Optimization of phycocyanin extraction from Spirulina platensis using factorial design

Optimization of phycocyanin extraction from Spirulina platensis using factorial design

Bioresource Technology 98 (2007) 1629–1634 Optimization of phycocyanin extraction from Spirulina platensis using factorial design S.T. Silveira, J.F...

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Bioresource Technology 98 (2007) 1629–1634

Optimization of phycocyanin extraction from Spirulina platensis using factorial design S.T. Silveira, J.F.M. Burkert, J.A.V. Costa, C.A.V. Burkert, S.J. Kalil

*

Department of Chemistry, Fundac¸a˜o Universidade Federal do Rio Grande, P.O. Box 474, Rio Grande-RS 96201-900, Brazil Received 3 September 2005; received in revised form 30 May 2006; accepted 31 May 2006 Available online 8 September 2006

Abstract Phycocyanin extraction from cyanobacteria Spirulina platensis was optimized using factorial design and response surface techniques. The effects of temperature and biomass-solvent ratio on phycocyanin concentration and extract purity were evaluated to determine the optimum conditions for phycocyanin extraction. The optimum conditions for the extraction of phycocyanin from S. platensis were the highest biomass-solvent ratio, 0.08 g mL1, and 25 C. Under these conditions it’s possible to obtain an extract of phycocyanin with a concentration of 3.68 mg mL1 and purity ratio (A615/A280) of 0.46.  2006 Elsevier Ltd. All rights reserved. Keywords: Extraction; Optimization; Phycocyanin; Spirulina platensis

1. Introduction In cyanobacteria, the light-harvesting pigments include chlorophyll-a, carotenoids and phycobiliproteins (Reis et al., 1998). The latter are proteins with linear tetrapyrrole prosthetic groups, called bilins, found not only in cyanobacteria but also in red algae and cryptomonads (Bermejo et al., 2002). Phycobiliproteins are divided into three main classes according to their structure: phycoerythrins, phycocyanin and allophycocyanins (Bermejo et al., 2003). The phycocyanin has been used mainly as a food pigment, however, small quantities are included as biochemical tracers in immunoassays due to their fluorescent properties (Vonshak, 1997). Recently, it has been observed that phycocyanin also has shown anti-inflammatory and anti-cancer properties (Reddy et al., 2003). The cyanobacteria Spirulina platensis is an excellent source of phycocyanin. The protein fraction may contain up to 20% of phycocyanin (Vonshak, 1997). Presently, studies were accomplished evaluating the physical-chemical and nutritional parameters of the cultivation (Costa et al., *

Corresponding author. Tel.: +55 53 3233 8754; fax: +55 53 3233 8720. E-mail address: [email protected] (S.J. Kalil).

0960-8524/$ - see front matter  2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2006.05.050

2000, 2003) as well as determining the engineering parameters of the cultivation process (Costa et al., 2004). Several factors can influence the phycocyanin extraction. The most important are, cellular disruption method, type of solvent, biomass-solvent ratio and extraction time (Abalde et al., 1998; Reis et al., 1998). Factorial design of a limited set of variables is advantageous when compared to the conventional method which varies a single parameter per trial. The latter approach frequently fails to locate optimal conditions due to its failure to clearly show possible effects of interactions between parameters (Kalil et al., 2000). In this work, the best solvent for phycocyanin extraction from S. platensis was first investigated. Subsequently, the effects of temperature and biomass-solvent ratio on the phycocyanin concentration and extract purity were evaluated to establish the optimum conditions for phycocyanin extraction. 2. Methods 2.1. Culture conditions of Spirulina platensis Spirulina platensis LEB 52 (Costa et al., 2000) was cultivated in a 450 L open outdoor photo-bioreactors, under

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Table 1 Coded levels and real values (in parentheses) for a full factorial design, phycocyanin concentration (PC) and extract purity (EP) during extraction Run

