Optimization of methylene blue degradation by Aspergillus terreus YESM 3 using response surface methodology

Human activities coupled with industrial development cause pollution to air, water and soil (Zhang et al. 2019; Sun et al. 2019; Miao et al. 2020). The release of chemicals from many industries poses a hazard to earth's biodiversity (Trivedi & Verma 2016). Among numerous kinds of ecological pollution, dye-based industries' aquatic pollution is of major concern. Synthetic dyes are complex aromatic chemicals that pollute aquatic ecosystems (Ismail et al. 2019; Yusuf 2019). Dyes are used in several industries such as foodstuff, printing, textiles, pharmaceutical and cosmetics (Sun et al. 2007; Saratale et al. 2011; Jain et al. 2012; Rios-Del Toro et al. 2013; Meng et al. 2014).

The discharging of dyes into aquatic resources affects natural properties of water and causes severe environmental problems (Sun et al. 2007; Qu et al. 2012; Chaudhari et al. 2013). Dye contamination threatens human health and environmental equilibrium (Inthorn et al. 2004; Sadhasivam et al. 2007; Wang & Hu 2007). Moreover, the dyes' colours inhibit the penetration of sunlight and therefore, decrease photosynthetic activity (Maurya et al. 2006; Özer et al. 2007; Doğan et al. 2008). The majority of dyes are resistant to environmental factors such as heat and photodegradation due to their complex aromatic structures (Srinivasan & Viraraghavan 2010). Therefore, the remediation of dye-contaminated wastewater is of special ecological concern (Meng et al. 2014).

Several conventional methods such as physical and chemical have been used to control dyes pollution (Kaushik & Malik 2009; Saratale et al. 2011). However, some drawbacks, such as the high cost and low effectiveness, limit their use (Crini 2006; Chhabra et al. 2015; Nouren & Bhatti 2015). On the other hand, bioremediation techniques are eco-friendly, low cost and have high efficiency (Meng et al. 2014). Microbial degradation results in decolourization and breakdown of dyes into non-toxic products through the action of enzymes (Kaushik & Malik 2009; Balapure et al. 2019; Pande et al. 2019).

Methylene blue (MB) (Pasti-Grigsby et al. 1992) is a cationic thiazine dye. It is a widespread pollutant in textile effluents and commonly used in textile industries such as dyeing wools, cottons and colouring paper (Ansari & Mosayebzadeh 2010). It is also used in microbiology, diagnostics and surgery as a sensitizer (Aksu et al. 2010). Malachite green (MG), safranin (S) and MB cause several health and environmental problems such as vomiting, burning human eyes and increasing heart rate, harm photosynthesis, etc. (Vadivelan & Kumar 2005; Tan et al. 2008; Zhang et al. 2011). Therefore, the removal of MG, S and MB from wastewater is required. The present study aims to explore the potentiality of Aspergillus terreus YESM 3 to degrade MB, MG and S. In addition, it aims to optimize the biodegradation of MB in liquid medium using response surface design.

Dyes were purchased from Sigma Aldrich Co. (St. Louis, MO, USA). Sodium nitrate, potassium dihydrogen phosphate, magnesium sulphate, potassium chloride, ferrous sulphate, agar and other chemicals and solvents were supplied from El Gomhoria Co. (Alexandria, Egypt).

Standard stock solutions of 1,000 mg/L were prepared by dissolving 100 mg of each dye into a volumetric flask; the volume was completed to 100 mL with distilled water. Working solutions of each dye were sterilized using 0.2 μm Minisart filter unit then added to sterilized Czapek Dox Agar (CDA) medium to reach the required final concentrations (5–400 mg/L).

CDA medium was freshly prepared as follows: sucrose 30 g; sodium nitrate 3 g; potassium dihydrogen phosphate 1 g; magnesium sulphate 0.5 g; potassium chloride 0.5 g; ferrous sulphate 0.01 g; and agar 20 g were dissolved in distilled water (1 L). The pH of the medium was adjusted to 6.0 with 0.1N NaOH or HCl solutions via digital pH-meter (Hanna Instruments, Italy) before autoclaving.

The filamentous fungus Aspergillus terreus YESM 3 used in the current study for biodegradation of dyes was isolated from industrial effluent obtained from Abu-Qir (El-Amia) drain, Alexandria, Egypt. A. terreus YESM 3 fungus was identified using morphology and sequencing analysis of the amplified ITS1-5.8S rDNA-ITS2. The obtained nucleotide sequence was deposited in the EMBL nucleotide sequence databases under the accession number LM653117. The phylogenetic neighbour-joining tree that reflects evolutionary relationships was constructed using MEGA 4.0.2 software (Figure 1). The strain was maintained on CDA slants at 28 °C and stored at 4 °C.

