Ecological Informatics 31 (2016) 112–121
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Bioinformatics aided microbial approach for bioremediation of wastewater containing textile dyes S. Senthil Kumar a,⁎, S. Shantkriti a,1, T. Muruganandham a,1, E. Murugesh b, Niraj Rane c, S.P. Govindwar c a b c
Department of Biotechnology, National College (Autonomous), Tiruchirapalli 620001, India Department of Bioinformatics, Bharathiar University, Coimbatore 641046, India Department of Biochemistry, Shivaji University, Kolhapur 416004, India
a r t i c l e
i n f o
Article history: Received 5 September 2015 Received in revised form 26 October 2015 Accepted 6 December 2015 Available online 11 December 2015 Keywords: Azo dye Aeromonas hydrophila Lysinibacillus sphaericus Molecular docking Wastewater Decolorization
a b s t r a c t Four textile azo dyes, Joyfix Red, Remazol Red, Reactive Red and Reactive Yellow, were studied for decolorization. Of nineteen soil bacterial isolates, two novel strains were found to highly decolorize Joyfix Red and were identified as Lysinibacillus sphaericus (KF032717) and Aeromonas hydrophila (KF032718) through 16S rDNA analysis. Laccase and Azoreductase enzyme modeling and enzyme–dye interaction performed using Schrödinger Suite imitated decolorization percentage. Results based on cumulative Glide score (Dry laboratory) and decolorization percentage of the other three dyes based on ultraviolet–visible (UV–vis) spectroscopy (Wet laboratory) were reliable. Biodegradation of Joyfix Red was confirmed by high-performance liquid chromatography (HPTLC) elution profile which showed four peaks at 1.522, 1.800, 3.068 and 3.804 min with that of parent dye which showed single peak at 1.472 min. Fourier transform infrared spectroscopy (FT-IR) analysis supported the biotransformation of Joyfix Red. Gas chromatography–mass spectroscopy (GC–MS) analysis showed sodium (3E,5Z)-4-amino-6-hydroxyhexa-13,5-triene-2-sulfonate was formed as end product during biodegradation. From these findings, it can be inferred that enzyme and dye interaction studies can assist in examining decolorization efficiency of bacteria and its enzyme, thereby enhancing the bioremediation process by reducing preliminary lengthy wet laboratory screening. This is the first report of a combinatorial in silico cum in vitro approach and its validation for the bioremediation of wastewater containing these textile azo dyes. © 2015 Elsevier B.V. All rights reserved.
1. Introduction The fast pace of worldwide industrialization and urbanization has formed the basis of a correlation between ecological pollution and public well-being. Textile industries use huge quantities of water and chemicals for bleaching, scouring, desizing, dyeing, printing and finishing steps. It is difficult for most textile factories to adequately treat their wastewater. Large amounts of wastewater discharged from textile industries to nearby water bodies lead to various environmental problems. Reports of Valipour (2014a, 2015a) indicate that the links between water and other development-related sectors such as population, energy, food and environment, and the interactions among them require reckoning, as they together will determine future food security and poverty reduction. The poor wastewater management practices of the textile industries have intensified waterlogging and salinity problems for irrigation (Valipour, 2014b).
⁎ Corresponding author at: PG & Research Department of Biotechnology, National College (Autonomous), Dindigul Road, Tiruchirapalli 620001, Tamilnadu, India. Tel.: +91 9865268433 (Mobile). E-mail address:
[email protected] (S.S. Kumar). 1 Authors' share equal contribution.
http://dx.doi.org/10.1016/j.ecoinf.2015.12.001 1574-9541/© 2015 Elsevier B.V. All rights reserved.