X1

X2

0h

4h

10 h

24 h

30 h

PC

EP

PC

EP

PC

EP

PC

EP

PC

EP

1 2 3 4 5 6 7 8 9 10 11 12

1 (0.0202) +1 (0.0698) 1 (0.0202) +1 (0.0698) 1.41 (0.01) +1.41 (0.08) 0 (0.045) 0 (0.045) 0 (0.045) 0 (0.045) 0 (0.045) 0 (0.045)

1 (23.6) 1 (23.6) +1 (41.4) +1 (41.4) 0 (32.5) 0 (32.5) 1.41 (20) +1.41(45) 0 (32.5) 0 (32.5) 0 (32.5) 0 (32.5)

0.68 1.13 0.68 0.77 0.21 1.74 0.42 0.51 0.78 0.98 0.98 1.06

0.57 0.59 0.58 0.58 0.40 0.43 0.54 0.54 0.40 0.43 0.42 0.43

0.85 3.15 0.88 3.07 0.45 3.74 2.00 2.02 2.02 2.01 2.01 2.03

0.51 0.49 0.44 0.46 0.44 0.46 0.49 0.43 0.46 0.46 0.45 0.45

0.86 3.36 0.85 3.40 0.47 3.77 2.08 1.97 2.01 1.97 2.00 2.04

0.46 0.46 0.40 0.47 0.43 0.42 0.45 0.38 0.42 0.43 0.42 0.43

0.86 3.25 0.75 2.45 0.44 3.16 2.09 1.51 2.01 2.16 1.98 2.00

0.42 0.43 0.42 0.44 0.46 0.49 0.41 0.38 0.41 0.41 0.43 0.45

0.86 3.14 0.65 1.81 0.42 2.86 2.05 1.28 1.86 2.10 1.81 1.82

0.40 0.43 0.37 0.31 0.45 0.45 0.40 0.33 0.46 0.49 0.46 0.49

X1 = biomass-solvent ratio (g mL1). X2 = temperature (C).

uncontrolled conditions, in the south of Brazil. During these cultivations, water was supplemented with 20% Zarrouk synthetic medium (Zarrouk, 1966), with an initial biomass concentration of 0.15 g L1. Samples were taken every 24 h to determine the biomass concentration via optical density measurements at 670 nm (Costa et al., 2002). At the end of cultivation, the biomass was recovered by filtration, dried at 40 C for 48 h, frozen at 18 C, homogenized and sieved (the perforations on the sieve being 150 mesh). 2.2. Phycocyanin extraction with different solvents Phycocyanin extraction was evaluated in terms of phycocyanin concentration (Eq. (1)) using different solvents, including, distilled water, 10 mM sodium phosphate buffer (pH 7.0), 10 mM sodium acetate buffer (pH 5.0), NaCl 0.15 M and CaCl2 10 g L1 (Abalde et al., 1998; Bermejo et al., 2003). The extraction was carried out by mixing 2 g of dried biomass with 50 mL of the solvent, in a rotary shaker at 30 C. Samples were collected at 24, 48 and 72 h. After centrifugation, the optical density of the supernatant was measured at 615 and 652 nm. In all experiments, 0.01% (p/v) of sodium azide was added. Phycocyanin concentration (PC), according to Bennett and Bogorad (1973), was defined as PC ¼

ðOD615  0:474ðOD652 ÞÞ ; 5:34

ð1Þ

variable were chosen, the upper and lower limits of these being set in the range described in the literature. In the statistical model, the coded variables were defined as follows: X1 = biomass-solvent ratio and X2 = temperature, and the dependent variables being phycocyanin concentration (PC) and extract purity (EP). Table 1 shows the independent variables and their levels, as well as, the responses evaluated. The experiments were carried out using distilled water in a rotary shaker at 100 rpm. Samples were collected at 0, 4, 10, 24 and 30 h to determine the phycocyanin concentration and the extract purity by Eqs. (1) and (2), respectively. The purity of phycocyanin extract was monitored spectrophotometrically by the A615/A280 ratio (Abalde et al., 1998). This relationship is indicative of the extract purity of phycocyanin with respect to most forms of contaminating proteins. Absorbance at 615 nm indicates the phycocyanin concentration, while that at 280 nm is due to the total concentration of proteins in the solution (Liu et al., 2005). Therefore, the extract purity of phycocyanin (EP) was defined as EP ¼

OD615 ; OD280

ð2Þ

where EP is the extract purity, OD615 is the optical density of the sample at 615 nm, OD280 is the optical density of the sample at 280 nm. The yield of the extraction was defined as

where PC is the phycocyanin concentration (mg mL ), OD615 is the optical density of the sample at 615 nm, OD652 is the optical density of the sample at 652 nm.

