ. This was coupled with a culture-dependent technique, that is, isolation using two different growth media, to analyse the microbial population in arsenic laden tailing dam sludge based on the culture-independent sequencing approach, 4 phyla and 8 genera were identified in a sample from the arsenic-rich gold mine. Firmicutes (92.23%) was the dominant phylum, followed by Proteobacteria (3.21%), Actinobacteria (2.41%), and Bacteroidetes (1.49%). The identified genera included Staphylococcus (89.8%), Pseudomonas (1.25), Corynebacterium (0.82), Prevotella (0.54%), Megamonas (0.38%) and Sphingomonas (0.36%). The Shannon index value (3.05) and Simpson index value (0.1661) indicated low diversity in arsenic laden tailing. The culture dependent method exposed significant similarities with culture independent methods at the phylum level with Firmicutes, Proteobacteria and Actinobacteria, being common, and Firmicutes was the dominant phylum whereas, at the genus level, only Pseudomonas was presented by both methods. It showed high similarities between culture independent and dependent methods at the phylum level and large differences at the genus level, highlighting the complementarity between the two methods for identification of the native population bacteria in arsenic-rich mine. As a result, the present study can be a resource on microbes for bio-treatment of arsenic in mining waste

Assessments of concentrations of sulfur dioxide (SO2) In Universiti Tun Hussein Onn Malaysia (UTHM) Campus Area, Batu Pahat

More air contaminants have an effect on public health. In recent decades, the topic of production of air pollutants has gained a lot of public interest and research attention. One of the main gases responsible for air pollutants is sulphur dioxide (SO2). The purpose of this research is to explore sulphur dioxide differences at various locations in the campus area of Universiti Tun Hussein Onn Malaysia (UTHM). For this purpose, air pollutant data from thirteen areas were measured at different times. The maximum levels of sulphur dioxide were recorded in the afternoon and the minimum in the morning. SPSS study (one-way ANOVA) of the SO2 concentration at various locations in UTHM revealed eight independent groups for all locations at p<0.5. The highest concentration of SO2 were recorded at KKTDI (a) with the reading of 0.198 and the lowest concentration of SO2 reading were at PKU with the reading of 0.03 ppm. The results of this investigation show that SO2 concentrations are strongly associated to locations near emission sources and have a significant fluctuation in the atmosphere

In vitro study of antidiabetic effect of abrus precatorius methanol leaves extract against glucose absorption

Diabetes mellitus is a common chronic systemic disorder characterised by hyperglycaemia as a standard feature. A traditional plant known as Abrus precatorius (AP) has been used for the treatment of type II diabetes mellitus in Malaysia. The potential of the 80% methanolic extract of A. precatorius leaves has been tested in vitro for its α-glucosidase inhibition and its glucose diffusion activity. It was observed that the extraction of A. precatorius leaves exhibit a high α-glucosidase inhibition at the concentrations of 25 and 50 mg/mL (65.4% and 84.6%), respectively, but low inhibition at the concentration of 6.25 to 12.5 mg/mL (25% and 28.2%) when compared to control. Meanwhile, the methanolic extract of A. precatorius slightly affected the glucose diffusion at the concentration of 50 mg/mL (9.5%) within 24 h compared to the control group. These results indicated that the methanolic extract of A. precatorius leaves is capable of inhibiting α-glucosidase activity, besides halting glucose diffusion activity by delaying the glucose absorption in the gut

Biosorption of as (iii) by non-living biomass of an arsenic-hypertolerant Bacillus cereus strain SZ2 isolated from a gold mining environment: equilibrium and kinetic study

The ability of non-living biomass of an arsenic-hypertolerant Bacillus cereus strain SZ2 isolated from a gold mining environment to adsorb As (III) from aqueous solution in batch experiments was investigated as a function of contact time, initial As (III) concentration, pH, temperature and biomass dosage. Langmuir model fitted the equilibrium data better in comparison to Freundlich isotherm. Themaximum biosorption capacity of the sorbent, as obtained from the Langmuir isotherm, was 153.41 mg/g. The sorption kinetic of As (III) biosorption followed well the pseudo-second-order rate equation. The Fourier transform infrared spectroscopy analysis indicated the involvement of hydroxyl, amide and amine groups in As (III) biosorption process. Field emission scanning electron microscopy-energy dispersive X-ray analysis of the non-living B. cereus SZ2 biomass demonstrated distinct cell morphological changes with significant amounts of As adsorbed onto the cells compared to non-treated cells. Desorption of 94%As (III)was achieved at acidic pH 1 showing the capability of non-living biomass B. cereus SZ2 as potential biosorbent in removal of As (III) from arsenic-contaminated mining effluent

The adsorptive removal of as (III) using biomass of arsenic resistant Bacillus thuringiensis strain WS3: characteristics and modelling studies