Hence, textile industries are under considerable pressure to minimize the water consumption and reduce the treatment cost. Huge quantities of diverse dyes are being utilized in the textile industry for dyeing. Dye is the hardest constituent to take care of in the textile wastewater. These dyes have a number of structural varieties such as acidic, reactive, basic, disperse, azo, diazo, anthraquinone-based and metal-complex dyes. More than half of them contain azo compounds (Kariyajjanavar et al., 2010). These represent a major group of dyes that are of major environmental concern due to its persistent color, bio-recalcitrance and potential toxic nature to the animals and humans consuming it (Senthil et al., 2013). Many dyes are visible in water at concentrations as low as 1 mg L− 1. Textile processing wastewaters with dye contents in the range of 10–200 mg L− 1 are highly colored (Senthil et al., 2014). The majority of these dyes are potentially lethal to marine biodiversity (Metcalf and Eddy, 1991) and several are cancerous and mutagenic to human beings (Spadaro et al., 1992). Recent research reports indicate that the water supply and available land resources have played a major role in the process of agricultural production. In developing countries, farmers have started irrigating crops with industrial wastewater having high levels of various toxic compounds due to non-availability of alternative water resource for irrigation. Hence, appropriate treatment of wastewaters has become
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necessary prior to its final discharge into environment. (Valipour, 2015b; Valipour et al., 2015) Azo dye decolorization involves the dye degradation via reduction or cleavage of azo bonds through anaerobic digestion and eventual biotransformation of the aromatic amines in aerobic environment (Kolekar et al., 2012). Complete degradation and conversion of textile azo dyes to harmless substances is hard by conventional physicochemical treatment processes (Karapinar et al., 2000; Lin and Peng, 1994). The limited past investigations have shown that azo dyes can be completely decolorized, and some intermediates such as aromatic amines with side groups (–SO3, –OH, –COOH, –Cl) containing metabolites were quantitatively detected (Kolekar et al., 2012). In current times, biological treatment with the use of native microbes has become an appealing approach for the elimination of unwanted color and toxicity from textile wastewater as compared to other conventional treatment processes (Hassan et al., 2013). These microorganisms within the soil of the textile industrial areas where the dye effluents containing synthetic compounds are largely found, adapt themselves over the ages to the presence of synthetic dyes due to their persistency in its microenvironment. Bioremediation-based technology has become an upcoming area for the treatment of textile dye wastewater due to simple set-up, less expenditure, functional simplicity, reduced sludge quantity, ecofriendliness and broad area of application (Pasti-Grigsby et al., 1992; Walker, 1970; Zimmermann et al., 1984). In fact, the need of the hour is to develop fresh biological decolorization methods containing one or more microorganisms adapted in habitat concentration for the effective clean-up of the excess dyes in the wastewater. The potential of bacterial enzymes for decolorization of azo dyes has been studied by various computational approaches such as ab initio, Density Functional Theory calculation (DFT) and Computational Fluid Dynamics (CFD) modeling (Laurence et al., 2005; Mahmoodi et al., 2009). A report for combined study of in vitro and in silico method for crude laccase-mediated remediation of dyes was carried out recently, and the authors reported that the in vitro results were in good agreement with the in silico outcomes. Hence, this combined approach may assist in ranking dyes in terms of their affinity to bind with the enzyme and so can be applied for enzyme-mediated remediation methodology (Abbott et al., 2005; Sridhar et al., 2013). The main objective of this study was to isolate and identify novel bacterial isolates having strong dye decolorizing ability which can be potential candidates for the bioremediation of textile dye wastewater to decolorize and degrade azo dyes. Four dyes, namely Reactive Yellow F3R, Remazol Red RR, Reactive Red F3B and Joyfix Red RB, were used for this work. In order to compare experimentally obtained decolorization and degradation profile of azo dyes, molecular docking study of ligand (azo dyes) with modeled bacterial enzymes was performed. Moreover to identify the specific enzyme of these species mainly involved in decolorization, we opted for molecular docking study. The enzymes laccase and azoreductase of both the strains were retrieved from GenPept Databank (Protein Sequence Database) followed by Homology modeling to predict three-dimensional structure of the protein. For enzyme–dye interacting affinity analysis, all the four chosen dyes were docked with the enzymes. The dyes were checked for binding affinity with the modeled protein structure in order to compare with the obtained spectroscopic profile of the dyes. In this work, enzyme modeling, enzyme–ligand docking and wet laboratory studies were combined to investigate the decolorization of
Table 1 Grid points for modeled protein to dock. Grid points Aeromonas sps. Lysinibacillus sps.
Azoreductase Laccase Azoreductase Laccase
X-axis
Y-axis
Z-axis
34.89 45.97 21.83 19.04
24.61 31.06 47.34 29.89
21.09 22.87 45.67 32.9
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azo dyes. We intended to analyze, compare the binding affinity of dyes with enzyme and the decolorization profile obtained from spectroscopic studies and identify the bacterial enzyme. To the best of our knowledge, this is the first report of a combined in silico cum in vitro approach and its reverse validation for bioremediation of wastewater containing textile azo dyes using novel bacterial isolates.
2. Materials and methods 2.1. Commercial dyes and chemicals The Four textile azo dyes, namely Joyfix Red RB, Remazol Red RR, Reactive Red F3B and Reactive Yellow F3R, used in the study were procured from Jamara textile industry, Perundurai, Erode, Tamil Nadu, India. They were studied for absorption spectrum in a UV–vis Spectrophotometer (Shimadzu UV–Vis 1800, Japan) from 350 nm to 800 nm. All other chemicals and reagents were of Analytical grade (Merck, India).