Tolerance and biodegradation of dyes were performed according to the method described by Tang et al. (2009) with some modification. Discs (10 mm diameter) of fungus CDA plates previously grown for 6 days at 28 ± 2 °C were inoculated at the centre of CDA plates supplemented with different concentrations (5, 10, 25, 50, 100, 200 and 400 mg/L) of each dye separately and the plates incubated at 28 °C for 6 days. All experiments were run in triplicate. A plate of A. terreus YESM 3 with no added dye was used as a positive control, and CDA medium containing dye without fungus was used as a negative control. Average diameters of both fungal colony and decolourization zone were measured. The tolerance index (TI) of fungal growth was calculated as the ratio of the average linear growth of fungus in treated plates to that of the control (Mohammed & Badawy 2017).

For optimizing MB degradation, the Box–Behnken experimental design (BBD) (Box & Behnken 1960) was applied. Three important parameters, MB concentration (⁠⁠), pH (⁠⁠) and inoculum size (⁠⁠), were chosen as the independent variables, and percentage degradation was the dependent response variable. The independent variables were studied at three different levels (−, 0 and +) according to the Box–Behnken design using Minitab 16 software in three variables with a total of 15 experiments. Percentages of dye degradation, corresponding to combined effects of four components, were studied in their specified ranges. The plan of BBD in coded and actual levels of the three independent variables is shown in Table 1.

For batch biodegradation experimental design, fungal conidia from CDA culture surface were gently scraped in sterile distilled water, used as inoculum (El-Metwally & Mohammed 2019) and transferred to 100 mL Erlenmeyer flasks containing 20 mL of CD liquid medium according to Table 1. The inoculated flasks and the control sets (non-inoculated flasks) were incubated at 28 °C under static conditions. All experiments were conducted in triplicate.

Experimental data are presented as mean ± standard error (SE), and the analysis of variance (ANOVA) of data was conducted and mean property values were separated (p ≤ 0.05) with Student–Newman–Keuls (SNK) test by the SPSS program (ver. 21.0, USA).

A. terreus strain YESM 3 was tested for its ability to degrade different dyes on CDA plates. The degradation ability varied among different dyes (Figure 2). A. terreus YESM 3 was capable of decolourizing all tested dyes to varying degrees. This difference might be due to the presence of inhibitory groups, variation in chemical structures as well as difference in molecular weight of the dyes as previously reported by other researchers (Pasti-Grigsby et al. 1992; Patil et al. 2008; Hussain et al. 2013; Bheemaraddi et al. 2014). The highest degradation efficiency, as revealed by diameter of decolourization zone, was for MB followed by S and MG (Figure 3). The degradation degree of all tested dyes was higher at lower concentrations, and this may be due to low toxicity and less availability of dye molecules to A. terreus YESM 3. Increase in dye concentrations decreases percentage of dye degradation efficiency; the highest degradation efficiency was recorded for MB at 10 mg/L, forming a decolourization zone of 9.02 cm. Data in Figure 4 depict that TI of fungus strain was dependent on dye concentrations. In general, TI of A. terreus was decreased gradually with increasing concentration of each tested dye. The highest value of TI (2.03) was recorded with media amended with 10 mg/L MB, followed by media supplemented with S and MG. Parshetti et al. (2006) reported that increase in dye concentration influences the mass transfer resistance between dyes and the cells.

It is noteworthy to mention that only a few strains belonging to the genus Aspergillus have been characterized for dye degradation. Few reports have been published on degradation of synthetic dyes by Aspergillus spp. This report aspires to be a novel study on biodegradation of methylene blue by A. terreus YESM 3.

Response surface methodology (RSM) is the most relevant multivariate statistical technique used in optimizing processes (Lebron et al. 2018). The application of statistical experimental design techniques to the decolourization process can result in improved removal, reduced process variability, closer confirmation of the output response to nominal and target requirements, and reduced development time and overall costs (Srinivasan & Murthy 2009; Bonugli-Santos et al. 2016). The main aim of response surface analysis is to investigate the interaction among the variables and to determine the optimum concentration of each factor for maximum MB biodegradation. Table 1 represents the design matrix of the coded variables together with the experimental results for biodegradation (%) of MB. Data revealed a considerable variation in biodegradation (%) depending on the levels of the three independent variables.

The statistical significance of regression equations was checked using F-test. The adequacy of the model was further evaluated by ANOVA analysis (Table 2). The model F-value was found to be 313.95 corresponding to p < 0.001, suggesting that the model was highly significant. The linear and the quadratic terms of MB concentration, pH and inoculum size and interaction between them were highly significant for MB biodegradation by Aspergillus terreus YESM 3 (p < 0. 001). The relevance of the model was checked by determination coefficient (R²). The closer the R² value to 1.0, the better the fitness of the model in the experimental data (Sharma et al. 2009). The R² was calculated to be 0.9982, indicating that 99.82% variability in the response could be explained by this model. Therefore, the present R² value reflected a very good fit between the observed and predicted responses, and implied that the model is reliable for predicting MB biodegradation. The value of the adjusted determination coefficient (Adj R² = 0.9951) suggests that the total variation of 99.51% for the dye degradation is depending on the independent variables, and only about 0.49% of the total variation cannot be explained by the model.

