Aqueous two-phase system (ATPS) composed of polyethylene glycol 6000 (PEG 6000) and sodium citrate (SC) has been proposed to recover the valuable soluble proteins from tannery wastewater. A sequential optimization strategy which included fractional factorial design (fFD) and central composite design (CCD) was employed to enhance the recovery. From this strategy, a second-order polynomial model was obtained for the protein recovery and it was validated. The optimum recovery was found as 93.46% when pH, NaCl concentration, and temperature were kept at 7.5, 0.1 M, and 33°C, respectively, for a phase system composed of 20% (w/w) PEG 6000-15% (w/w) SC. Thus the proposed ATPS can serve as an alternative to the conventional precipitation method to recover the soluble proteins from tannery wastewater.
The leather industry is one of the major foreign exchange earners in India nearly over last thirty years [
There are a few reports available in the literature for the recovery of soluble proteins from industry effluents using membrane separation processes, but the major drawback of these processes is membrane fouling [
In the context of clean environment and pollution prevention, nanotechnology could play a key role [
Therefore, a benign technique for the proteins, ATPS, has been proposed in the present study in order to recover the soluble proteins from the tannery wastewater. ATPS is a downstream processing method which uses the principles of liquid-liquid extraction. It can be formulated by mixing two hydrophilic polymers (Poly Ethylene Glycol (PEG)-Dextran) with water or one hydrophilic polymer (PEG) and inorganic salts (phosphates, sulfates, and citrates) with water [
For the first time, Saravanan et al. [
For the maximization of recovery of proteins from tannery wastewater, a sequential method of optimization using response surface methodology (RSM) has been employed which includes the following steps: screening of significant process variables which affect the protein partitioning in ATPS by a fractional factorial design (fFD), crude optimization of the most significant variables by a full factorial design (FFD) with center points, final optimization of the most significant variables by central composite design (CCD) using response surface methodology (RSM), development and verification of mathematical model and expressing the relationship between the protein partitioning and significant process variables.
PEG 6000 was purchased from Merck and used without further purification. Tri-sodium citrate, citric acid, and sodium chloride were also purchased from Merck and Millipore-Milli-Q water was used in all the experiments.
The tannery wastewater sample was prepared as discussed elsewhere [
Calculated amounts of tri-sodium citrate and citric acid were taken, and pH of the system was adjusted. ATPS was prepared by mixing appropriate amounts of PEG and citrate solutions, with tannery waste sample as described in the previous section in 15 mL graduated tubes. By the addition of water, the weight of the system was maintained at 10 g. The systems were well mixed in a vortex mixer and left in a water bath at various temperatures for overnight.
The soluble protein from the tannery wastewater was quantified by Bradford method [
The partitioning of soluble proteins in ATPS is characterized by two factors, namely, partition coefficient
Partitioning of proteins in ATPS is a complex phenomenon. It depends on many factors like type and concentration of phase-forming components, pH, temperature, presence of neutral salts, and so forth. Based on prior experiments (data not shown), the following five factors namely, concentration of PEG 6000, concentration of SC, pH of the system, concentration of NaCl, and temperature were chosen as the factors that affect the protein partitioning.
Consequently, a
Coded and uncoded values of factors of 25–1 fractional factorial design (fFD).
