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/lp/springer-journals/biodegradation-optimization-and-metabolite-elucidation-of-reactive-red-z8hwXpqW71
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- Springer Journals
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- Copyright © 2017 by Springer-Verlag Berlin Heidelberg and the University of Milan
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- Life Sciences; Microbiology; Microbial Genetics and Genomics; Microbial Ecology; Mycology; Medical Microbiology; Applied Microbiology
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- 1590-4261
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- 1869-2044
- DOI
- 10.1007/s13213-017-1259-1
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Abstract
Ann Microbiol (2017) 67:303–312 DOI 10.1007/s13213-017-1259-1 ORIGINAL ARTICLE Biodegradation optimization and metabolite elucidation of Reactive Red 120 by four different Aspergillus species isolated from soil contaminated with industrial effluent 1 2 Fuad Ameen & Fatimah Alshehrei Received: 26 October 2016 /Accepted: 7 February 2017 /Published online: 11 March 2017 Springer-Verlag Berlin Heidelberg and the University of Milan 2017 Abstract Azo dyes are recalcitrant owing to their xenobiotic Introduction nature and exhibit high resistance to degradation processes. In the present study, different Aspergillus species (A. flavus, Synthetic dyes are extensively used in the textiles, pharma- A. fumigatus, A. niger,and A. terreus)isolated from soilsam- ceuticals, cosmetics, printing, leather, food, and paper indus- ples contaminated with industrial effluent, collected from tries. The dye-loaded effluent emanating from these industries Jeddah, Saudi Arabia, were analyzed for azo dye, Reactive are considered as one of the most serious water pollutions, Red 120 (RR120) biodegradation. The physicochemical pa- with reports that approximately 100 tons of used dyes per rameters such as carbon (sucrose) and nitrogen (ammonium annum are discharged into water streams worldwide (Yagub sulfate) sources, pH, and temperature affecting the biodegra- et al. 2012). Reactive azo dyes, in particular, are widely uti- dation of RR120 were optimized using central composite de- lized in textile dyestuffs, owing to their simple dying proce- sign–response surface methodology (CCD-RSM). The maxi- dures and good stability during washing procedures (Spadaro mum RR120 degradation was found to be 84% (predicted) at et al. 1992). The majority of these dyes and their transformed the optimum level of sucrose (11.73 g/L), ammonium sulfate products are highly toxic and mutagenic to biotic communities (1.26 g/L), pH (5.71), and temperature (28.26 °C). Further, the (Benigni et al. 2000; Poonkuzhali et al. 2011;Sathishkumar validation results confirmed that the predicted values are in et al. 2013). Therefore, treatment of the dye-loaded effluent good agreement with the experimental results for RR120 deg- without causing secondary pollution is essential to protect the radation by A. flavus (86%), A. fumigatus (84%), A. niger ecosystems receiving the effluent (Sathishkumar et al. 2014). (85%), and A. terreus (86%). The metabolic product of In recent decades, several physicochemical and biological RR120 after biodegradation by different Aspergillus species treatment techniques have been reported for the remediation was identified as sodium 2-aminobenzenesulfonate. The pres- of reactive azo dyes (Sathishkumar et al. 2012; Adnan et al. ent study suggests that Aspergillus species are good candi- 2016; Saadon et al. 2016). Among these techniques, biologi- dates for azo dye-loaded effluent treatment. cal treatments have received a great deal of interest owing to their minimal impact on the ecosystem and their cost-effec- tiveness. Although bacterial treatment is economical and sim- . . Keywords Aspergillus Biodegradation Metabolic ple, there is a problem associated with the formation of toxic . . product Reactive Red 120 Sodium aromatic amines during the degradation process (Vyrides et al. 2-aminobenzenesulfonate Response surface methodology 2014). Treatment with ascomycota has proven to be promising for reducing costs and providing an eco-friendly process, ow- * Fuad Ameen ing to the utilization of natural