2.2. Isolation, screening and identification of dye degrading microorganisms Soil samples were collected aseptically from the dumping grounds of the textile mill sludge under usage for over a decade within the textile industrial complex and carefully transported to the laboratory. The soil samples were serially diluted by following the standard protocol, and the dilution series of 10−2 to 10−8 was plated in Nutrient Agar (Merck) medium. Each dilution was maintained in triplicates. All the plates were incubated at 37 °C for 24 h (Capuccino and Sherman, 2004; Franciscon et al., 2009). Nineteen cultures were identified based on their morphology and color and were transferred aseptically into sterile Nutrient agar slants for raising pure cultures to perform further study. The organisms from stock culture were used for the decolorization studies after pre-culturing in Nutrient Broth (g. L− 1): Peptone 10.0, NaCl 5.0, Yeast Extract 2.0 and Beef Extract 1.0 at 37 ± 2 °C for 16 h under shaking condition (120 rpm) and at neutral pH (Jadhav et al., 2010). Table 2 Absorption spectra and chemical structure of Joyfix Red RB, Remazol Red RR, Reactive Red F3B and Reactive Yellow F3R (a—native dye; b—after biological treatment). Dye Joyfix Red RB C.I. Reactive red 198 λmax (nm): 520 CAS No: 145017-98-7 PubChem ID: CID_6506390 Remazol Red RR λmax (nm): 520 PubChem ID: CID_9570342
Reactive Red F3B C.I. Reactive Red 180 λmax (nm): 520 CAS No: 72828-03-6 Reactive Yellow F3R C.I. Reactive Yellow 145 λmax (nm): 450 CAS No: 93050-80-7
Absorption spectra
Structure
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Fig. 1. Evolutionary relationship analysis of 16S rDNA sequence of dye-degrading strains.
2.3. Screening of novel isolates with best decolorizing ability The decolorizing ability of all the 19 bacterial isolates was tested individually on a chosen dye (Joyfix Red RB—an azo containing reactive dye). Decolorization experiments were performed in three sets. Inoculum was used at 5% concentration when the Optical Density reached 1.0, in a 250-mL Erlenmeyer flask containing 100 mL nutrient broth with the dye concentration of 100 mg L−1 in both shaking (120 rpm) and static conditions at 37 °C for a period of 72 h (Kalyani et al., 2008). Decolorization was detected by UV–vis spectrophotometer (Shimadzu UV–Vis 1800, Japan) at respective λmax using
the supernatant from the liquid culture medium after centrifugation at 10,000 rpm for ten minutes in a refrigerated centrifuge (5804R, Eppendorf, Germany). The removal of the color was reported as percentage of decolorization. Abiotic controls (without microorganisms) were also included. 2.4. Molecular identification of the novel bacteria and phylogenetic analysis The chromosomal DNA of the two strains with best decolorization potential was isolated according to the procedure described by Rainey et al. (1996). The isolates were identified using 16S rDNA sequence
Percentage of decolorization
100 90 80 70 60 50 40 30 20 10 0
SK1 SK2 SK3 SK4 SK5 SK6 SK7 SK8 SK9 SK10 SK11 SK12 SK13 SK14 SK15 SK16 SK17 SK18 SK19 Shaking 66.3 4.167 22.25 19.62 27.12 0 0 60.25 54 0 18.13 24.27 86.27 10.48 11.43 89.3 5.25 27.25 4.2 Static 36.6 3.217 11.48 5.433 38.28 0 0 35 68.33 0 35 18.58 88.52 17 31.48 91.02 16.48 15.52 5
Autochthonous bacterial isolates Fig. 2. Graph showing the percentage of decolorization of Joyfix Red RB by nineteen bacterial isolates (SK 1 to SK 19) under shaking and static conditions.
S.S. Kumar et al. / Ecological Informatics 31 (2016) 112–121 Table 3 Percentage of decolorization of chosen dyes under biological treatment process. Name of the dyes
Percentage of decolorization
SK 13 SK 16 Joyfix Red RB Remazole Red RR Reactive Red F3B Reactive Yellow F3R
85 86.25 90.81 86.84
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Table 4 Z score with Standard deviation (SD) of modeled one with library accessed conformations.