Experiment no. | Codeda and uncodedb values of variables | Recovery |
||||
---|---|---|---|---|---|---|
PEG (% w/w) | SC (% w/w) | pH | NaCl (M) | Temperature (°C) | ||
1 | 12 (−1) | 23(+1) | 8 (+1) | 0.3 (+1) | 20 (−1) | 67.24 |
2 | 20 (+1) | 15 (−1) | 8 (+1) | 0.1 (−1) | 40 (+1) | 68.24 |
3 | 12 (−1) | 15 (−1) | 6 (−1) | 0.1 (−1) | 40 (+1) | 33.95 |
4 | 20 (+1) | 23 (+1) | 8 (+1) | 0.3 (+1) | 40 (+1) | 83.42 |
5 | 12 (−1) | 23 (+1) | 6 (−1) | 0.3 (+1) | 40 (+1) | 52.71 |
6 | 12 (−1) | 23 (+1) | 8 (+1) | 0.1 (−1) | 40 (+1) | 50.49 |
7 | 20 (+1) | 23 (+1) | 8 (+1) | 0.1 (−1) | 20 (−1) | 52.21 |
8 | 12 (−1) | 23 (+1) | 6 (−1) | 0.1 (−1) | 20 (−1) | 37.29 |
9 | 20 (+1) | 15 (−1) | 6 (−1) | 0.1 (−1) | 20 (−1) | 29.89 |
10 | 20 (+1) | 15 (−1) | 8 (+1) | 0.3 (+1) | 20 (−1) | 71.77 |
11 | 20 (+1) | 23 (+1) | 6 (−1) | 0.3 (+1) | 20 (−1) | 54.59 |
12 | 20 (+1) | 15 (−1) | 6 (−1) | 0.3 (+1) | 40 (+1) | 64.49 |
13 | 12 (−1) | 15 (−1) | 8 (+1) | 0.3 (+1) | 40 (+1) | 75.33 |
14 | 12 (−1) | 15 (−1) | 8 (+1) | 0.1 (−1) | 20 (−1) | 61.46 |
15 | 20 (+1) | 23 (+1) | 6 (−1) | 0.1 (−1) | 40 (+1) | 48.93 |
16 | 12 (−1) | 15 (−1) | 6 (−1) | 0.3 (+1) | 20 (−1) | 58.49 |
aData in brackets; bData without brackets.
It has been observed from the analysis that the three factors, namely, pH, NaCl, and temperature are the significant factors which enhance the protein recovery. Since PEG and SC do not play a significant role in partitioning, PEG was fixed at 20% (positive effect) and SC was fixed at 15% (negative effect) for all the upcoming experiments. The three significant variables were further optimized using a 23 FFD (Table
Central composite design (CCD) of variables with % recovery as response.
Experiment no. | Codeda and uncodedb values of variables | Recovery, |
||||
---|---|---|---|---|---|---|
pH | NaCl (M) | Temperature (°C) | Experimental | Predicted | ||
1 | 6.4 (−1) | 0.14 (−1) | 24 (−1) | 76.78 | 78.30 | |
2 | 7.6 (+1) | 0.14 (−1) | 24 (−1) | 87.69 | 86.51 | |
3 | 6.4 (−1) | 0.26 (+1) | 24 (−1) | 79.68 | 78.88 | |
4 | 23 Factorial points | 7.6 (+1) | 0.26 (+1) | 24 (−1) | 84.35 | 84.82 |
5 | 6.4 (−1) | 0.14 (−1) | 35 (+1) | 88.90 | 88.45 | |
6 | 7.6 (+1) | 0.14 (−1) | 36 (+1) | 89.56 | 90.39 | |
7 | 6.4 (+1) | 0.26 (+1) | 36 (+1) | 76.85 | 78.06 | |
8 | 7.6 (−1) | 0.26 (+1) | 36 (+1) | 79.21 | 77.72 | |
| ||||||
9 | 7 (0) | 0.2 (0) | 30 (0) | 90.66 | 89.81 | |
10 | I set of center points | 7 (0) | 0.2 (0) | 30 (0) | 90.50 | 89.81 |
11 | 7 (0) | 0.2 (0) | 30 (0) | 89.65 | 89.81 | |
| ||||||
12 | 6 (−1.68) | 0.2 (0) | 30 (0) | 83.22 | 82.36 | |
13 | 8 (+1.68) | 0.2 (0) | 30 (0) | 88.15 | 88.98 | |
14 | Star points | 7 (0) | 0.1 (−1.68) | 30 (0) | 92.46 | 92.05 |
15 | 7 (0) | 0.3 (+1.68) | 30 (0) | 81.51 | 81.88 | |
16 | 7 (0) | 0.2 (0) | 20 (−1.68) | 88.62 | 83.64 | |
17 | 7 (0) | 0.2 (0) | 40 (+1.68) | 78.55 | 78.51 | |
| ||||||
18 | 7 (0) | 0.2 (0) | 30 (0) | 89.56 | 89.81 | |
19 | II set of center points | 7 (0) | 0.2 (0) | 30 (0) | 88.62 | 89.81 |
20 | 7 (0) | 0.2 (0) | 30 (0) | 89.85 | 89.81 |
In order to include the curvature, few more experiments were done by adding 6 axial (star) points (Table
In this methodology, the effects of the variables on the protein recovery were fit to the second-order polynomial model according to the following equation:
For the statistical calculations, the variables were coded according to the following equation:
The fFD showing the recovery of protein from each experiment combination shown in Table
Normal probability plot of the effects.