redox mediators in catalyzing fhasan@ksu.edu.sa the enzymatic mechanism, which are produced by the fungus itself (Rodríguez-Couto 2012; Adnan et al. 2015). In the present study, Reactive Red 120 (RR120) dye was Department of Botany & Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia selected as a model dye for the degradation analysis, because it is removed during processing operations and is significantly Department of Biology, Umm Al-Qura University, Makkah 24382, Saudi Arabia present in textile industry wastewater (Suwannaruang et al. 304 Ann Microbiol (2017) 67:303–312 2015). In addition, four different species of the ascomycota rRNA sequencing. In brief, the genomic DNA isolated from fungi genus Aspergillus isolated from effluent-contaminated the selected fungal strain was amplified using polymerase soil samples near weaving factories in Jeddah, Saudi Arabia, chain reaction (PCR) with ITS1 (5′-TCCGTAGGTGAACC were chosen, owing to their remarkable properties of rapid TGCGG-3′) and ITS2 (5′-GCATCGATGAAGAACGCAGC growth and high percentages of RR120 degradation. Further, -3′) utilized as universal primers. The reaction was assisted by optimum conditions including carbon and nitrogen sources, the addition of MgCl , PCR buffer, heat-stable Taq polymer- pH, and temperature were assessed using central composite ase, dNTPs mixture, and DNA template. The PCR process design–response surface methodology (CCD-RSM). Finally, underwent a series of thermal cycling: 1 cycle at 94 °C for 3 the metabolic product obtained from RR120 after biodegrada- min, 25 cycles at 94 °C for 30 s and 50 °C for 30 s, and tion by Aspergillus species was identified as sodium 2- concluded with gene amplification at 72 °C for 10 min aminobenzenesulfonate. To our knowledge, this is the first (Saroj et al. 2014). The amplified genes were then cloned into study to demonstrate this new and non-hazardous metabolic pGEM-T Easy (Promega) before being sent to Seeing product of RR120 biodegradation by Aspergillus species. Bioscience Corporation, Taiwan, for identification. The nucle- otide alignment and phylogenetic tree were constructed based on the comparison of the resulting sequence with the known Materials and methods gene sequences from the National Center for Biotechnology Information (NCBI) GenBank database. Chemicals RR120 biodegradation and optimization by RSM RR120 was procured from Sigma Aldrich (St. Louis, MO, USA). Ammonium acetate and methanol [high-performance In the present study, pure RR120 biodegradation fungi inocu- liquid chromatography (HPLC) grade] were purchased from lums (2%) were mixed with mineral salt medium broth Merck (Kenilworth, NJ, USA). All other chemicals and re- (MSMB). The MSMB contained the following components agents used in the present study were of analytical grade. (g/L): potassium dihydrogen phosphate 0.5, potassium hydro- gen phosphate 0.5, calcium chloride 0.1, ferrous sulfate 0.07, Sample collection magnesium sulfate 1.0, potassium chloride 0.5. The pH of the medium was adjusted (according to RSM design) with 1N Soil samples were collected in sterilized tubes at different sodium hydroxide or 1N hydrochloric acid before autoclaving locations from effluent-contaminated soil near weaving facto- at 121 °C for 15 min. In a preliminary study, most significant ries (sediment had slight dye contamination) located in the carbon (glucose, sucrose, fructose, lactose, mannitol, and industrial city of Jeddah, Saudi Arabia. This city has an area starch) and nitrogen (casein, peptone, sodium nitrate, ammo- greater than 12 million m and contains 552 industrial activi- nium chloride, ammonium sulfate, and ammonium nitrate) ties, including food, mineral, and chemical processing sources were screened using Plackett–Burman (PB) design. industries. Based on the PB screening results, sucrose and ammonium sulfate were selected as suitable carbon and nitrogen sources, Screening of fast-growing and rapid RR120 degrading respectively, for further optimization study. In addition, the fungal isolates most significant parameters such as pH and temperature were considered for optimization with fixed initial concentration of Different fungal strains isolated from the collected soil sam- RR120 (100 ppm), agitation (120 rpm), and incubation period