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Process optimization for poly-β-hydroxybutyrate production in a nitrogen fixing cyanobacterium, Nostoc muscorum using response surface methodology
Bioresource Technology 98 (2007) 987–993
Process optimization for poly-b-hydroxybutyrate production in a nitrogen fixing cyanobacterium, Nostoc muscorum using response surface methodology Laxuman Sharma, Akhilesh Kumar Singh, Bhabatarini Panda, Nirupama Mallick
*
Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721 302, India Received 19 January 2006; received in revised form 18 April 2006; accepted 21 April 2006 Available online 12 June 2006
Abstract A five-level-four-factor central composite rotary design was employed to find out the interactive effects of four variables, viz. concentrations of acetate, glucose and K2HPO4, and dark incubation period on poly-b-hydroxybutyrate (PHB) production in a N2-fixing cyanobacterium, Nostoc muscorum. Acetate, glucose and dark incubation period exhibited positive impacts on PHB yield. Using response surface methodology (RSM), a second order polynomial equation was obtained by multiple regression analysis. A yield of 45.6% of dry cell weight (dcw) was achieved at reduced level of nutrients, i.e. 0.17% acetate, 0.16% glucose and 5 mg l1 K2HPO4 at a dark incubation period of 95 h as compared to 41.6% PHB yield in 0.4% acetate, 0.4% glucose and 40 mg l1 K2HPO4 at a dark incubation period of 168 h under single factor optimization strategy. 2006 Elsevier Ltd. All rights reserved. Keywords: CCRD; Chemoheterotrophy; Nostoc muscorum; Poly-b-hydroxybutyrate; RSM
1. Introduction In today’s modern era of science and technology plastics have become one of the most widely used materials all over the world. Their applications are nearly universal: components in automobiles, home appliances, computer equipments, packages and even medical applications are areas, where plastics clearly have become indispensable. How much ever we may applaud about the quality of plastics and its uses in day-to-day life, they have long been vilified because they are environmentally unfriendly, i.e. they are not biologically degradable. The search for biodegradable plastics has led to a number of partially and completely biodegradable products. Amongst all, microbially-formed polyhydroxyalkanoates (PHAs) offer much potential for significant contributions
*
Corresponding author. Tel.: +91 3222 283166; fax: +91 3222 282244. E-mail address: [email protected] (N. Mallick).
0960-8524/$ - see front matter 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2006.04.016
as ‘‘bioplastics’’. Poly-b-hydroxybutyrate is the most widespread and thoroughly characterized PHA found in bacteria. It is accumulated as a carbon and/ or energy storage material in various microorganisms usually under limiting nutritional conditions such as N and P stresses in presence of excess carbon (Steinbu¨chel, 1991; Byrom, 1994; Liebergesell et al., 1994; Yu, 2001). Until now, PHB is been produced by heterotrophic bacteria with the help of fermentation technology. Cyanobacteria, however, are indigenously the sole prokaryotes that accumulate PHA by oxygenic photosynthesis. More than 100 cyanobacterial strains screened so far, about 70% of them were found to contain PHB at concentrations ranging from 0.04% to 6% of dry cell weight (dcw) under photoautotrophic growth conditions. Most recently however, Nishioka et al. (2001) and Sharma and Mallick (2005a) demonstrated accumulation ranging from 43-55% (dcw), respectively in Synechococcus sp. MA19 and Nostoc muscorum under phosphate-limited and chemoheterotrophic growth conditions.
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Earlier studies revealed that PHB yield in cyanobacteria was a function of various encompassing cultural and nutritional conditions. Growth phase, light-dark cycles, temperature, pH (Stal, 1992; Sharma and Mallick, 2005b; Panda et al., 2006), nutrient limitations, viz. nitrogen (Stal, 1992; Lama et al., 1996; Wu et al., 2001) and phosphorus (Nishioka et al., 2001; Panda et al., 2006), mixotrophy (Wu et al., 2001; Sudesh et al., 2002; Panda et al., 2006), chemoheterotrophy (Miyake et al., 1996; Sharma and Mallick, 2005a) and gas exchange limitation (Sharma and Mallick, 2005a) have emerged as critical variables for enhanced PHB accumulation in cyanobacterial cell. Process optimization for PHB yield in Rhizobium meliloti was studied by taking variables such as complex sucrose, urea, inoculum size and K2HPO4 by Lakshman et al. (2004). Khanna and Srivastava (2005) optimized the concentration of KH2PO4, Na2HPO4, MgSO4 Æ 7H2O and fructose for PHB production in Wautersia eutropha using central composite design. It is worth mentioning here that no report on process optimization for PHB yield in cyanobacteria using any statistical tool is yet available. Present study, therefore, envisaged to optimize some nutritional factors, viz. concentrations of acetate, glucose and K2HPO4, and dark incubation period for enhanced PHB production in N. muscorum by response surface methodology. 2. Methods 2.1. Organism and experimental conditions N. muscorum Agardh was grown axenically in NO3-free BG-11 medium (Rippka et al., 1979) at 25 ± 1 C, pH 8.0, under 14 h light (75 lmol photon m2s1 PAR): 10 h dark cycles. Phosphate deficiency was obtained by replacing K2HPO4 of the medium with equi-molar concentration of KCl. For chemoheterotrophic growth condition, cultures supplemented with glucose and acetate at different concentrations were incubated under complete darkness following Sharma and Mallick (2005a). 2.2. Growth and dry weight measurement
was washed with acetone and was dissolved again in hot chloroform. 2.4. Assay of poly-b-hydroxybutyrate (PHB) PHB was quantified following the propanolysis method of Riis and Mai (1988) with the help of gas chromatography (Clarus 500, Perkin Elmer) in split mode (1:50, v/v), equipped with Elite-1 dimethylpolysiloxane capillary column (30 m · 0.25 mm · 0.25 lm) and flame ionization detector. Benzoic acid was used as the internal standard. 2.5. Experimental design A five-level-four-factor central composite rotary design (CCRD) obtained by using the software Design-Expert 6.0.10, Stat-Ease Inc. Minneapolis, USA was employed to find out the interactive effects of four variables, viz. concentrations of acetate, K2HPO4, and glucose, and duration of dark incubation on PHB production. Stationary phase cultures of N. muscorum were transferred to BG-11 medium with varying concentrations of K2HPO4, glucose and acetate as given in Table 1. Duration of dark incubation was imposed as per the experimental design. Central composite design at the given range of the above parameters in terms of coded and actual terms is presented in Table 2. 2.6. Statistical analysis The experimental data obtained from the design were analyzed by the response surface regression procedure using the following second-order polynomial equation: X X X Y i ¼ b0 þ bi xi þ bii x2i þ bij xi xj i