88.75 88.20 89.00 90.40
analysis. The 16S rDNA gene sequencing of isolated strains was carried out at Chromous Biotech Pvt. Ltd, Bangalore, India. The nucleotide sequence analysis of the sequence was carried out at Blast-n site at NCBI server (http://www.ncbi.nlm.hin.gov/BLAST). The alignment of sequence was done by CLUSTALW program V1.82 at European bioinformatics site (http://www.ebi.ac.uk/clustalw). The sequence was refined manually after cross-checking with raw data to remove ambiguities and submitted to the NCBI. The Phylogenetic tree was constructed using Maximum parsimony method on the program, Mega 2.0 (Kumar et al., 2001) for evolutionary relationship analysis as it is well suited for sequences that are quite similar and for smaller number of sequences (Yang, 1996). 2.5. Biodecolorization and biodegradation analysis Decolorization of all four dyes was monitored by UV–visible spectral analysis (Schimadzu UV–Vis 1800, Japan), while biodegradation of Joyfix Red RB was monitored by high-performance liquid chromatography (HPLC), Fourier transform infrared spectroscopy (FT-IR) and gas chromatography coupled with mass spectroscopy (GC–MS). The culture broth was centrifuged after complete decolorization in the optimized condition, and the supernatant was extracted with equal volume of ethyl acetate. The extracted metabolite with ethyl acetate was dried over anhydrous Na2SO4, evaporated to dryness in rotary evaporator
Organism with enzymes
Z-score mean
Z-score SD
Z-score RMS
No. of scored atoms
No. of outliers
Percentage of outliers
Aeromonas sps. Azoreductase Laccase
−0.174 0.146
1.607 1.469
0.252 0.198
642 939
6 9
0.7 0.6
Lysinibacillus sps. Azoreductase −0.643 Laccase 0.038
1.804 1.647
0.178 0.11
758 986
2 1
0.2 0.1
and dissolved in methanol for further analysis. During UV–visible analysis (350–800 nm), change in absorption spectra of the decolorized samples was noted at the respective characteristic peak area (λmax) and compared with control dyes. HPLC analysis was performed in Shimadzu LC 40102010 system equipped with dual absorbance detector, using C18 column (symmetry, 4.6 × 250 mm) with HPLC grade methanol as a mobile phase at flow rate of 1.0 mL/min for 10 min at 470 nm. FTIR analysis was carried out to investigate functional groups of control and biodegraded sample by using Perkin Elmer (spectrum RX I). It was in the mid IR-region of 400–4000 cm−1 with 16 scan speed. The samples were mixed with spectroscopically pure KBr (potassium bromide) in the ratio (5:95). The pellets were fixed in the sample holder and analyzed. The metabolites produced during biodegradation of Joyfix Red RB were identified using 45XGC-44 gas chromatography (GC) coupled with Scion MS-40 mass spectroscopy (Bruker). The ionization voltage was 70 eV. Helium was used as carrier gas at a flow rate of 1.0 mL/min and run time of 26 min. GCMS was conducted in the programming mode with a DB-WAX column (0.25 mm–30 mm). The column oven temperature was initially 80 °C for 2 min, and then increased linearly at 10 °C up to 250 °C held for 26 min. The metabolites were identified on the basis of mass spectrum and NIST library.
Fig. 3. Homologue enzyme model and Ramachandran Plot for (a) laccase (Aeromonas hydrophila), (b) azoreductase (Aeromonas hydrophila), (c) laccase (Lysinibacillus sphaericus) and (d) azoreductase (Lysinibacillus sphaericus).