The plot of the mean percentage recovery and experiment levels (Figure
Main effect plot for recovery (%).
Table
ANOVA table for fFD.
Source | Degrees of freedom | Sum of squares (SS) | Mean square |
|
|
---|---|---|---|---|---|
PEG | 1 | 83.63 | 83.63 | 5.93 | 0.055 |
pH | 1 | 1402.88 | 1402.88 | 99.50 | 0.000* |
NaCl | 1 | 1324.60 | 1324.60 | 93.95 | 0.000* |
Temperature | 1 | 124.43 | 124.43 | 8.83 | 0.014* |
PEG*Temperature | 1 | 294.29 | 294.29 | 20.87 | 0.001* |
Error | 10 | 140.99 | 14.10 | ||
| |||||
Total | 15 | 3370.82 |
*Significant at 95% confidence level.
The positive effect of PEG at high concentration may be because of the volume occupied by the PEG molecules with the increase in concentration decreases the free space available for the molecules in the top phase. Therefore, because of “volume exclusion effect” all the biomolecules tend to partition towards the bottom phase and thus percentage recovery in the bottom phase increases [
In contrast to this, SC had a negative effect on percentage recovery which can be explained based on the “salting-out effect”. At high salt concentrations of salt, the ions decrease the solubility of biomolecules which makes them to move to the PEG rich top phase and therefore the percentage recovery in the bottom phase decreases [
The pH presented a statistically significant positive effect for the partitioning of proteins to the bottom phase. It can be explicated with respect to the isoelectric point of the proteins. The wastewater proteins present in tannery wastewater are soluble and globular proteins [
NaCl presence in the ATPS showed a significant positive effect which may be due to the alterations of hydrophobic interactions or changes in the electrostatic potential difference. For the NaCl concentrations studied in this study (0.1 M to 0.3 M), the interaction of biomolecules with the salt rich bottom phase increases because of the changes in the electrostatic potential difference [
The temperature also indicated a significant positive effect on the percentage recovery. The increase in temperature not only alters the structure of biomolecules but also changes the phase composition of the ATPS. Therefore the increase in temperature increases the protein recovery in the bottom phase [
As a conclusion from fFD, the factors pH, NaCl, and temperature are confirmed as significant factors and therefore selected for further optimization to maximize the percentage recovery. From the Table
After crude optimization of pH, NaCl, and temperature by 23 FFD with three center points and ascertaining of optimal region, additional experiments were performed with 6 axial points and 3 more center points to frame a complete CCD (Table
Estimated regression coefficients for percentage recovery.
Term | Coefficient | Standard error of coefficient |
|
|
---|---|---|---|---|
Constant | 89.8802 | 1.1292 | 79.597 | 0.000 |
pH | 1.9683 | 0.7492 | 2.627 | 0.025* |
NaCl |
|
0.7492 |
|
0.002* |
Temperature |
|
0.7492 |
|
0.312 |
pH |
|
0.7492 |
|
0.024* |
NaCl |
|
0.7492 |
|
0.070 |
Temperature |
|
0.7492 |
|
0.004* |
pH |
|
0.7492 |
|
0.574 |
pH |
|
0.7492 |
|
0.140 |
NaCl |
|
0.7492 |
|
0.019* |
*Significant at 95% confidence level.
As discussed earlier, at 95% confidence level, the terms having
Table
ANOVA for % recovery.