Extraction of PHAs was done following Yellore and Desia (1998) with certain modifications. A known amount of cyanobacterial cells was suspended in methanol at 4 C (overnight) for removal of pigments. The pellet so obtained after discarding the supernatant was dried at 60 C. The polymer was extracted in hot chloroform followed by precipitation with cold diethyl ether. The sample was then centrifuged at 11,000 · g for 20 min to get the pellet. The pellet
ij
where Yi was the predicted response, xixj were independent variables, b0 was the offset term, bi was the ith linear coefficient, bii was the ith quadratic coefficient and bij was ijth interaction coefficient. However, in this study, the independent variables were coded as A, B, C and D. Thus the second order polynomial equation could be presented as follows: Y ¼ b0 þ b1 A þ b2 B þ b3 C þ b4 D þ b11 A2 þ b22 B2 þ b33 C 2 þ b44 D2 þ b12 AB þ b13 AC þ b14 AD þ b23 BC þ b24 BD
Growth was measured in terms of chlorophyll a following Mackinney (1941). Cell dry weight was determined gravimetrically following Rai et al. (1991). 2.3. Extraction of poly-hydroxyalkanoates (PHAs)
ii
þ b34 CD
Table 1 Levels of factors used for optimization of nutritional factors for PHB production Variable
A B C D
Name
Acetate (% w/v) K2HPO4 (mg l1) Glucose (% w/v) Period of dark incubation (h)
Level 2 (a)
1
0
1
2 (+a)
0.05 10 0.05 42
0.10 0 0.10 84
0.15 10 0.15 126
0.20 20 0.20 168
0.25 30 0.25 210
L. Sharma et al. / Bioresource Technology 98 (2007) 987–993 Table 2 Central composite design of independent variables for optimization of nutritional factors Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Coded
Actual
A
B
C
D
1 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1 2 0 0 0 0 2 1 1 0 1 1 1 0 0
1 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1 0 0 2 0 0 0 1 1 2 1 1 1 0 0
1 1 1 0 0 1 1 1 0 2 1 1 1 1 0 1 0 0 0 0 2 0 1 1 0 1 1 1 0 0
1 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1 0 0 0 2 0 0 1 1 0 1 1 1 2 0
A 0.20 0.10 0.20 0.15 0.15 0.10 0.10 0.20 0.15 0.15 0.20 0.10 0.10 0.10 0.15 0.20 0.25 0.15 0.15 0.15 0.15 0.05 0.20 0.20 0.15 0.10 0.10 0.20 0.15 0.15
B 20 0 0 10 10 20 0 20 10 10 20 0 20 20 10 0 10 10 10 10 10 10 20 0 30 0 20 0 10 10
C 0.20 0.10 0.10 0.15 0.15 0.10 0.10 0.10 0.15 0.25 0.20 0.20 0.20 0.20 0.15 0.20 0.15 0.15 0.15 0.15 0.05 0.15 0.10 0.10 0.15 0.20 0.10 0.20 0.15 0.15
D 168 168 84 126 126 168 84 168 126 126 84 84 168 84 126 84 126 126 126 42 126 126 84 168 126 168 84 168 210 126
The statistical software package, Design-Expert 6.0.10 was used for regression analysis of the experimental data and also to plot the response surface graphs. Analysis of variance (ANOVA) was used to estimate the statistical parameters. The second order polynomial equation was employed to fit the experimental data. The significance of the model equation and model terms were evaluated by F-test. The quality of fit of the polynomial model equation was expressed by the coefficient of determination (R2), adjusted R2 and ‘‘adequate precision’’. The fitted polynomial equation was expressed as three-dimensional surface plots to visualize the relationship between the responses and the experimental levels of each factor used in the design. To optimize the level of each factor for maximum response ‘‘Point Optimization’’ process was employed. The combination of different optimized parameters, which gave maximum response, i.e. maximum PHB yield was tested experimentally to see the validity of the model. 3. Results 3.1. Fitting the model The design matrix in actual terms and the experimental results of PHB accumulation in N. muscorum by the central
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composite rotary design with 6 central points, 16 cubic points and 8 axial points are presented in Table 3. Different combinations of sodium acetate (0.1–0.2%, w/v), K2HPO4 (0–20 mg l1), glucose (0.1–0.2%, w/v) and dark incubation period (84–168 h) yielded PHB as low as 16.23 and as high as 47.23% (dcw). The predicted values, calculated by using the model were in the range of 18.42–48.03% (dcw, Table 3). The regression analysis of the experimental design demonstrated that the linear model terms (A, B and C), quadratic model terms (A2, B2, C2 and D2) and interactive model terms (AB, AC, AD, BD and CD) were significant (P < 0.05, data not shown). However, the linear model term D and the interactive model term BC were found to be insignificant (P > 0.05). Applying multiple regression analysis, the results were fitted to a second-order polynomial equation. Thus the mathematical regression model for PHB production fitted in terms of coded factors was obtained as follows: YðPHBÞ ¼ þ42:42 þ 5:20A 5:98B þ 1:39C þ 0:77D 3:40A2 2:64B2 1:87C2 1:93D2 1:15AB þ 1:16AC þ 1:56AD þ 1:34BD 2:37CD:
Table 3 Central composite design matrix with measured and predicted responses of PHB yield Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Factors
Response (Y)
A
B
C
D
Predicted
Actual
0.20 0.10 0.20 0.15 0.15 0.10 0.10 0.20 0.15 0.15 0.20 0.10 0.10 0.10 0.15 0.20 0.25 0.15 0.15 0.15 0.15 0.05 0.20 0.20 0.15 0.10 0.10 0.20 0.15 0.15
20 0 0 10 10 20 0 20 10 10 20 0 20 20 10 0 10 10 10 10 10 10 20 0 30 0 20 0 10 10
0.20 0.10 0.10 0.15 0.15 0.10 0.10 0.10 0.15 0.25 0.20 0.20 0.20 0.20 0.15 0.20 0.15 0.15 0.15 0.15 0.05 0.15 0.10 0.10 0.15 0.20 0.10 0.20 0.15 0.15
168 168 84 126 126 168 84 168 126 126 84 84 168 84 126 84 126 126 126 42 126 126 84 168 126 168 84 168 210 126
35.32 33.02 39.81 42.42 42.42 24.45 32.55 33.34 42.42 37.75 32.70 36.14 21.79 25.41 42.42 48.03 39.21 42.42 43.83 33.14 32.18 18.42 21.25 46.52 19.73 27.14 18.60 45.28 36.23 42.42
33.61 36.64 42.44 43.34 43.23 23.28 32.17 35.19 41.30 38.11 32.25 37.44 22.43 26.38 42.21 47.23 40.20 44.21 42.44 31.89 30.62 16.23 20.20 43.61 20.22 26.22 20.17 46.93 36.34 40.23
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41.3
PHB (% dcw)
PHB (% dcw)
48.7 48.7 41.3 33.8 26.4
33.8 26.4
0.20 20 13
0.17 7
B: K2HPO4 -1 (mg l )
0
0.17
0.13 C: glucose 0.10 (%)
0.13 A: sodium acetate (%)
0.10
0.20 0.17
0.20
0.13 A: sodium acetate (%)
(B)
(A)
48.7
PHB (% dcw)
48.7
PHB (% dcw)
0.10
41.3 33.8 26.4
168
41.3 33.8 26.4
168
0.20 140
0.17
112 D: dark incubation 84 Period ( h)
0.10
20 140
13 112
0.13 A: sodium acetate (%)
D: dark incubation period (h)
(C)
7 84
0
B: K2HPO4 -1 (mg l )
(D)
PHB (% dcw)
48.7 41.3 33.8 26.4
168
0.20 140
0.17 112
D: dark incubation Period (h)
0.13 84
0.10
C: glucose (%)
(E) Fig. 1. 3D response surface: Interactive effects of (A) varied sodium acetate and K2HPO4 concentrations at 0.15% glucose and 126 h dark incubation period, (B) varied glucose and sodium acetate concentrations at 10 mg l1K2HPO4 and dark incubation period (126 h), (C) varied sodium acetate and dark incubation period at 0.15% glucose and 10 mg l1 K2HPO4, (D) varied K2HPO4 and dark incubation period at 0.15% each of glucose and sodium acetate, and (E) varied dark incubation period and glucose at 10 mg l1 K2HPO4 and 0.15% sodium acetate.