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Table 5a Glide Score obtained after docking azo dyes with bacterial enzymes. Bacterial species/enzyme
Glide score (kcal/mol) of Azo dyes Joyfix Red RB
Remazole Red RR
Reactive Red F3B
Reactive Yellow F3R
Aeromonas hydrophila Laccase −5.591 Azoreductase –
−5.069 −0.194
−3.522 –
−5.264 –
Lysinibacillus sphaericus Laccase – Azoreductase −4.236
−1.213 −5.047
−3.735 −5.783
– −1.862
2.6. In silico study for biological decolorization 2.6.1. Homology modeling The crystal structures of enzymes were unavailable, so homologue models of the enzymes were built. The protein sequence of azoreductase of Aeromonas hydrophila (Accession No. WP_016350845) and Lysinibacillus sphaericus (Accession No. B1HYS6), as well as laccase of Aeromonas hydrophila (Accession No. WP_017787102) and Lysinibacillus sphaericus (Accession No. ACA39600), was retrieved from NCBI GenBank (Benson et al., 2000). The template structure was identified using BLASTp tool (Altschul et al., 1997) with Protein Databank. The crystal structure of 1 T58 Chain A and 3 W77 Chain A for azoreductase of Aeromonas hydrophila and Lysinibacillus sphaericus, respectively, whereas crystal structure of 1RW0 Chain A and 1T8H Chain A for laccase of Aeromonas hydrophila and Lysinibacillus sphaericus, respectively, was downloaded from Protein Data Bank (PDB) (Sussman et al., 1998) and was used as template. The structures of selected templates were determined by X
Table 5b Binding details of azoreductase of Lysinibacillus sphaericus and laccase of Aeromonas hydrophila with the azo dyes. Organism with enzyme
Azo dyes
Enzyme residues
No. of H bond
H bond distance (Å)
Azoreductase of Lysinibacillus sphaericus
Joyfix Red RB
TYR (H) LYS (H) ASN (H) GLY (H) ARG (H) ASN (H) ASN (H) ASN (H) ARG (H) ARG (H) HIS (H) ASN (H) SER (H) SER (H) ARG (H) ARG (H) ARG (H) GLN (H) TRP (O) ARG (H) TRP (H) ARG (H) ARG (H) ARG (H) ARG (H) TRP (H) TRP (H) ASN (H) ARG (H) ARG (H) TRP (H) TRP (H) ASN (H)
2
1.97 2.00 2.04 1.78 2.13 1.71 2.00 2.01 1.66 1.82 2.20 1.93 3.43 2.05 1.72 1.62 2.19 2.05 2.10 1.55 1.73 1.86 1.79 1.96 2.07 2.38 2.14 2.13 1.72 2.04 2.50 1.90 2.18
Remazole Red RR Reactive Red F3B Reactive Yellow F3R
Laccase of Aeromonas hydrophila
Joyfix Red RB
Remazole Red RR
Reactive Red F3B
Reactive Yellow F3R
3
3
3
7
5
5
5
Diffraction method, which is having less than 3 Å of resolution. The 3D model of all the enzymes was built by employing Consensus energy-based method by conglomerating corresponding region and identical sites from the template structure from PRIME module of Schrodinger Inc. (Jacobson et al., 2004). [Coordinates of each model are attached as supplementary] 2.6.2. Molecular docking study Molecular docking of azo dyes (ligands) with modeled enzymes was performed using Glide application of Schrödinger Inc. (Friesner et al., 2004). To understand the best ligand pose, all possible conformation and orientation of the ligands that bind with the receptor significantly were examined. The ligands were prepared using LigPrep tool and the modeled enzymes were preprocessed using PrepWizard tool of Schrödinger Inc. The enzyme structures were refined by hydrogen addition, bond-order assignment, hetero atoms removal, protein optimization and energy minimization. A grid-based, extra precision, flexible ligand docking was carried out for selected azo dyes with modeled enzymes. Table 1 is the information of grid point set-up for the modeled protein to dock with dyes. The grid points were selected based on the hydrophobic and hydrophilic combinations of the dye structures that could be interacted. To select exact pocket of the binding site to interact, grid points were selected for the whole protein by retaining its chirality of the complex structure. The binding affinity of the ligands was also analyzed. The analysis was based on the Glide Score multi-ligand scoring function combined with Emodel scoring, ranks all ligand poses. The interaction of each dye with enzyme residues was carefully examined. 2.7. Reverse validation of in silico analysis via in vitro studies The binding profile of the remaining three dyes, that is, Remazol Red RR, Reactive Red F3B and Reactive Yellow F3R, obtained by in silico analysis was correlated with biological decolorization percentage obtained by Uv–vis spectral analysis. Based on the dry laboratory results, decolorization experiments were performed as explained previously to confirm that the dry laboratory studies of enzyme and dye interaction can assist in examining decolorization efficiency of bacterial source and its respective enzyme, thereby aiding in the bioremediation process by reducing the need of preliminary wet laboratory studies. 3. Results and discussion 3.1. Isolation, screening, and identification of microorganisms Based on different colony morphology, 19 different bacterial strains were raised as pure culture and named SK1 to SK19. Owing to best decolorizing ability, the bacterial strains SK13 and SK16 were subjected to 16S rDNA sequencing method of identification and found to be Lysinibacillus sphaericus SK13 and Aeromonas hydrophila SK16 and submitted to the GenBank database under NCBI Accession Numbers KF032717 and KF032718, respectively. The absorption spectra, absorption maxima and chemical structure, of the four dyes are shown in Table 2. The phylogenetic tree constructed based on the partial sequences of 16S rDNA gene of twenty-seven bacterial strain is shown in Fig. 1 along with bootstrap values. Among the twenty-seven bacterial strain, the strain Aeromonas hydrophila SK16 and Lysinibacillus sphaericus SK13 showed higher dye degrading activity than other strains. Both the strains exhibited 54% of bootstrap values between them, while Lysinibacillus sphaericus SK13exposed 100% of bootstrap values with Lysinibacillus species strain JMC-UBL 45. 3.2. Decolorization analysis All the 19 isolates obtained, when subjected to decolorization of Joyfix Red RB which is a representative of azo group containing reactive
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Fig. 4. Enzyme-dye binding profile for azoreductase of Lysinibacillus sphaericus species (a–d) and laccase of Aeromonas hydrophila species (e–h) for the four dyes, Joyfix Red RB, Remazole Red RR, Reactive Red F3B and Reactive Yellow F3R.