ples were inoculated into RR120 dye-amended potato dex- (7 days). trose agar (PDA) medium and incubated at 27 °C. Fungal Generally, optimization experiments could be done by em- growth and RR120 decolorization efficiency were then regu- pirical or statistical methods. The empirical method is time- larly monitored based on the color change of the RR120- consuming, incomplete, and does not necessarily enable an amended medium. A non-inoculated dye–PDA plate was effective optimization. In this study, CCD-RSM was applied maintained as a control. The most efficient RR120 degrading to optimize the dye degradation process by the isolates. This fungal strains were selected for further molecular identifica- statistics-based optimization method is a powerful experimen- tion and dye degradation. tal design to recognize the performance of composite systems (Coman and Bahrim 2011; Balan et al. 2012; Fabiszewska Identification of fungi et al. 2015; Chang et al. 2017). Interestingly, CCD-RSM, which involves full factorial search by examining simulta- The selected isolates were examined under macroscopic and neous, systematic, and efficient variation of important vari- microscopic observation. Subsequently, molecular identifica- ables, was applied to model the optimization process, identify possible interactions, higher order effects, and determine the tion of the selected fungal strains was performed by 18S Ann Microbiol (2017) 67:303–312 305 optimum operational conditions (Sathishkumar et al. 2015; separatory funnel, and 5 mL of ethyl acetate was added. The Krishnan et al. 2016). The independent variables used in this separatory funnel was shaken vigorously for approximately study for optimization were sucrose (g/L) (X ), ammonium 2 min with periodic venting to release vapor. Further, the sulfate (g/L) (X ), pH (X ), and temperature (°C) (X )atfive organic layer was allowed to separate for 10 min and was 2 3 4 levels (+2, +1, 0, −1, and −2), as shown in Table 1.The recovered into a 50-mL beaker. The aqueous layer was re- percentage of RR120 degradation by selected fungal strains extracted twice with 2 mL of ethyl acetate and the combined was considered as the dependent variable. According to the extract was dried by passing through a funnel containing an- CCD matrix, 30 runs were carried out to achieve the response hydrous sodium sulfate. The dried extract was dissolved in (actual) and the central point was replicated six times to de- methanol (HPLC grade) and used for the identification of termine the experimental error (Table 2). The data obtained metabolites by HPLC and gas chromatography–mass spec- were fitted to a second-order polynomial as follows (Eq. 1): trometry (GC-MS) analysis. HPLC analysis was carried out using a Waters 1525 instrument (Waters Associates Inc.) on a Y ¼ b C18 column (Symmetry, 150 mm) by the isocratic method X 4 X 4 X a X 4 using the gradient of methanol with a flow rate of 1 mL þ b x þ b x þ X b x −1 i i ii ii ij min for 10 min and UV photodiode array detector (model i¼1 i¼1 i¼ j j¼1þ1 2996) at 254 nm. A total of 10 mL of filtered sample was ð1Þ manually injected into the injector port. where Y is the percentage of RR120 degradation, b , b , b , 0 i ii The identification of metabolites formed after RR120 bio- and b are constant coefficients, and x are uncoded indepen- ij i degradation was performed using a Thermo Trace DSQ II GC- dent variables. The data from the RSM experiments per- MS. The ionization voltage was 70 eV. The column tempera- formed were analyzed and interpreted using Design-Expert ture program was set as follows: 50 °C hold for 3 min, 10 °C −1 −1 10 (Stat Ease, Minneapolis, MN, USA). Three main analytical min to 180 °C hold for 1 min, and 10 °C min to 280 °C steps, analysis of variance (ANOVA), a regression analysis, hold for 3 min. Helium was used as the carrier gas with a flow −1 and the plotting of the response surface, were performed to rate of 1.0 mL min . The RR120 biodegradation products obtain an optimum condition for the RR120 degradation. To were detected by comparison of the retention time and frag- verify the dye degradation results predicted by the model, a mentation pattern, as well as with mass spectra from the NIST validation experiment was performed with the predicted spectral