L. Sharma et al. / Bioresource Technology 98 (2007) 987–993
Analysis of variance (ANOVA) explained the significance of the model for PHB (F-value: 35.61, data not shown). Lack of fit was insignificant. R2 was close to unity (0.9666, data not shown). 3.2. Optimization of process PHB yield for different levels of the variables was predicted from the respective contour plots (Fig. 1(A)–(E)). Each contour curve represents an infinite number of combinations of two test variables with the other two maintained at their respective zero levels. Elliptical nature of the contour in 3D-response surface graphs (Fig. 1(A)– (E)) depicted the mutual interactions of all the variables. Fig. 1(A) explains the interaction of sodium acetate with K2HPO4, where with increasing sodium acetate concentration and decreasing K2HPO4 level, PHB production achieved a quadratic gain. Therefore, a negative effect of interaction of these variables was assumed, which could be seen from the negative sign of the coefficient of AB model term in the equation. Similarly, Fig. 1(B) explains the interaction of glucose and sodium acetate at zero level of K2HPO4 and dark incubation period. In this graph, PHB concentration increased with increase in both the variables above the zero level till certain point, but there was a sharp convergence of the curve near the boundary, explaining that addition of glucose and acetate above certain limit would not contribute for increasing PHB production further. Interaction of sodium acetate and dark incubation period was significant and positive as visualized from Fig. 1(C). However, interaction of dark incubation period and K2HPO4 followed quite a different trend (Fig. 1(D)). The convergence of the curve toward the center point of dark incubation period demonstrated that there would be no further rise in PHB yield by increasing dark incubation period above the zero level, i.e. above 126 h. The response surface graph drawn for glucose and dark incubation period at zero level of the other two variables showed negative impact (Fig. 1(E)). However, the interactive model term BC, i.e. glucose and K2HPO4 did not show significant effect on PHB accumulation, which was reflected from flat response surface and more parallel contour lines (data not shown). After knowing the possible direction for maximizing PHB production, optimization was done using ‘‘Point Optimization’’ technique. A maximum polymer yield of 47.4% (dcw) was predicted at 0.16% glucose, 0.17% acetate, 5 mg l1 K2HPO4 and a dark incubation period of 95 h. 3.3. Verification of the model Experiments were performed in triplicate using the optimized conditions to verify the model. It could be visualized from Table 4 that the predicted (47.4% dcw) and experimental (45.6% dcw) PHB content after optimization were well in agreement. Though there was not significant rise
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Table 4 PHB yield before and after optimization of nutritional parameters Variable
Beforea
After
PHB yield (% dcw) Beforea
Sodium acetate (% w/v) K2HPO4 (mg l1) Glucose (% w/v) Dark incubation period (h) a
0.4
0.17
40 0.4 168
5.0 0.16 95
41.6
After Predicted
Experimental
47.4
45.6
Sharma and Mallick (2005a).
in PHB level after optimization, the input was however, greatly reduced. The PHB content before optimization was 41.6% (dcw) at 0.4% acetate, 0.4% glucose and 40 mg l1 K2HPO4, and dark incubation period of 168 h. After optimization PHB yield was raised up to 45.6% (dcw) at 0.17% acetate, 0.16% glucose, 5 mg l1 K2HPO4 and 95 h of dark incubation period. 4. Discussion In a previous study with N. muscorum (Sharma and Mallick, 2005a,b), one factor optimization or at some instances two factors were considered, and the appropriate range of critical factor(s) contributing to the increased production of PHB was selected. The significant rise in PHB pool of N. muscorum under mixotrophic, chemoheterotrophic, gas-exchange limited conditions, and also under limitations of phosphate and nitrogen as a function of incubation period pointed towards the optimization of these factors for maximum response. Amongst these critical factors, nitrogen and gas-exchange limitations were excluded, since nitrogen limitation in this N2-fixing organism was achieved by eliminating molybdenum from the culture medium, which was used at micro level only and therefore, was difficult for assigning the different levels to study the effect on responses. Besides, the impurities present in various salts (used in preparation of the medium) cannot be avoided which may contain traces of molybdenum, as use of high-grade salts is not feasible commercially. Gasexchange limitation was also excluded owing to the slow growth rate of the organism and the longer incubation period for PHB accumulation. Therefore, nutritional parameters, viz. concentrations of glucose, acetate, phosphate and duration of dark incubation (Table 1) were considered for RSM study to maximize the PHB production in N. muscorum. The rotatable central composite design was used to get the optimum response (Tables 2 and 3). In this study, the regression equation is given using coded factors. The results showed significant effects for all the model terms except D and BC. The results were fitted to a second order polynomial model by removing the insignificant model term BC. Though insignificant, variable D was not