dye (100 mg L−1) in nutrient broth, demonstrated varying levels of efficiency in both shaking and static conditions at 37 °C and pH 7 and are calculated in percentage (%) of decolorization from the optical density. Every isolate was capable of decolorizing Joyfix Red RB dye to varying extents from almost No Decolorization (ND) to 88.52% (SK13) and 91.02% (SK16) of decolorization after 72 h (Fig. 2). The isolate SK16 was capable of decolorizing the Joyfix Red RB to a maximum of 85% within 24 h (data not shown). The isolate SK13 was also equally capable of decolorizing to a maximum of 85%, but in 48 h (data not shown). Experiments revealed that Joyfix Red RB, Remazol Red RR, Reactive Red F3B and Reactive Yellow F3R dyes were decolorized by
SK13 and SK16 in such a way that their absorption peak at 520 and 450 nm in the visible range disappeared, thus indicating molecular rearrangement of the dye (Table 2). Reactive Yellow F3R (100 mg L−1) was decolorized to a maximum of 90.40% by SK16 under standardized non-shaking conditions of 37 °C and pH 8 in nutrient broth, while Reactive Red F3B,Joyfix Red RB and Remazol Red RR were decolorized to a maximum of 89%, 88.75% and 88.20%, respectively (Table 3). However, all organisms decolorized the Joyfix Red RB better in static condition than in shaking condition though without significant difference (Fig. 2). Similar results were also observed by Saratale et al. (2011) on decolorizing various textile azo dyes. It has been reported
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Table 6 Comparison of in vitro and in silico analysis—reverse validation. Dye and organism
Enzyme
Joyfix Red RB SK16 (Aeromonas hydrophila) SK13 (Lysinibacillu ssphaericus)
Laccase Azoreductase
Remazole Red RR SK16 (Aeromonas hydrophila) SK13 (Lysinibacillus sphaericus)
G Score Laccase Azoreductase
Reactive Red F3B SK16 (Aeromonas hydrophila) SK13 (Lysinibacillus sphaericus)
G Score Laccase Azoreductase
Reactive Yellow F3R SK16 (Aeromonas hydrophila) SK13 (Lysinibacillus sphaericus)
G Score Laccase Azoreductase
In vitro
In silico
Decolorization % 88.75 85 In silico Decolorization % −5.069 −5.047 In silico Decolorization % −3.522 −5.783 In silico Decolorization % −5.264 −1.862
G Score −5.591 −4.236 In vitro 88.20 86.25 In vitro 89.00 90.81 In vitro 90.40 86.84
that under static conditions, the feeding of carbon sources either simple or complex could affect the decolorization process and that most of the reduction of azo dyes to amines occur during active bacterial growth (Banat et al., 1996; Van Der Zee and Villaverde, 2005; Yoo et al., 2001). Further, it is assumed that under static conditions (anoxic), reductive enzymes activities are higher; however, a small amount of oxygen is also required for the oxidative enzymes which are involved in the degradation of azo dyes (Knapp and Newby, 1995). It was also observed that the decoloration was far superior under static conditions, although it also occurred under shaking conditions. Bacterial strains SK1, SK3, SK4, SK8 and SK18 demonstrated decoloration under shaking conditions indicating aeration and agitation augment the decolorization process. Generally, azo dyes undergo degradation under static (anoxic) conditions and that is what depicted by other bacterial isolates, especially SK13 and SK16, which decolorized the chosen dyes to the maximum. Azoredutase and laccase are key enzymes responsible for reductive azo dye degradation in bacterial species. The demonstration of decoloration by few strains under shaking conditions is attributed to the varying azoreductase type enzymes produced by the strains or dye might have absorbed on to bacterial surfaces due to its reactive nature (Naeem et al., 2009). Bacterial azoreductases have been shown to be inducible flavoproteins and to use both NADH and NADPH as electron donors. The presence of oxygen normally inhibits the azo bond reduction, since aerobic respiration may dominate use of NADH, thus impeding electron transfer from NADH to the azo bonds. The advantage of the anaerobic reduction of azo dyes is that the depletion of oxygen is easily accomplished under static conditions. However, the precise mechanism of anaerobic azo reduction is not yet totally understood. Earlier studies provided evidence that bacterial anaerobic azoreduction was linked to electron transport chain and suggested that dissimilatory azo reduction was a form of bacterial anaerobic respiration. In addition, various models for the non-specific azo reduction which did not require transport of azo dyes or reduced flavins through cell membrane and that described the extracellular reduction of azo dyes by different bacterial species were recently suggested. These results suggested that azo dye reduction was a strain-specific mechanism that could be performed by an azoreductase enzyme or by a more complex metabolic pathway (Franciscon et al., 2009). Therefore, consideration of multiple aspects in degradation studies of azo dyes cannot be ignored and a detailed physiological understanding of such bacterial strains is needed for standardization of bioremediation of textile dyes containing wastewater. 3.3. In silico analysis for decolorization 3.3.1. Enzyme modeling The protein sequences for the bacterial enzymes obtained from GenPept Databank were used to obtain template protein by searching