PC  V ; ð3Þ DB where PC is phycocyanin concentration (mg mL1), V is the volume of solvent (mL), DB is dried biomass (g).

2.3. Optimization of phycocyanin extraction

3. Results and discussion

The influence of temperature and biomass-solvent ratio on phycocyanin extraction was evaluated using a full factorial design (22 plus star configuration) with four replicates in the central points, which was a total of 12 treatment combinations (Box et al., 1978). Five levels of each independent

3.1. Influence of different solvents on the phycocyanin extraction

1

Yield ¼

The phycocyanin content during the extraction with different solvents was investigated, and the results are

S.T. Silveira et al. / Bioresource Technology 98 (2007) 1629–1634 Table 2 Tukey’s test for the different solvents after 24 h of extraction Solvent Water Phosphate buffer pH 7.0 Acetate buffer pH 5.0 NaCl 0.15 M CaCl2 10 g L1 a b

PC (mg mL1) a

3.73 4.20a 1.84b 3.32a 3.48a

Std. err. 0.12 0.72 0.23 0.26 0.74

Differ significantly. p < 0.05.

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Synechococcus sp. IO201 of 27 lg mL1, and Minkova et al. (2003) extracting C-phycocyanin from fresh biomass of S. fusiformis of 1.28 mg mL1. The statistical analysis was performed with data obtained at 24 h of extraction; there was no significant increase in the yield after one day. The results for the Tukey’s test accomplished with the different solvents is presented in Table 2. The Tukey’s test demonstrated that, at a 95% confidence level, only the 10 mM sodium acetate buffer (pH 5.0) differed from the others and represented the lowest phycocyanin concentration. Near the isoelectric point, proteins interact less in water, reducing the extraction amounts. However, pH and ionic strength similar to intracellular conditions lead to improved extraction. It was observed that extraction with water did not differ much from that of 10 mM sodium phosphate buffer (pH 7.0), probably due to mechanical disruption of cells, which caused increased release of the phycocyanin. A preliminary attempt with different solvents was carried out to determine the factors most influencing the phycocyanin extraction, considerably reducing the number of experiments needed for the results presented in the next section. 3.2. Optimization of phycocyanin extraction

Fig. 1. Phycocyanin concentration (PC) with different solvents as a function of time.

displayed in Table 2. Fig. 1 shows that in the first 48 h of extraction, 10 mM sodium phosphate buffer (pH 7.0) extracted the largest amount of phycocyanin, approximately 4.20 mg mL1, followed by water with a phycocyanin concentration of 3.73 mg mL1. After 72 h, water extracted the largest amount, 4.54 mg mL1. These results are superior to those reported by Abalde et al. (1998) obtaining a phycocyanin concentration from

The experimental conditions and the results of the phycocyanin concentration (PC) and extract purity (EP) as a function of time, for the experimental design, are shown in Table 1. The statistical analysis was performed with data obtained after 4 h of extraction, as there was no significant increase in the responses evaluated (Figs. 2 and 3). In this period, the phycocyanin concentration varied from 0.45 mg mL1 (run 5) to 3.74 mg mL1 (run 6), while the extract purity varied slightly from 0.43 (run 8) to 0.51 (run 1).

Fig. 2. Phycocyanin concentration (PC) for each run for the factorial design after 30 h of extraction.

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Fig. 3. Extract purity (EP) for each run for the factorial design after 30 h of extraction.