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neglected while fitting the model due to its interaction with other variables. According to the second order polynomial equation, the linear coefficient A (acetate), C (glucose) and D (dark incubation period) showed positive effects on PHB yield, whereas B (K2HPO4) exhibited negative impact. The model so obtained for PHB production was adequate enough as depicted from the high F-value (35.61), insignificant lack of fit (Probability > F = 0.1256) and R2 close to unity (0.9666). This indicates that 96.66% of variability in the response could be explained by this model. The contour plots in 3D response depicted the variation in PHB yield, as a function of interaction of variables. From Fig. 1(A)–(E), it is concluded that increasing sodium acetate and glucose concentrations and decreasing K2HPO4 concentration resulted into rise in PHB content as a function of time within the surface. The optimum conditions for maximum PHB yield were obtained as follows: 0.17% (w/v) sodium acetate, 5 mg l1 K2HPO4, 0.16% (w/ v) glucose and 95 h of dark incubation period for the predicted PHB yield of 47.4% (dcw) (Table 4). The experimental value of 45.6% (dcw) (Table 4) is well in agreement with that of the predicted one. Before optimization, a value 41.6% PHB was obtained at higher concentrations of glucose and acetate (0.4%, each) and 40 mg l1 of K2HPO4 at 168 h of dark incubation period (Sharma and Mallick, 2005a). The enhanced PHB production in N. muscorum under phosphate limitation is supported with the scientific basis that PHB biosynthesis is expected to increase under phosphate limitation, when reducing power may be in excess, because ATP production is known to decrease markedly with the onset of phosphate limitation, while the reduction of NADP through non-cyclic photosynthetic electron flow is not inhibited (Bottomley and Stewart, 1976; Konopka and Schnur, 1981). The optimum concentration of phosphate was 5 mg l1, rather than complete P-deficiency agrees with the findings of Nishioka et al. (2001) and Panda et al. (2005), where a minimal level of internal phosphate is essential for PHB accumulation. The stimulatory effect of acetate on PHB accumulation could be due to the direct utilization of acetate for the synthesis of the polyester by means of the usual pathway operating in prokaryotes (Dawes, 1992). Glucose utilization in cyanobacteria however, occurs via pentose phosphate pathway. Thus, the positive effect of glucose on PHB production could be attributable to the increased supply of the reduced cofactor, i.e. NADPH (Lee et al., 1995). Enhancement of PHB accumulation during dark incubation could possibly be due to the degradation of glycogen to supply acetyl-CoA (substrate for PHB biosynthesis) as reported for Gloeothece PCC 6909 and Synechocystis sp. PCC 6803 (Stal, 1992; Wu et al., 2001). In conclusion, the response surface methodology was effectively used for the optimization of the process parameters for PHB production in N. muscorum and chemoheterotrophic conditions with glucose and acetate with simultaneous limitation of phosphate were the desirable
conditions for enhanced PHB accumulation in N. muscorum. Acknowledgement Financial support from Department of Biotechnology, Ministry of Science and Technology, India is thankfully acknowledged. References Bottomley, P.J., Stewart, W.D.P., 1976. ATP pools and transients in the blue-green alga, Anabaena cylindrica. Arch. Microbiol. 108, 249–258. Byrom, D., 1994. Polyhydroxyalkanoates. In: Mobley, D.P. (Ed.), Plastics from Microbes: Microbial Synthesis of Polymers and Polymer Precursors. Munich, Hanser, pp. 5–33. Dawes, E.A., 1992. Storage polymers in prokaryotes. In: Mohan, S., Dow, C., Coles, J.A. (Eds.), Prokaryotic Structure and Function: A New Perspective. Cambridge University Press, Cambridge, pp. 88–122. Khanna, S., Srivastava, A.K., 2005. Statistical media optimization studies for growth and PHB production by Ralstonia eutropha. Process Biochem. 40, 2173–2182. Konopka, A., Schnur, M., 1981. Biochemical composition and photosynthetic carbon metabolism of nutrient limited cultures of Merismopedia tenuissima (Cyanophyceae). J. Phycol. 17, 118–122. Lakshman, K., Rastogi, N.K., Shamala, T.R., 2004. Simultaneous and comparative assessment of parent and mutant strain of Rhizobium meliloti for nutrient limitation and enhanced polyhydroxyalkanoate (PHA) production using optimization studies. Process Biochem. 39, 1977–1983. Lama, L., Nicolaus, B., Calandrelli, V., Maria, M.C., Romano, I., Gambacorta, A., 1996. Effect of growth conditions on endo- and exopolymer biosynthesis in Anabaena cylindrica 10C. Phytochemistry 42, 655–659. Lee, I.Y., Kim, M.K., Chang, H.N., Park, Y.H., 1995. Regulation of polyb-hydroxybutyrate biosynthesis by nicotinamide nucleotides in Alcaligenes eutrophus. FEMS Microbiol. Lett. 131, 35–39. Liebergesell, M., Sonomoto, K., Madkour, M., Mayer, F., Steinbu¨chel, A., 1994. Purification and characterization of the poly (hydroxyalkanoic acid) synthase from Chromatium vinosum and localization of the enzyme at the surface of poly (hydroxyalkanoic acid) granules. Eur. J. Biochem. 226, 71–80. Mackinney, G., 1941. Absorption of light by chlorophyll solution. J. Biol. Chem. 140, 315–322. Miyake, M., Erata, M., Asada, Y., 1996. A thermophilic cyanobacterium, Synechococcus sp. MA19, capable of accumulating poly-b-hydroxybutyrate. J. Ferment. Bioengg. 82, 512–514. Nishioka, M., Nakai, K., Miyake, M., Asada, Y., Taya, M., 2001. Production of poly-b-hydroxybutyrate by thermophilic cyanobacterium, Synechococcus sp. MA19, under phosphate limitation. Biotechnol. Lett. 23, 1095–1099. Panda, B., Sharma, L., Mallick, N., 2005. Poly-b-hydroxybutyrate accumulation in Nostoc muscorum and Spirulina platensis under phosphate limitation. J. Plant Physiol. 162, 1376–1379. Panda, B., Jain, P., Sharma, L., Mallick, N., 2006. Optimization of cultural and nutritional conditions for accumulation of poly-bhydroxybutyrate in Synechocystis sp. PCC 6803. Biores. Technol. 97, 1296–1301. Rai, L.C., Mallick, N., Singh, J.B., Kumar, H.D., 1991. Physiological and biochemical characteristics of a copper tolerant and a wild type strain of Anabaena doliolum under copper stress. J. Plant Physiol. 138, 68–74. Riis, V., Mai, W., 1988. Gas chromatographic determination of poly-bhydroxybutyric acid in microbial biomass after hydrochloric acid propanolysis. J. Chromatogr. 445, 285–289.