against inherent NCBI BLAST server of PRIME homology modeling workflow. The template protein was used to build homologue enzyme model, and the modeled enzymes, azoreductase and laccase were validated by analyzing Ramachandran plot (Fig. 3). The phi–psi distribution for residues more than 90% constituting core alpha (A), core beta (B) and core left-handed alpha was found in most allowed regions for all modeled enzyme (Morris et al., 1992). Z score of Azoreductase and Laccase modeled protein from Aeromonas species and Lysinibacillus species was predicted using SAVES server. The Z score with standard deviation of modeled one with library accessed conformations was analyzed (Table 4). The limitation of Z score should be + 3 to − 3 based on its rmsD and percentage of outliers. So all the structures used for this study were validated. 3.3.2. Enzyme–ligand binding analysis by molecular docking Post-docking analysis was observed that the enzyme laccase of Aeromonas hydrophila showed seven site interactionswith a binding score of −5.591 kcal/mol (Tables 5a, 5b). This shows that the dye Joyfix Red RB interacts with the laccase enzyme of SK16 responsible for binding with the dye and hence can be attributed for causing maximum decolorization. Likewise, it is observed that the Reactive Red F3B possess binding score of −5.783 kcal/mol (Table 5a) with three site interactions (Table 5b) with the enzyme azoreductase of Lysinibacillus sphaericus. As per the experimental analysis, Reactive Red F3B was found to undergo 90.81% decolorization by SK13 that is the docking score must be due to azoreductase of L. sphaericus. The site–site interaction of enzyme residue and dye atom provided a view for ligand orientation and binding mode responsible for dye and enzyme interaction (Fig. 4). Docking score of interacted complex (Enzyme and Dye) showed that both the species L. sphaericus and A. hydrophila possess good interaction with all azo dyes except Remazol Red RR with A. hydrophila and Reactive Yellow F3R with L. sphaericus (Tables 5a, 5b). It is observed that the dye Reactive Red F3B interacts the most with azoreductase enzyme of L. sphaericus and that of Joyfix Red RB for laccase enzyme of A. hydrophila. From spectroscopic study and analysis, it is observed that the Joyfix Red RB was decolorized by both bacterial species but by 88.75% by SK16 (A. hydrophila) in static condition which also agrees with our docking results. 3.4. Comparison of in vitro and in silico analysis and its reverse validation The decolorization percentage obtained by Joyfix Red RB treatment complied with the in silico analysis in terms of G Score implying that SK16 showed more decolorization than SK13. Therefore, the use of a reverse approach by first doing in silico studies and then confirming it with wet laboratory data was attempted (Table 6). The in silico analysis in terms of G Score for the remaining three dyes was carried out. The G Score for Remazol Red RR, Reactive Yellow F3R and Reactive Red F3B was in agreement with the experimental data in terms of decolorization percentage. This in silico molecular docking approach can be used to screen large number of bacterial strains to choose the best decolourizers among given samples, eliminating the need for time-consuming and cumbersome preliminary screening by conventional method of analyzing the decolorization percentages of all dye and bacterial strain combinations. 3.5. Biodegradation analysis of Joyfix Red RB To identify the possible mechanism of dye decolorization and degradation, biotransformation products of Joyfix Red RB by UV– visible spectroscopy, HPLC, FTIR and GC–MS were analyzed. Azo dye decolorization occurs due to the enzymatic reduction of azo bonds by bacterial species under static conditions (Stolz, 2001). Peak observed at 520 nm (0 h) decreased without any shift in λmax till complete decolorization of the dye (72 h). Virtually zero absorbance at λmax after 72 h incubation (Table 2) confirms dye removal indicating
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Fig. 5. FTIR spectrum of (a) Joyfix Red RB and (b) metabolites obtained after its biodegradation.