Moreover, the lack of fit F-value of 7.46 with p-value 0.12 implied that the lack of fit was insignificant relative to the pure error. So the model was found to be adequate to predict the MB biodegradation process within the range of experimental variables (Table 2).

The three-dimensional response surface plots and contour plots are the graphical representations of the regression equation (Sharma et al. 2009). The main goal of response surface and contour plots is to track efficiently the optimum values of the variables for maximization of response. The MB biodegradation is generated for the pair-wise combination of the three factors, with one variable kept constant at its optimum level and with variation of the other two variables within the experimental range. The optimum value of each variable was located based on the hump in the three-dimensional plot. These plots are presented in Figure 5.

In Figure 5(b) the interaction between MB concentration and pH on degree of degradation reveals that the degradation was enhanced gradually by increasing both MB concentration and pH to reach their optimum level and then decreased steadily in combination with the high level of MB concentration and pH. Environmental factors are known to play a crucial role affecting the decolourization activity of microorganisms (Khan et al. 2013). pH is among the most important factors governing not only the growth, but also the functions performed by the microbial populations (Abbas et al. 2016). The major effect of pH may be attributed to the transport of dye molecules across the cell membrane, which may be considered as the rate limiting step for the decolourization (Lourenco et al. 2000; Chang & Lin 2001). It was observed that highly acidic and alkaline pH showed a significant negative effect on degradation potential. Highest level of degradation was recorded at mid-point tested range of pH; this might be due to relatively higher enzymatic activities involved in degradation process at this pH (Abbas et al. 2016).

In addition, Figure 5(b) shows the surface plot of the percentage of degradation as a function of MB concentration and inoculum size. It could be inferred that the degradation gradually increased as dye concentration increased, and further increase in dye concentration resulted in decrease of the degradation process. In agreement with our results, Zeng et al. (2015) reported that a higher decolourization percentage for MB was reported at lower concentration.

A similar effect was found in previous studies, suggesting that higher concentration of dye has a negative effect on degradation efficiency due to the toxicity and inhibitory effects or the inhibition of enzyme activity involved in the decolourization process (Ozdemir et al. 2008; Zeng et al. 2015; Ryu et al. 2017). Moreover, the formation of a larger quantity of metabolites, possible inhibitory compounds and accumulation of waste materials at higher dye concentrations consequently create an adverse effect on the active sites of the enzymes responsible for decolourization (Saratale et al. 2013; Zhao et al. 2014; Maniyam et al. 2020). It was also presumed that the insufficient supply of initial cell concentration decelerated decolourization activity (Olukanni et al. 2010; Maniyam et al. 2020). In general, high concentrations of dye result in a decrease in degradation efficiency.

Figure 5(b) showed that the degradation of dye increased with the increase in inoculum size and then decreased with the further increase in the inoculum size, which could be attributed to early depletion of nutrients. Similar findings were reported by other researchers (Sivaraj et al. 2011; Kumar et al. 2012; Asgher et al. 2013).

The optimum values of the variables for maximum MB biodegradation (%) can be analysed by checking the maxima formed by the X and Y coordinates; the conditions obtained at the saddle point for best response. Responses were initial dye concentration 31.41 (mg/L), pH 6, and inoculum size 5.7778 × 10⁴ (conidia/mL); up to 89.41% dye degradation was achieved. These points were located within the experimental ranges, implying that the statistical design could be used to identify the optimal conditions for MB biodegradation by A. terreus YESM 3. Figure 6 illustrates MB biodegradation by A. terreus YESM 3 in liquid media in a period of 6 days at optimum conditions compared to uninoculated control that showed no dye colour removal.

A new and eco-friendly system for the biodegradation of methylene blue dye by A. terreus YESM 3 (accession number LM653117) to the extent of 89.41% has been efficiently developed. Efficient bioremediation using this fungus will require the optimization of physicochemical factors for maximum biodegradation. This biological system is simple, fast and inexpensive, and hence could be used for the bioremediation of dye-contaminated wastewater. Thus, A. terreus YESM 3 could be a potential candidate for the bioremediation of MB dye-contaminated wastewater.

We would like to express our special appreciation and thanks to Prof. Dr Soraya A. Sabry, Professor of Microbiology, Botany and Microbiology Department, Faculty of Science, Alexandria University, Egypt. Soraya Sabry, you have been a tremendous mentor for us. We would like to thank you for encouraging our research and for allowing us to grow as research scientists. Your advice on both research as well as on our career has been invaluable.

All relevant data are included in the paper or its Supplementary Information.