The results obtained in this work demonstrated that the purity of the extract was significantly influenced by temperature. High temperature resulted in reduced purity because it facilitated the extraction of other proteins. Since the phycocyanin concentration was only slightly affected by temperature, the increase of temperature did not improve phycocyanin extraction. The variable biomass-solvent ratio strongly influenced the phycocyanin concentration, and the maximum value was obtained using the largest biomass-solvent ratio. This observation is important because it makes possible the use of smaller volumes of extractant in the purification steps. In addition, the yield of extracted materials (Eq. (3)) did not vary, being 44.7 mg g1 and 46.8 mg g1 for the smallest and largest biomass-solvent ratio, respectively. Previous evaluations using a biomass-solvent ratio high than 0.08 g mL1 showed that the suspension obtained was very concentrated. At this point, the solvent is unable to promote an appropriate interaction with the biomass for efficient extraction. An estimate of a main effect is obtained by evaluating the difference in process performance caused by a change from low (1) to high (+1) levels of the corresponding factor (Haaland, 1989). The performance of the process was measured by phycocyanin concentration and extract purity responses. Both the t-test and p-value statistical parameters were used to confirm the significance of the factors studied (Tables 3 and 6). The variable most relevant to phycocyanin concentration is the biomass-solvent ratio (Table 3). An increase in biomass-solvent ratio from 0.0202 to 0.0698 led to an increase in the phycocyanin concentration, on average, 2.25 mg mL1. A change in temperature from 23.6 to 41 C reduced the phycocyanin concentration, on average, 0.02 mg mL1, probably due to denaturing of phycocya-

Table 3 Main effects and interactions analysis for phycocyanin concentration after 4 h of extraction Factor

Effect (mg mL1)

Mean Biomass-solvent ratio (1) Temperature (2) Biomass-solvent ratio · temperature a

Std. err.

t-Value

p-Value

2.00 2.25

0.003 0.009

591.58 234.48

<0.000a <0.000a

0.02 0.06

0.009 0.009

2.61 5.74

0.079 0.010a

Significant factors p < 0.05.

Table 4 Regression coefficients for phycocyanin concentration after 4 h of extraction Factor

Regression coefficient

Std. err.

t-Value

p-Value

Mean Biomass-solvent ratio (L) Biomass-solvent ratio (Q) Temperature (L) Temperature (Q) Biomass-solvent ratio · temperature

2.02 1.14 0.021 0.003 0.021 0.028

0.005 0.003 0.004 0.003 0.004 0.005

421.49 337.61 5.92 0.81 5.33 5.74

<0.000a <0.000a 0.009a 0.479 0.012a 0.010a

a

Significant factors p < 0.05.

Table 5 ANOVA for the phycocyanin concentration after 4 h of extraction Source of variation

Sum of square

Degrees of freedom

Mean square

F-ratio (model significance)

Regression Residual Lack of fit Pure error Total

10.46 0.0134 0.0131 0.0003 10.47

4 7 4 3 11

2.61 0.0019 0.0032 0.0001 –

1,373a

Regression coefficient: 0.994, F0.95,4,7 = 4.12. a F-ratio (regression/residual).

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nin. When the effects of variables are interactive, this effect can be evaluated (Box et al., 1978). In this study, the combining effect of biomass-solvent ratio and temperature resulted in a reduction in the phycocyanin concentration, on average, of 0.05 mg mL1. To construct a second order model that can predict the phycocyanin concentration (dependent variable) as a function of the biomass-solvent ratio and temperature (independent variables), the analysis of variance (ANOVA) was used to evaluate the adequacy of the fit. The regression coefficients for the phycocyanin concentration after 4 h of extraction are shown in Table 4. On the basis of the ANOVA, as shown in Table 5, for 4 h of extraction, a second order model was established (Eq. (4)), describing the phycocyanin concentration as a function of independent variables. The error factor was very low, indicating optimal precision for the experimental data. Based on the F-test, the model is predictive, since its calculated F-value was higher than the critical F-value and the regression coefficient (0.994) is close to unity. The coded model was used to generate the response surface (Fig. 4). PC ¼ 2:01 þ 0:021X21  0:021X22 þ 1:14X1  0:028X1 X2 ð4Þ