library support stored in the GC-MS solution software values of independent variables. (version 1.10 beta, Shimadzu). Analysis of all samples was performed in triplicate. The data were calculated using SPSS Statistics 17.0 software. The significant difference between Measurement of RR120 biodegradation the treatments and the control was detected based on least significant difference at P <0.05. The RR120 dye degradation experiments were carried out under optimized conditions, and, further, the residual RR120 in the culture medium was analyzed based on the method Results and discussion described by Wang et al. (2009), with minor modifications. Briefly, 1 mL of culture medium was collected every 24 h and Isolation and identification of RR120 decolorizing fungi centrifuged at 8000 × g for 10 min. The RR120 biodegrada- tion was then determined by measuring the absorbance at Twenty fungal isolates were obtained from the collected soil 595 nm using a UV-visible spectrophotometer (DR 2700, samples. Among these, four fungal strains (isolates B, D, H, Hach, Loveland, CO, USA). The percentage of RR120 bio- and K) were selected for further RR120 biodegradation stud- degradation (BD %) was calculated using the following equa- ies, based on superior growth performance and RR120 degra- tion (Eq. 2): dation efficiency. Subsequently, these isolates were identified by molecular and microscopic techniques as A. flavus (B), A A 0 t BDðÞ % ¼ x100 ð2Þ A. fumigatus (D), A. niger (H), and A. terreus (K). where, A refers to the initial absorbance, A is the absorbance RR120 biodegradation optimization by RSM 0 t after incubation, and t is the incubation time. After biodegradation of RR120, the fungal mycelium was To enhance the rate of RR120 biodegradation by the isolates removed from the culture by filtration. The supernatant ob- (A. flavus, A. fumigatus, A. niger,and A. terreus), carbon tained from the culture was utilized to extract the metabolites (sucrose) and nitrogen (ammonium sulfate) sources, tempera- with an equal volume of ethyl acetate. The mixture was shak- ture, and pH were optimized according to the CCD-RSM en, 5 mL of the mixture was transferred into a 50-mL matrix. Almost all the selected Aspergillus species’ RR120 306 Ann Microbiol (2017) 67:303–312 Table 1 Coded and uncoded Variables Range of variables and level Step change value (ΔZi) values of independent variables used in the central composite −2 −10 +1+2 design (CCD) design Glucose (g/L) 2 6 10 14 16 4 Ammonium sulfate (g/L) 0.5 1 1.5 2 2.5 0.5 pH 5.0 5.5 6.0 6.5 7.0 0.5 Temperature(°C) 20253035405 degradation efficiencies were found to be similar (data not The results show that the percentage of RR120 degradation shown). The mean value of RR120 degradation by all the corresponded to the combined effect of the four selected in- selected Aspergillus species results are shown in Table 2. dependent variables in their specified ranges. The RR120 Table 2 Range and level of S. Glucose Ammonium sulfate pH Temperature Response (dye degradation, variables in the full factorial CCD no. (g/L) (g/L) (°C) %) matrix and response X X X X Observed Predicted 1 2 3 4 (Y ) (Ŷ ) j j 1 −1 −1 −1 −164 65 2+1 −1 −1 −177 79 3 −1+1 −1 −167 65 4+1 +1 −1 −170 72 5 −1 −1+1 −154 56 6+1 −1+1 −173 74 7 −1+1 +1 −154 52 8+1 +1 +1 −165 65 9 −1 −1 −1+1 67 69 10 +1 −1 −1+1 77 77 11 −1+1 −1+1 72 75 12 +1 +1 −1+1 78 79 13 −1 −1+1+1 61 60 14 +1 −1+1+1 78 79 15 −1+1 +1 +1 64 63 16 +1 +1 +1 +1 73 75 17 −2 0 0 0 41 39 18 +2 0 0 0 66 62 19 0 −200 76 78 20 0 +2 0 0 73 69 21 0 0 −2 0 80 80 22 0 0 +2 0 73 69 23 0 0 0 −270 71 24 0 0 0 +2 77 75 25 0 0 0 0 79 80 26 0 0 0 0 78 80 27 0 0 0 0 79 80 28 0 0 0 0 80 80 29 0 0 0 0 81 80 30 0 0 0 0 80 80 The observed dependent responses are the mean of all isolated Aspergillus sp. Ann Microbiol (2017) 67:303–312 307 degradation varied markedly in the range of 41–81%. These The R values had advocated a high correlation between results suggest that the selected variables strongly affect the both the experimental and predicated values, which in- RR120 degradation process. dicates that the regression model gives a good explana- The statistical analysis of the CCD-RSM experimen- tion of the relationship between the independent vari- tal results were performed using Design-Expert 10 soft- ables