L. Sharma et al. / Bioresource Technology 98 (2007) 987–993 Rippka, R., Deruelles, J., Waterbury, J.B., Herdman, M., Stanier, R.Y., 1979. Generic assignments, strain histories and properties of pure cultures of cyanobacteria. J. Gen. Microbiol. 111, 1–61. Sharma, L., Mallick, N., 2005a. Enhancement of poly-b-hydroxybutyrate accumulation in Nostoc muscorum under mixotrophy, chemoheterotrophy and limitations of gas-exchange. Biotechnol. Lett. 27, 59–62. Sharma, L., Mallick, N., 2005b. Accumulation of poly-b-hydroxybutyrate in Nostoc muscorum: regulation by pH, light-dark cycles, N and P status and carbon sources. Bioresour. Technol. 96, 1304–1310. Stal, L.J., 1992. Poly(hydroxyalkanoates) in cyanobacteria: a review. FEMS Microbiol. Rev. 103, 169–180. Steinbu¨chel, A., 1991. Polyhydroxyalkanoic acids. In: Byrom, D. (Ed.), Biomaterials: Novel Materials from Biological Sources. Stockton, New York, pp. 124–213.
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Process optimization for poly-b-hydroxybutyrate production in a nitrogen fixing cyanobacterium, Nostoc muscorum using response surface methodology Laxuman Sharma, Akhilesh Kumar Singh, Bhabatarini Panda, Nirupama Mallick
*
Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur 721 302, India Received 19 January 2006; received in revised form 18 April 2006; accepted 21 April 2006 Available online 12 June 2006
Abstract A five-level-four-factor central composite rotary design was employed to find out the interactive effects of four variables, viz. concentrations of acetate, glucose and K2HPO4, and dark incubation period on poly-b-hydroxybutyrate (PHB) production in a N2-fixing cyanobacterium, Nostoc muscorum. Acetate, glucose and dark incubation period exhibited positive impacts on PHB yield. Using response surface methodology (RSM), a second order polynomial equation was obtained by multiple regression analysis. A yield of 45.6% of dry cell weight (dcw) was achieved at reduced level of nutrients, i.e. 0.17% acetate, 0.16% glucose and 5 mg l1 K2HPO4 at a dark incubation period of 95 h as compared to 41.6% PHB yield in 0.4% acetate, 0.4% glucose and 40 mg l1 K2HPO4 at a dark incubation period of 168 h under single factor optimization strategy. 2006 Elsevier Ltd. All rights reserved. Keywords: CCRD; Chemoheterotrophy; Nostoc muscorum; Poly-b-hydroxybutyrate; RSM
1. Introduction In today’s modern era of science and technology plastics have become one of the most widely used materials all over the world. Their applications are nearly universal: components in automobiles, home appliances, computer equipments, packages and even medical applications are areas, where plastics clearly have become indispensable. How much ever we may applaud about the quality of plastics and its uses in day-to-day life, they have long been vilified because they are environmentally unfriendly, i.e. they are not biologically degradable. The search for biodegradable plastics has led to a number of partially and completely biodegradable products. Amongst all, microbially-formed polyhydroxyalkanoates (PHAs) offer much potential for significant contributions
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0960-8524/$ - see front matter 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2006.04.016
as ‘‘bioplastics’’. Poly-b-hydroxybutyrate is the most widespread and thoroughly characterized PHA found in bacteria. It is accumulated as a carbon and/ or energy storage material in various microorganisms usually under limiting nutritional conditions such as N and P stresses in presence of excess carbon (Steinbu¨chel, 1991; Byrom, 1994; Liebergesell et al., 1994; Yu, 2001). Until now, PHB is been produced by heterotrophic bacteria with the help of fermentation technology. Cyanobacteria, however, are indigenously the sole prokaryotes that accumulate PHA by oxygenic photosynthesis. More than 100 cyanobacterial strains screened so far, about 70% of them were found to contain PHB at concentrations ranging from 0.04% to 6% of dry cell weight (dcw) under photoautotrophic growth conditions. Most recently however, Nishioka et al. (2001) and Sharma and Mallick (2005a) demonstrated accumulation ranging from 43-55% (dcw), respectively in Synechococcus sp. MA19 and Nostoc muscorum under phosphate-limited and chemoheterotrophic growth conditions.
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Earlier studies revealed that PHB yield in cyanobacteria was a function of various encompassing cultural and nutritional conditions. Growth phase, light-dark cycles, temperature, pH (Stal, 1992; Sharma and Mallick, 2005b; Panda et al., 2006), nutrient limitations, viz. nitrogen (Stal, 1992; Lama et al., 1996; Wu et al., 2001) and phosphorus (Nishioka et al., 2001; Panda et al., 2006), mixotrophy (Wu et al., 2001; Sudesh et al., 2002; Panda et al., 2006), chemoheterotrophy (Miyake et al., 1996; Sharma and Mallick, 2005a) and gas exchange limitation (Sharma and Mallick, 2005a) have emerged as critical variables for enhanced PHB accumulation in cyanobacterial cell. Process optimization for PHB yield in Rhizobium meliloti was studied by taking variables such as complex sucrose, urea, inoculum size and K2HPO4 by Lakshman et al. (2004). Khanna and Srivastava (2005) optimized the concentration of KH2PO4, Na2HPO4, MgSO4 Æ 7H2O and fructose for PHB production in Wautersia eutropha using central composite design. It is worth mentioning here that no report on process optimization for PHB yield in cyanobacteria using any statistical tool is yet available. Present study, therefore, envisaged to optimize some nutritional factors, viz. concentrations of acetate, glucose and K2HPO4, and dark incubation period for enhanced PHB production in N. muscorum by response surface methodology. 2. Methods 2.1. Organism and experimental conditions N. muscorum Agardh was grown axenically in NO3-free BG-11 medium (Rippka et al., 1979) at 25 ± 1 C, pH 8.0, under 14 h light (75 lmol photon m2s1 PAR): 10 h dark cycles. Phosphate deficiency was obtained by replacing K2HPO4 of the medium with equi-molar concentration of KCl. For chemoheterotrophic growth condition, cultures supplemented with glucose and acetate at different concentrations were incubated under complete darkness following Sharma and Mallick (2005a). 2.2. Growth and dry weight measurement