biodegradation as the mechanism for decolorization of dyes as established by previous studies (Saratale et al., 2012). The HPLC elution profile of Joyfix Red RB parent dye showed a single peak at 1.472 min (data not shown). After degradation, parent dye showed several detectable peaks at retention times 1.522, 1.800, 3.068 and 3.804 min which confirmed biotransformation by A. hydrophila SK16. FTIR spectrum of Joyfix Red RB parent dye showed a peak at 3443 cm−1 for (intra-molecular hydrogen bonded) O–H stretching, a peak at 2093 cm−1 for NH3 stretching, azo bond NN at 1608 cm−1, a peak at 1549 cm−1 for CN stretching, presence of nitrosamine NO at 1490 cm−1, sulfonic group SO at 1047 cm−1, a peak at 1212 cm−1 for C–N vibration and the peaks at 892, 840 and 744 cm−1 representing C–H deformations, respectively (Fig. 5). FTIR spectrum of 48 h extracted sample showed charged amines N–H at 3781 cm−1, peak at 2362 cm−1
for NH+stretching, peak at 1107 cm−1 for R–O–R stretching. As the lack of peak at 1608 cm−1 for azo bond which was present in parent dye, it indicates cleavage of azo bond by azoreductase and confirms complete biodegradation of Joyfix Red RB by A. hydrophila SK16. GC–MS analysis was carried out to identify the metabolite produced during biodegradation of Joyfix Red RB. Based on the m/z and molecular weight, GC–MS pathway has been proposed. It showed four metabolites viz. sodium 3-aminobenzenesulfonate (molecular weight 195, m/z 196, retention time 15.100), sodium 4amino-5-hydroxynaphthalene-2-sulfonate (molecular weight 261, m/z 264, retention time 24.316), sodium (3E,5Z)-4-amino-6hydroxyocta-1,3,5,7-tetraene-2-sulfonate (molecular weight 239, m/z 239, retention time 20.287) and sodium (3E,5Z)-4-amino-6hydroxyhexa-13,5-triene-2-sulfonate (molecular weight 213, m/z 213, retention time 20.915) as end product (Fig. 6).
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Fig. 6. Proposed pathway for Joyfix Red RB biodegradation by Aeromonas hydrophila SK16 and its related mass peak.
It is known that several enzymes are present in the microsomal and cytosolic fraction of the microorganisms (Dawkar et al., 2008; Parshetti et al., 2006). Most of the enzymes have an oxidative mechanism, which might be used in the degradation of dyes (Jadhav and Govindwar, 2006). The presence of enzymes such as laccase and azoreductase causes asymmetric cleavage of dye as well as reductive cleavage of azo bond, respectively, generating smaller molecular weight products from complex dyes (Dawkar et al., 2008; Kalyani et al., 2009; Telke et al., 2008). Hence, the biodegradation of Joyfix Red RB dye was confirmed through these analytical studies by the consecutive action of oxidoreductive enzymes present in A. hydrophila SK16. 4. Conclusions In this study, L. sphaericus SK13 and A. hydrophila SK16 demonstrated significant potential for decolorization of four azo dyes. Spectroscopic and molecular docking analysis was in good agreement. Hence, dye-
enzyme docking maybe considered as a preliminary tool to simplify conventional wet laboratory procedure in bioremediation. UV–vis spectroscopy, HPLC, FTIR and GCMS of control dye and extracted metabolites confirmed biodegradation of Joyfix Red RB by A. hydrophila SK16. A possible biodegradative pathway for this dye was proposed. To our knowledge, this is the first report of a combined in silico and in vitro approach and its reverse validation for bioremediation of textile azo dyes containing wastewater. The foregoing results suggest that the potential utilization of techniques in microbiology, molecular biology and biochemistry coupled with the advances in genomics and proteomics shall revolutionize various aspects of fundamental biological sciences and may offer a wide range of possibilities for screening and enhancing the performance of bacterial treatments employed for azo dye containing textile wastewater. However, potential of bacterial decolorization and degradation of azo dyes needs to be demonstrated for its application in treatment of real time effluents using appropriate bioreactor system and toxicity studies.
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