Source | DF | Seq SS | Adj SS | Adj MS |
|
|
---|---|---|---|---|---|---|
Regression | 9 | 429.487 | 429.487 | 47.721 | 6.23 | 0.004* |
Linear | 3 | 186.308 | 186.308 | 62.103 | 8.10 | 0.005* |
Square | 3 | 160.677 | 160.677 | 53.559 | 6.99 | 0.008* |
Interaction | 3 | 82.501 | 82.501 | 27.500 | 3.59 | 0.054 |
Residual Error | 10 | 76.654 | 76.654 | 7.665 | ||
Lack-of-Fit | 5 | 73.949 | 73.949 | 14.790 | 27.34 | 0.001* |
Pure Error | 5 | 2.704 | 2.704 | 0.541 | ||
| ||||||
Total | 19 | 506.140 |
*Significant at 95% confidence level.
Residual plot with outlier.
Consequently, this data point was omitted and the regression was repeated for the remaining data. The regression coefficients and the ANOVA values after the omission of outlier are given in Tables
Estimated regression coefficients for recovery (%) without outlier.
Term | Coefficient | Standard Error of coefficient |
|
|
---|---|---|---|---|
Constant | 89.8078 | 0.5011 | 179.231 | 0.000* |
pH | 1.9683 | 0.3324 | 5.922 | 0.000* |
NaCl |
|
0.3324 | −9.091 | 0.000* |
Temperature |
|
0.4108 |
|
0.097 |
pH |
|
0.3317 | −4.416 | 0.002* |
NaCl |
|
0.3317 | −3.030 | 0.014* |
Temperature |
|
0.4236 |
|
0.000* |
pH |
|
0.4343 | −1.310 | 0.223 |
pH |
|
0.4343 | −3.612 | 0.006* |
NaCl |
|
0.4343 | −6.318 | 0.000* |
*Significant at 95% confidence level.
ANOVA for recovery (%) without outlier.
Source | DF | Seq SS | Adj SS | Adj MS |
|
|
---|---|---|---|---|---|---|
Regression | 9 | 483.698 | 483.698 | 53.744 | 35.62 | 0.000* |
Linear | 3 | 180.715 | 182.794 | 60.931 | 40.39 | 0.000* |
Square | 3 | 220.481 | 220.481 | 73.494 | 48.71 | 0.000* |
Interaction | 3 | 82.501 | 82.501 | 27.500 | 18.23 | 0.000* |
Residual Error | 9 | 13.578 | 13.578 | 1.509 | ||
Lack-of-Fit | 4 | 10.874 | 10.874 | 2.718 | 5.03 | 0.053 |
Pure Error | 5 | 2.704 | 2.704 | 0.541 | ||
| ||||||
Total | 18 | 497.275 |
*Significant at 95% confidence level.
Substituting the new regression coefficients into (
Residual plot without outlier.
The three-dimensional response surface plots (Figures
Response surface and contour plots showing the effect of process variables in uncoded values on % recovery. ((a) and (b)) NaCl and temperature; ((c) and (d)) pH and temperature.
In order to validate these results, experiments were done in triplicates (Table
Experimental verification of the model.
Optimized input process parameters | Modified value of input process parameters | Predicted recovery | Experimental recovery | ||||
---|---|---|---|---|---|---|---|
pH | NaCl (M) | Temperature (°C) | pH | NaCl (M) | Temperature (°C) | ||
7.45 | 0.1 | 32.72 | 7.5 | 0.1 | 33 | 94.40% | 93.46 ± 0.7% |
A sequential optimization method which consisted of fFD and CCD was used to obtain the optimum values of significant factors for the recovery of soluble proteins from tannery wastewater in PEG 6000-SC ATPS. The fFD revealed that only pH, concentration of NaCl, and temperature were the significant factors. From the CCD studies, the optimized values of these significant factors were determined: pH 7.5, NaCl 0.1 M, and temperature 33°C for a phase system composed of 20% (w/w) PEG 6000-15% (w/w) SC. The predicted and observed recoveries were 94.40% and 93.46%, respectively, which confirmed that the proposed quadratic model was valid. Thus, it is concluded that ATPS can be used as an alternative method to recover the valuable soluble proteins from tannery wastewater.
The authors declare that they have no conflict of interests.
The authors gratefully acknowledge the Department of Biotechnology, MIT, Manipal University, for providing the facilities to carry out the research work.