was washed with acetone and was dissolved again in hot chloroform. 2.4. Assay of poly-b-hydroxybutyrate (PHB) PHB was quantified following the propanolysis method of Riis and Mai (1988) with the help of gas chromatography (Clarus 500, Perkin Elmer) in split mode (1:50, v/v), equipped with Elite-1 dimethylpolysiloxane capillary column (30 m · 0.25 mm · 0.25 lm) and flame ionization detector. Benzoic acid was used as the internal standard. 2.5. Experimental design A five-level-four-factor central composite rotary design (CCRD) obtained by using the software Design-Expert 6.0.10, Stat-Ease Inc. Minneapolis, USA was employed to find out the interactive effects of four variables, viz. concentrations of acetate, K2HPO4, and glucose, and duration of dark incubation on PHB production. Stationary phase cultures of N. muscorum were transferred to BG-11 medium with varying concentrations of K2HPO4, glucose and acetate as given in Table 1. Duration of dark incubation was imposed as per the experimental design. Central composite design at the given range of the above parameters in terms of coded and actual terms is presented in Table 2. 2.6. Statistical analysis The experimental data obtained from the design were analyzed by the response surface regression procedure using the following second-order polynomial equation: X X X Y i ¼ b0 þ bi xi þ bii x2i þ bij xi xj i
Extraction of PHAs was done following Yellore and Desia (1998) with certain modifications. A known amount of cyanobacterial cells was suspended in methanol at 4 C (overnight) for removal of pigments. The pellet so obtained after discarding the supernatant was dried at 60 C. The polymer was extracted in hot chloroform followed by precipitation with cold diethyl ether. The sample was then centrifuged at 11,000 · g for 20 min to get the pellet. The pellet
ij
where Yi was the predicted response, xixj were independent variables, b0 was the offset term, bi was the ith linear coefficient, bii was the ith quadratic coefficient and bij was ijth interaction coefficient. However, in this study, the independent variables were coded as A, B, C and D. Thus the second order polynomial equation could be presented as follows: Y ¼ b0 þ b1 A þ b2 B þ b3 C þ b4 D þ b11 A2 þ b22 B2 þ b33 C 2 þ b44 D2 þ b12 AB þ b13 AC þ b14 AD þ b23 BC þ b24 BD
Growth was measured in terms of chlorophyll a following Mackinney (1941). Cell dry weight was determined gravimetrically following Rai et al. (1991). 2.3. Extraction of poly-hydroxyalkanoates (PHAs)
ii
þ b34 CD
Table 1 Levels of factors used for optimization of nutritional factors for PHB production Variable
A B C D
Name
Acetate (% w/v) K2HPO4 (mg l1) Glucose (% w/v) Period of dark incubation (h)
Level 2 (a)
1
0
1
2 (+a)
0.05 10 0.05 42
0.10 0 0.10 84
0.15 10 0.15 126
0.20 20 0.20 168
0.25 30 0.25 210
L. Sharma et al. / Bioresource Technology 98 (2007) 987–993 Table 2 Central composite design of independent variables for optimization of nutritional factors Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Coded
Actual
A
B
C
D
1 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1 2 0 0 0 0 2 1 1 0 1 1 1 0 0
1 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1 0 0 2 0 0 0 1 1 2 1 1 1 0 0
1 1 1 0 0 1 1 1 0 2 1 1 1 1 0 1 0 0 0 0 2 0 1 1 0 1 1 1 0 0
1 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1 0 0 0 2 0 0 1 1 0 1 1 1 2 0
A 0.20 0.10 0.20 0.15 0.15 0.10 0.10 0.20 0.15 0.15 0.20 0.10 0.10 0.10 0.15 0.20 0.25 0.15 0.15 0.15 0.15 0.05 0.20 0.20 0.15 0.10 0.10 0.20 0.15 0.15
B 20 0 0 10 10 20 0 20 10 10 20 0 20 20 10 0 10 10 10 10 10 10 20 0 30 0 20 0 10 10
C 0.20 0.10 0.10 0.15 0.15 0.10 0.10 0.10 0.15 0.25 0.20 0.20 0.20 0.20 0.15 0.20 0.15 0.15 0.15 0.15 0.05 0.15 0.10 0.10 0.15 0.20 0.10 0.20 0.15 0.15
D 168 168 84 126 126 168 84 168 126 126 84 84 168 84 126 84 126 126 126 42 126 126 84 168 126 168 84 168 210 126
The statistical software package, Design-Expert 6.0.10 was used for regression analysis of the experimental data and also to plot the response surface graphs. Analysis of variance (ANOVA) was used to estimate the statistical parameters. The second order polynomial equation was employed to fit the experimental data. The significance of the model equation and model terms were evaluated by F-test. The quality of fit of the polynomial model equation was expressed by the coefficient of determination (R2), adjusted R2 and ‘‘adequate precision’’. The fitted polynomial equation was expressed as three-dimensional surface plots to visualize the relationship between the responses and the experimental levels of each factor used in the design. To optimize the level of each factor for maximum response ‘‘Point Optimization’’ process was employed. The combination of different optimized parameters, which gave maximum response, i.e. maximum PHB yield was tested experimentally to see the validity of the model. 3. Results 3.1. Fitting the model The design matrix in actual terms and the experimental results of PHB accumulation in N. muscorum by the central
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composite rotary design with 6 central points, 16 cubic points and 8 axial points are presented in Table 3. Different combinations of sodium acetate (0.1–0.2%, w/v), K2HPO4 (0–20 mg l1), glucose (0.1–0.2%, w/v) and dark incubation period (84–168 h) yielded PHB as low as 16.23 and as high as 47.23% (dcw). The predicted values, calculated by using the model were in the range of 18.42–48.03% (dcw, Table 3). The regression analysis of the experimental design demonstrated that the linear model terms (A, B and C), quadratic model terms (A2, B2, C2 and D2) and interactive model terms (AB, AC, AD, BD and CD) were significant (P < 0.05, data not shown). However, the linear model term D and the interactive model term BC were found to be insignificant (P > 0.05). Applying multiple regression analysis, the results were fitted to a second-order polynomial equation. Thus the mathematical regression model for PHB production fitted in terms of coded factors was obtained as follows: YðPHBÞ ¼ þ42:42 þ 5:20A 5:98B þ 1:39C þ 0:77D 3:40A2 2:64B2 1:87C2 1:93D2 1:15AB þ 1:16AC þ 1:56AD þ 1:34BD 2:37CD:
Table 3 Central composite design matrix with measured and predicted responses of PHB yield Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Factors
Response (Y)
A
B
C
D
Predicted
Actual
0.20 0.10 0.20 0.15 0.15 0.10 0.10 0.20 0.15 0.15 0.20 0.10 0.10 0.10 0.15 0.20 0.25 0.15 0.15 0.15 0.15 0.05 0.20 0.20 0.15 0.10 0.10 0.20 0.15 0.15
20 0 0 10 10 20 0 20 10 10 20 0 20 20 10 0 10 10 10 10 10 10 20 0 30 0 20 0 10 10
0.20 0.10 0.10 0.15 0.15 0.10 0.10 0.10 0.15 0.25 0.20 0.20 0.20 0.20 0.15 0.20 0.15 0.15 0.15 0.15 0.05 0.15 0.10 0.10 0.15 0.20 0.10 0.20 0.15 0.15
168 168 84 126 126 168 84 168 126 126 84 84 168 84 126 84 126 126 126 42 126 126 84 168 126 168 84 168 210 126
35.32 33.02 39.81 42.42 42.42 24.45 32.55 33.34 42.42 37.75 32.70 36.14 21.79 25.41 42.42 48.03 39.21 42.42 43.83 33.14 32.18 18.42 21.25 46.52 19.73 27.14 18.60 45.28 36.23 42.42
33.61 36.64 42.44 43.34 43.23 23.28 32.17 35.19 41.30 38.11 32.25 37.44 22.43 26.38 42.21 47.23 40.20 44.21 42.44 31.89 30.62 16.23 20.20 43.61 20.22 26.22 20.17 46.93 36.34 40.23
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41.3
PHB (% dcw)
PHB (% dcw)
48.7 48.7 41.3 33.8 26.4
33.8 26.4
0.20 20 13
0.17 7
B: K2HPO4 -1 (mg l )
0
0.17
0.13 C: glucose 0.10 (%)
0.13 A: sodium acetate (%)
0.10
0.20 0.17
0.20
0.13 A: sodium acetate (%)
(B)
(A)
48.7
PHB (% dcw)
48.7
PHB (% dcw)
0.10
41.3 33.8 26.4
168
41.3 33.8 26.4
168
0.20 140
0.17
112 D: dark incubation 84 Period ( h)
0.10
20 140
13 112
0.13 A: sodium acetate (%)
D: dark incubation period (h)
(C)
7 84
0
B: K2HPO4 -1 (mg l )
(D)
PHB (% dcw)
48.7 41.3 33.8 26.4
168
0.20 140
0.17 112
D: dark incubation Period (h)
0.13 84
0.10
C: glucose (%)
(E) Fig. 1. 3D response surface: Interactive effects of (A) varied sodium acetate and K2HPO4 concentrations at 0.15% glucose and 126 h dark incubation period, (B) varied glucose and sodium acetate concentrations at 10 mg l1K2HPO4 and dark incubation period (126 h), (C) varied sodium acetate and dark incubation period at 0.15% glucose and 10 mg l1 K2HPO4, (D) varied K2HPO4 and dark incubation period at 0.15% each of glucose and sodium acetate, and (E) varied dark incubation period and glucose at 10 mg l1 K2HPO4 and 0.15% sodium acetate.
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Analysis of variance (ANOVA) explained the significance of the model for PHB (F-value: 35.61, data not shown). Lack of fit was insignificant. R2 was close to unity (0.9666, data not shown). 3.2. Optimization of process PHB yield for different levels of the variables was predicted from the respective contour plots (Fig. 1(A)–(E)). Each contour curve represents an infinite number of combinations of two test variables with the other two maintained at their respective zero levels. Elliptical nature of the contour in 3D-response surface graphs (Fig. 1(A)– (E)) depicted the mutual interactions of all the variables. Fig. 1(A) explains the interaction of sodium acetate with K2HPO4, where with increasing sodium acetate concentration and decreasing K2HPO4 level, PHB production achieved a quadratic gain. Therefore, a negative effect of interaction of these variables was assumed, which could be seen from the negative sign of the coefficient of AB model term in the equation. Similarly, Fig. 1(B) explains the interaction of glucose and sodium acetate at zero level of K2HPO4 and dark incubation period. In this graph, PHB concentration increased with increase in both the variables above the zero level till certain point, but there was a sharp convergence of the curve near the boundary, explaining that addition of glucose and acetate above certain limit would not contribute for increasing PHB production further. Interaction of sodium acetate and dark incubation period was significant and positive as visualized from Fig. 1(C). However, interaction of dark incubation period and K2HPO4 followed quite a different trend (Fig. 1(D)). The convergence of the curve toward the center point of dark incubation period demonstrated that there would be no further rise in PHB yield by increasing dark incubation period above the zero level, i.e. above 126 h. The response surface graph drawn for glucose and dark incubation period at zero level of the other two variables showed negative impact (Fig. 1(E)). However, the interactive model term BC, i.e. glucose and K2HPO4 did not show significant effect on PHB accumulation, which was reflected from flat response surface and more parallel contour lines (data not shown). After knowing the possible direction for maximizing PHB production, optimization was done using ‘‘Point Optimization’’ technique. A maximum polymer yield of 47.4% (dcw) was predicted at 0.16% glucose, 0.17% acetate, 5 mg l1 K2HPO4 and a dark incubation period of 95 h. 3.3. Verification of the model Experiments were performed in triplicate using the optimized conditions to verify the model. It could be visualized from Table 4 that the predicted (47.4% dcw) and experimental (45.6% dcw) PHB content after optimization were well in agreement. Though there was not significant rise
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Table 4 PHB yield before and after optimization of nutritional parameters Variable
Beforea
After
PHB yield (% dcw) Beforea
Sodium acetate (% w/v) K2HPO4 (mg l1) Glucose (% w/v) Dark incubation period (h) a
0.4
0.17
40 0.4 168
5.0 0.16 95
41.6
After Predicted
Experimental
47.4
45.6
Sharma and Mallick (2005a).