Globally, the contamination of water with arsenic is a serious health issue. Recently, several researches have endorsed the efficiency of biomass to remove As (III) via adsorption process, which is distinguished by its low cost and easy technique in comparison with conventional solutions. In the present work, biomass was prepared from indigenous Bacillus thuringiensis strain WS3 and was evaluated to remove As (III) from aqueous solution under different contact time, temperature, pH, As (III) concentrations and adsorbent dosages, both experimentally and theoretically. Subsequently, optimal conditions for As (III) removal were found; 6 (ppm) As (III) concentration at 37 °C, pH 7, six hours of contact time and 0.50 mg/ml of biomass dosage. The maximal As (III) loading capacity was determined as 10.94 mg/g. The equilibrium adsorption was simulated via the Langmuir isotherm model, which provided a better fitting than the Freundlich model. In addition, FESEM-EDX showed a significant change in the morphological characteristic of the biomass following As (III) adsorption. 128 batch experimental data were taken into account to create an artificial neural network (ANN) model that mimicked the human brain function. 5-7-1 neurons were in the input, hidden and output layers respectively. The batch data was reserved for training (75%), testing (10%) and validation process (15%). The relationship between the predicted output vector and experimental data offered a high degree of correlation (R 2 = 0.9959) and mean squared error (MSE; 0.3462). The predicted output of the proposed model showed a good agreement with the batch work with reasonable accuracy

The removal of arsenic species from aqueous solution by indigenous microbes: batch bioadsorption and artificial neural network model

Arsenic contamination of groundwater is a problem that affects millions of people across the world. Biological treatment of arsenic using microorganisms is an interesting alternative to conventional methods because it is most efficient, low cost and eco-friendly. In this study, three different bacterial species were isolated from arsenic laden tailing dam sludge at gold mining and the 16S rRNA sequencing data exposed their affiliation to three different genera, Bacillus thuringiensis strain WS3, Pseudomonas stutzeri strain WS9 and Micrococcus yunnanensis strain WS11. Considering the advantage of the different structures of these bacterial cell walls in adsorption, attempts were made to use individual and mixed dried biomass of these strains to achieve highest As (III) and As (V) removal under different conditions. Mixed dried biomass of WS3, WS9 and WS11 were found to be efficient in the removal of As (III) and As (V) up to 95% and 98%, respectively. Optimal conditions for arsenic removal were found; 8 and 6 h of contact time for As (III) and As (V), respectively, 7.5 (ppm) As (III) and 9 (ppm) As (V) concentration at 37 °C, pH 7, and 0.60 mg/ml of biomass dosage. In comparison of estimated coefficient of determination (R2), Langmuir isotherm model provided the best fit to the experimental data while the adsorption kinetic model followed the pseudo-second-order. FESEM–EDX analysis established diverse cell morphological changes with significant amounts of arsenic adsorbed onto the biomass compared to original biomass. FTIR analysis showed the involvement of hydroxyl, thiol, amide and amine functional groups in arsenic removal. Comparisons between actual and model adsorption results show that the artificial neural network model can predict adsorption efficiency with high accuracy (R2 > 0.98). Consequently, mixed dried biomass of WS3, WS9 and WS11 are strongly recommended for bio-treatment of toxic arsenic from the environment

Optimization of As(V) Removal by Dried Bacterial Biomass: Nonlinear and Linear Regression Analysis for Isotherm and Kinetic Modelling

Arsenic occurrence and toxicity records in various industrial effluents have prompted researchers to find cost-effective, quick, and efficient methods for removing arsenic from the environment. Adsorption of As(V) onto dried bacterial biomass is proposed in the current work, which continues a line of previous research. Dried bacterial biomass of WS3 (DBB) has been examined for its potential to remove As(V) ions from aqueous solutions under various conditions. Under optimal conditions, an initial concentration of 7.5 ppm, pH 7, adsorbent dose of 0.5 mg, and contact period of 8 h at 37 °C results in maximum removal of 94%. Similarly, amine, amide, and hydroxyl groups were shown to contribute to As(V) removal by Fourier transform infrared spectroscopy (FTIR), and the adsorption of As(V) in the cell wall of DBB was verified by FESEM-EDX. In addition, equilibrium adsorption findings were analyzed using nonlinear and linear isotherms and kinetics models. The predicted best-fit model was selected by calculating the coefficient of determination (R2). Adsorption parameters representative of the adsorption of As(V) ions onto DBB at R2 values were found to be more easily attained using the nonlinear Langmuir isotherm model (0.95). Moreover, it was discovered that the nonlinear pseudo-second-order rate model using a nonlinear regression technique better predicted experimental data with R2 than the linear model (0.98). The current study verified the nonlinear approach as a suitable way to forecast the optimal adsorption isotherm and kinetic data