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As can be seen in Fig. 4, an increase in the biomass-solvent ratio led to an increase in the phycocyanin concentration, for the range of studied temperatures. Therefore, to maximize the phycocyanin concentration, the biomass-solvent ratio should be kept at the highest levels and at room temperature. The effects of the biomass-solvent ratio and temperature on extract purity are shown in Table 6. The temperature was the most significant variable, negatively correlated with the extract purity, at a 95% confidence level. A change in temperature from 23.6 to 41 C produced a reduction in the extract purity, on average, of 0.05. However, the biomass-solvent ratio had no effect, at a 95% confidence level. The regression coefficients for the extract purity after 4 h of extraction is presented in Table 7, and in Table 8 is shown the ANOVA for evaluating the adequacy of the fitted model. Starting from the ANOVA it was possible to generate the model that predicts the extract purity as a function of

Table 6 Main effects and interactions analysis for extract purity of phycocyanin, after 4 h of extraction Factor

Effect

Std. err.

t-Value

p-Value

Mean Biomass-solvent ratio (1) Temperature (2)a Biomass-solvent ratio · temperature

0.465 <0.000

0.002 0.005

227.8 <0.000

<0.000a 1.000

0.050 0.020

0.005 0.005

8.66 3.46

a

0.0032a 0.040a

Significant factors (p < 0.05).

Table 7 Regression coefficients for the extract purity after 4 h of extraction Factor

Regression coefficient

Std. err.

t-Value

p-Value

Mean Biomass-solvent ratio (L) Biomass-solvent ratio (Q) Temperature (L) Temperature (Q) Biomass-solvent ratio · temperature

0.455 0.003 0.002 0.023 0.007 0.010

0.003 0.002 0.002 0.002 0.002 0.003

157.60 1.72 1.11 11.28 3.27 3.47

<0.000a 0.183 0.345 0.001a 0.046a 0.040a

a

Significant factors (p < 0.05).

Table 8 ANOVA for extract purity after 4 h of extraction

Fig. 4. Response surface (a) and contour diagrams (b) for the phycocyanin concentration as a function of the temperature and biomass-solvent ratio, after 4 h of extraction.

Source of variation

Sum of square

Degrees of freedom

Mean square

F-ratio (model significance)

Regression Residual Lack of fit Pure error Total

0.0049 0.0011 0.0010 0.0001 0.0061

3 8 5 3 11

0.00165 0.000146 0.000214 0.000033

16

Regression coefficient: 0.9, F0.95,3,8 = 4.07. * F-ratio (regression/residual).

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In the method presented, a simplified approach for phycocyanin extraction that makes possible easy scale up of the phycocyanin extraction is presented. S. platensis was confirmed to be a good choice because of its high phycocyanin content and easy cultivation and processing. Acknowledgement This research was supported by Coordenac¸a˜o de Aperfeic¸oamento de Pessoal de Nı´vel Superior (CAPES). References

Fig. 5. Response surface (a) and contour diagrams (b) for the extract purity as a function of the temperature and biomass-solvent ratio, after 4 h of extraction.

the biomass-solvent ratio, temperature and the interaction among those variables, according to Eq. (5). EP ¼ 0:456  0:023X2 þ 0:007X22 þ 0:010X1 X2

ð5Þ

The response surface for the extract purity as a function of the biomass-solvent ratio and temperature is presented in Fig. 5. The extract purity was favored when using low temperatures. The variable biomass-solvent ratio slightly influenced the extract purity; this response favored using a smaller biomass-solvent ratio. 4. Conclusions The present work describes a suitable method for the extraction of phycocyanin from the cyanobacteria S. platensis. Water was chosen as the extractant, because it produced high phycocyanin concentration. In addition, it is a low cost extractant. The condition established for phycocyanin extraction was a biomass-solvent ratio of 0.08 g mL1, for 4 h, at 25 C. Under these conditions it is possible to reach an extract with a phycocyanin concentration of 3.68 mg mL1 and purity ratio (A615/A280) of 0.46.

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