in PHB level after optimization, the input was however, greatly reduced. The PHB content before optimization was 41.6% (dcw) at 0.4% acetate, 0.4% glucose and 40 mg l1 K2HPO4, and dark incubation period of 168 h. After optimization PHB yield was raised up to 45.6% (dcw) at 0.17% acetate, 0.16% glucose, 5 mg l1 K2HPO4 and 95 h of dark incubation period. 4. Discussion In a previous study with N. muscorum (Sharma and Mallick, 2005a,b), one factor optimization or at some instances two factors were considered, and the appropriate range of critical factor(s) contributing to the increased production of PHB was selected. The significant rise in PHB pool of N. muscorum under mixotrophic, chemoheterotrophic, gas-exchange limited conditions, and also under limitations of phosphate and nitrogen as a function of incubation period pointed towards the optimization of these factors for maximum response. Amongst these critical factors, nitrogen and gas-exchange limitations were excluded, since nitrogen limitation in this N2-fixing organism was achieved by eliminating molybdenum from the culture medium, which was used at micro level only and therefore, was difficult for assigning the different levels to study the effect on responses. Besides, the impurities present in various salts (used in preparation of the medium) cannot be avoided which may contain traces of molybdenum, as use of high-grade salts is not feasible commercially. Gasexchange limitation was also excluded owing to the slow growth rate of the organism and the longer incubation period for PHB accumulation. Therefore, nutritional parameters, viz. concentrations of glucose, acetate, phosphate and duration of dark incubation (Table 1) were considered for RSM study to maximize the PHB production in N. muscorum. The rotatable central composite design was used to get the optimum response (Tables 2 and 3). In this study, the regression equation is given using coded factors. The results showed significant effects for all the model terms except D and BC. The results were fitted to a second order polynomial model by removing the insignificant model term BC. Though insignificant, variable D was not
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neglected while fitting the model due to its interaction with other variables. According to the second order polynomial equation, the linear coefficient A (acetate), C (glucose) and D (dark incubation period) showed positive effects on PHB yield, whereas B (K2HPO4) exhibited negative impact. The model so obtained for PHB production was adequate enough as depicted from the high F-value (35.61), insignificant lack of fit (Probability > F = 0.1256) and R2 close to unity (0.9666). This indicates that 96.66% of variability in the response could be explained by this model. The contour plots in 3D response depicted the variation in PHB yield, as a function of interaction of variables. From Fig. 1(A)–(E), it is concluded that increasing sodium acetate and glucose concentrations and decreasing K2HPO4 concentration resulted into rise in PHB content as a function of time within the surface. The optimum conditions for maximum PHB yield were obtained as follows: 0.17% (w/v) sodium acetate, 5 mg l1 K2HPO4, 0.16% (w/ v) glucose and 95 h of dark incubation period for the predicted PHB yield of 47.4% (dcw) (Table 4). The experimental value of 45.6% (dcw) (Table 4) is well in agreement with that of the predicted one. Before optimization, a value 41.6% PHB was obtained at higher concentrations of glucose and acetate (0.4%, each) and 40 mg l1 of K2HPO4 at 168 h of dark incubation period (Sharma and Mallick, 2005a). The enhanced PHB production in N. muscorum under phosphate limitation is supported with the scientific basis that PHB biosynthesis is expected to increase under phosphate limitation, when reducing power may be in excess, because ATP production is known to decrease markedly with the onset of phosphate limitation, while the reduction of NADP through non-cyclic photosynthetic electron flow is not inhibited (Bottomley and Stewart, 1976; Konopka and Schnur, 1981). The optimum concentration of phosphate was 5 mg l1, rather than complete P-deficiency agrees with the findings of Nishioka et al. (2001) and Panda et al. (2005), where a minimal level of internal phosphate is essential for PHB accumulation. The stimulatory effect of acetate on PHB accumulation could be due to the direct utilization of acetate for the synthesis of the polyester by means of the usual pathway operating in prokaryotes (Dawes, 1992). Glucose utilization in cyanobacteria however, occurs via pentose phosphate pathway. Thus, the positive effect of glucose on PHB production could be attributable to the increased supply of the reduced cofactor, i.e. NADPH (Lee et al., 1995). Enhancement of PHB accumulation during dark incubation could possibly be due to the degradation of glycogen to supply acetyl-CoA (substrate for PHB biosynthesis) as reported for Gloeothece PCC 6909 and Synechocystis sp. PCC 6803 (Stal, 1992; Wu et al., 2001). In conclusion, the response surface methodology was effectively used for the optimization of the process parameters for PHB production in N. muscorum and chemoheterotrophic conditions with glucose and acetate with simultaneous limitation of phosphate were the desirable
conditions for enhanced PHB accumulation in N. muscorum. Acknowledgement Financial support from Department of Biotechnology, Ministry of Science and Technology, India is thankfully acknowledged. References Bottomley, P.J., Stewart, W.D.P., 1976. ATP pools and transients in the blue-green alga, Anabaena cylindrica. Arch. Microbiol. 108, 249–258. Byrom, D., 1994. Polyhydroxyalkanoates. In: Mobley, D.P. (Ed.), Plastics from Microbes: Microbial Synthesis of Polymers and Polymer Precursors. Munich, Hanser, pp. 5–33. Dawes, E.A., 1992. Storage polymers in prokaryotes. In: Mohan, S., Dow, C., Coles, J.A. (Eds.), Prokaryotic Structure and Function: A New Perspective. Cambridge University Press, Cambridge, pp. 88–122. Khanna, S., Srivastava, A.K., 2005. Statistical media optimization studies for growth and PHB production by Ralstonia eutropha. Process Biochem. 40, 2173–2182. Konopka, A., Schnur, M., 1981. Biochemical composition and photosynthetic carbon metabolism of nutrient limited cultures of Merismopedia tenuissima (Cyanophyceae). J. Phycol. 17, 118–122. Lakshman, K., Rastogi, N.K., Shamala, T.R., 2004. Simultaneous and comparative assessment of parent and mutant strain of Rhizobium meliloti for nutrient limitation and enhanced polyhydroxyalkanoate (PHA) production using optimization studies. Process Biochem. 39, 1977–1983. Lama, L., Nicolaus, B., Calandrelli, V., Maria, M.C., Romano, I., Gambacorta, A., 1996. Effect of growth conditions on endo- and exopolymer biosynthesis in Anabaena cylindrica 10C. Phytochemistry 42, 655–659. Lee, I.Y., Kim, M.K., Chang, H.N., Park, Y.H., 1995. Regulation of polyb-hydroxybutyrate biosynthesis by nicotinamide nucleotides in Alcaligenes eutrophus. FEMS Microbiol. Lett. 131, 35–39. Liebergesell, M., Sonomoto, K., Madkour, M., Mayer, F., Steinbu¨chel, A., 1994. Purification and characterization of the poly (hydroxyalkanoic acid) synthase from Chromatium vinosum and localization of the enzyme at the surface of poly (hydroxyalkanoic acid) granules. Eur. J. Biochem. 226, 71–80. Mackinney, G., 1941. Absorption of light by chlorophyll solution. J. Biol. Chem. 140, 315–322. Miyake, M., Erata, M., Asada, Y., 1996. A thermophilic cyanobacterium, Synechococcus sp. MA19, capable of accumulating poly-b-hydroxybutyrate. J. Ferment. Bioengg. 82, 512–514. Nishioka, M., Nakai, K., Miyake, M., Asada, Y., Taya, M., 2001. Production of poly-b-hydroxybutyrate by thermophilic cyanobacterium, Synechococcus sp. MA19, under phosphate limitation. Biotechnol. Lett. 23, 1095–1099. Panda, B., Sharma, L., Mallick, N., 2005. Poly-b-hydroxybutyrate accumulation in Nostoc muscorum and Spirulina platensis under phosphate limitation. J. Plant Physiol. 162, 1376–1379. Panda, B., Jain, P., Sharma, L., Mallick, N., 2006. Optimization of cultural and nutritional conditions for accumulation of poly-bhydroxybutyrate in Synechocystis sp. PCC 6803. Biores. Technol. 97, 1296–1301. Rai, L.C., Mallick, N., Singh, J.B., Kumar, H.D., 1991. Physiological and biochemical characteristics of a copper tolerant and a wild type strain of Anabaena doliolum under copper stress. J. Plant Physiol. 138, 68–74. Riis, V., Mai, W., 1988. Gas chromatographic determination of poly-bhydroxybutyric acid in microbial biomass after hydrochloric acid propanolysis. J. Chromatogr. 445, 285–289.
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