and the dependent variable. The insignificant ware to generate response surface modeling and optimi- lack-of-fit test (F-value = 3.06) also confirms that the zation of the process variables. Table 3 illustrates the model was perfectly fitting to the experimental data. In statistical significance for RR120 degradation assessed addition, the adequate precision ratio was found to be by Fisher’s(F) test and ANOVA for the response sur- 34.862, which indicates an adequate signal. Therefore, face quadratic model. The ANOVA result shows that the this model can be used to navigate the design space. fitted second-order response surface model was highly Table 3 shows that the individual terms (x , x , x ), 1 3 4 2 2 2 2 significant with the F-test = 68.38 (P < 0.0001). The squared terms (x , x , x , x ), and interactive terms 1 2 3 4 model reliability was confirmed by the determination (x x ,x x ,x x , x x ) of variables were highly signifi- 1 2 1 3 2 4 3 4 2 2 of coefficient R (0.9846), adjusted R (0.9702), and cant for the RR120 degradation. The final equation in predicted R (0.9205), which suggests that about 1% terms of coded variables for the RR120 degradation is of the total variation cannot be explained by the model. as follows: 2 2 2 2 Y ¼þ79:50 þ 5:75x −0:58x −2:67x þ 2:50x −6:69x −1:44x −0:94x −1:69x −1:87x x þ 1 2 3 4 1 2 1 2 3 4 ð3Þ 1:50 x x − 0:25 x x − 0:75 x x þ 1:00 x x þ 0:88 x x 1 3 1 4 2 3 2 4 3 4 Equation 1 was used to facilitate the plotting of response RR120 degradations achieved were highly influenced by all surfaces in order to ascertain the interactive effects of the the investigated variables. Further, the results confirm that the independent variables for RR120 degradation. Two- percentage of RR120 degradation was increased up to a cer- dimensional (2D) plots are the graphical representations of tain level for all of the investigated factors; however, beyond the regression equation that was generated for the pairwise that, degradation was decreased. combination of the four variables, while keeping the other The analysis of the residuals was performed to judge the two at their center point value. The interactions between the adequacy of the developed model. Figure 2 demonstrates that variables can be inferred from the shapes of the contour plots. none of the studentized residuals had a value higher than 1, Circular contour plots indicate that the interactions between and, also, all of the residuals fell within the acceptable range, the variables are negligible. In contrast, elliptical plots indicate thus certifying that the model is good. The predicted maxi- evidence of the interactions. Figure 1a–f shows that the mum RR120 degradation of 84% was derived from RSM Table 3 Analysis of variance Source Degrees of freedom Sum of squares Mean square F-value Prob. > F (ANOVA) results for the equation using Design-Expert 10 Model 14 2499.53 178.54 68.38 <0.0001* X 1 793.50 793.50 303.89 <0.0001* X 1 8.17 8.17 3.13 0.0973 X 1 170.67 170.67 65.36 <0.0001* X 1 150.00 150.00 57.45 <0.0001* X 1 1226.68 1226.68 469.79 <0.0001* X 1 56.68 56.68 21.71 0.0003* X 1 24.11 24.11 9.23 0.0083* X 1 78.11 78.11 29.91 <0.0001* X X 1 56.25 56.25 21.54 0.0003* 1 2 X X 1 36.00 36.00 13.79 0.0021 1 3 X X 1 1.00 1.00 0.38 0.5453 1 4 X X 1 9.00 9.00 3.45 0.0831 2 3 X X 1 16.00 16.00 6.13 0.0257 2 4 X X 1 12.25 12.25 4.69 0.0468 3 4 Residual 15 39.17 2.61 Lack of fit 10 33.67 3.37 3.06 0.1144 Pure error 5 5.50 1.10 Cor. total 29 2538.70 2 2 2 *Significant; SD: 1.62; R : 0.9846; adj R : 0.9702; pred R :0.9205 308 Ann Microbiol (2017) 67:303–312 Fig. 1 Contour plot for the RR120 degradation by Aspergillus species. Interaction of: a sucrose with ammonium sulfate, b sucrose with pH, c sucrose with temperature, d ammonium sulfate with pH, e ammonium sulfate with temperature, and f pH with temperature Fig. 3 RR120 degradation by Aspergillus species under response surface methodology (RSM) optimized conditions [sucrose (11.73 g/L), ammonium sulfate (1.26 g/L), pH (1.26 g/L), and temperature (28.26 Fig. 2 The studentized residuals and normal % probability plot of °C) with fixed initial concentration of RR120 (100 ppm), agitation (120 RR120 degradation by Aspergillus species rpm), and incubation period (7 days)] Ann Microbiol (2017) 67:303–312 309 regression at the optimum levels of sucrose, ammonium sul- Generally, the addition of carbon and nitrogen sources fate, pH, and temperature of 11.73 g/L, 1.26 g/L, 5.71, and to the culture medium enhances the efficacy of microor- 28.26 °C, respectively. Further, in order to validate the pre- ganisms to break down azo dyes. Ambrosio and Campos- dicted optimum results, the RR120 degradation experiments Takaki (2004) observed maximum degradation of reactive (replicates) were performed with optimized combinations of azo dyes in medium containing sucrose as the carbon the independent variables [sucrose 11.73 g/L, ammonium sul- source. Zhang et al. (1999) confirmed that the support of fate 1.26 g/L, pH 5.71, and temperature 28.2 °C with fixed media by a carbon source would work as a co-substrate to initial concentration of RR120 (100 ppm), agitation (120 enhance the biodegradation of azo dye by fungal isolates. rpm), and incubation period (7 days)], as described above. Ryu and Weon (1992) reported that the maximum degra- The RR120 degradation experimental results were found dation of azo dyes by A. sojae occurred in the presence of to be 86%, 84%, 85%, and 86% for A. flavus, additional ammonium sulfate (1.8 g/L) as the nitrogen A. fumigatus, A. niger,and A. terreus, respectively source. Zheng et al. (1999) indicated that the addition of (Fig. 3). This confirms that the predicted values are in ammonium ions to the culture medium could enhance dye good agreement with the experimental results. Similarly, decolorization by the fungal isolate. Ganesh et al. (1994) Sharma et al. (2009) observed 84.8% of diazo dye Acid observed that a decrease in fungal efficacy to degrade azo Red 151 (AR 151) decolorization at the optimum pH of 5.5 and temperature of 30 °C using RSM. dyes depends on an increase in acidic or alkaline Fig. 4 HPLC chromatogram of (i) RR120 and their metabolites after biodegradation by (ii) A. flavus, (iii) A. fumigatus,(iv) A. niger,and (v) A. terreus 310 Ann Microbiol (2017) 67:303–312 Fig. 5 Mass spectrum (m/z) of sodium 2-aminobenzenesulfonate produced from the biodegradation of RR120 by isolates of: a A. flavus, b A. fumigatus, c A. niger,and d A. terreus conditions for optimum environments suitable for the decreased with increasing pH and temperature. This might growth of fungus. The dye degradation was considerably be due to enzyme denaturation, which reduces the amount Fig. 6 Proposed mechanism of RR120 biodegradation by four different Aspergillus species Ann Microbiol (2017) 67:303–312 311 Acknowledgments The authors extend their appreciation to the of cell viability for extracellular enzymatic activities by Deanship of Scientific Research at King Saud University for funding this biodegrading the structure of targeted dye molecules work through research group NO (RGP-1438-029). (Khan et al. 2013). Compliance with ethical standards Identification of RR120 metabolic intermediates Conflict of interest The authors declare that they have no conflict of interest. The biodegradation intermediates formed by fungal isolates Disclosures The manuscript does not contain clinical studies or patient after the 7-day incubation period were assessed using HPLC data. analysis. The HPLC chromatogram in Fig. 4 shows that the peak which appeared at 2.91 m/z for RR120 disappeared and new peaks formed at low mass ions after biodegradation by References A. flavus, A. fumigatus, A. niger,and A. terreus. These results indicate that RR120 was broken down into many residues due Adnan LA, Sathishkumar P, Mohd Yusoff AR, Hadibarata T (2015) to the enzymatic process of Aspergillus species. Metabolites characterisation of laccase mediated reactive black 5 The metabolites of RR120 biodegradation by each of the biodegradation by fast growing ascomycete fungus Trichoderma atroviride F03. Int Biodeterior Biodegrad 104:274–282 Aspergillus species were detected using GC-MS analysis. Adnan LA, Hadibarata T, Sathishkumar P, Mohd Yusoff AR RR120 has a high molecular weight of 1469.98. After (2016) Biodegradation pathway of Acid Red 27 by white- Aspergillus species treatment, the azo bond (N = N) could rot fungus Armillaria sp. 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Journal
Annals of Microbiology – Springer Journals
Published: Mar 11, 2017