JIRI HANIKA1,2



|M. SHARIFZADEH BAEI1 | | |GROWTH KINETIC PARAMETERS AND BIOSYNTHESIS OF POLYHYDROXYBUTYRATE IN Cupriavidus necator DSMZ|

|G.D. NAJAFPOUR2 | | |545 ON SELECTED SUBSTRATES |

|H. YOUNESI3 | | |A kinetic model for Cupriavidus necator in batch culture using glucose, fructose and molasses|

|F. TABANDEH3 | | |as carbon sources was obtained. The experimental data was also fitted with the modified |

|H. ISSAZADEH2 | | |logistic equation that can provide adequate description for PHB synthesized by C. necator. |

|M. KHODABANDEH4 | | |The Lineweaver-Burk plot defined biokinetic coefficients which were described by a simplified|

|1Islamic Azad University, Ayatollah Amoli | | |Monod’s rate model. The specific growth rates, μmax and the Monod constants, Ks, for various |

|Branch, Department of Chemical | | |substrates such as glucose, fructose and molasses were 0.18, 1.25, 0.42 h-1 and 107.53, |

|Engineering, Amol, Iran | | |30.342 and 188.16 g/l, respectively. The kinetic constants were evaluated on the basis of |

|2Faculty of chemical engineering, | | |non-linear regression solved using MATLAB software. Good agreement was found between the |

|Noshirvani University of Technology, | | |experimental and the predicted values, which indicated that the model with differential |

|Babol, Iran | | |equations would describe fermentation process for the PHB formation. |

|3Department of Environmental Science, | | |Key words: PHB; Cupriavidus necator; logistic model; Monod rate model; biopolymer. |

|Faculty of Natural Resources and Marine | | | |

|Sciences, Tarbiat Modares University, | | | |

|Noor, Iran | | | |

|4Biotechnology Department, National | | | |

|Institute of Genetic Industrial | | | |

|Engineering and Biotechnology (NIGEB), | | | |

|Tehran, Iran | | | |

|scientific paper | | | |

|UDC 66.09/.66.098 | | | |

|DOI 10.2298/CICEQ100216043B | | | |

*Polyhydroxybutyrate (PHB) is a biopolymer that is used as a biodegradable thermoplastic material [1]. PHB is also used for medical purposes because of its biocompatibility [2]. The viability of large scale production of PHB via microbial process is dependent on the development of a low cost process that produces biodegradable plastics with properties similar or superior to petrochemical plastics [3]. Commercial production of PHB has been using relatively cheap substrates such as methanol [4], beet molasses [5], ethanol [6], starch and whey [7], sugarcane molasses [8] as a sole carbon source. Media enriched with nitrogen, such as casein hydrolysate, yeast extract, typtone, corn steep liquor and collagen hydrolysate have been used in PHB production using either Cupriavidus necator or recombinant Escherichia coli strains [9]. However, unrefined carbon sources such as corn syrup, sugarcane molasses, beet molasses, or malt extract are utilized for PHB formation. It was reported that, PHB yield with various untreated carbon sources were even better than the refined carbohydrate sources [9]. Beet molasses and malt extract promoted high polymer production due to presence of a growth stimulants in the cultured media [5]. PHB production by number of wild type bacterial strains occurs under nutrient depletion conditions [10]. In PHB production phase, the cell growth is limited due to depletion of essential nutrients such as carbon, nitrogen and phosphorus sources. Such depletion in the presence of excess amount of carbon source triggers the metabolic shift from growth to PHB production modes. It was also reported that C. necator, which is known as Wautersia eutropha, Ralstonia eutropha and Alcaligenes eutrophus are potential organisms for the optimal production of PHB, that is a homopolymer which is accumulated inside the cells under nitrogen limitation [10]. Azotobacter beijerinckii produces appreciable amount of PHB, the biopolymer concentration increases under oxygen limitation. The organism may tolerate nitrogen and phosphorus limitation [11]. A wide variety of PHA copolymers are synthesized by number of microorganisms via fermentation processes while utilizing various carbon sources [12–14]. PHB production is a complex process; where the final quality and quantity of the product yield depends on strains, metabolic pathway, process fermentation parameters, PHB production phase (growth and stationary phases), carbon sources and nutrient depletion conditions which are required for PHB synthesis.

Useful kinetic model for biopolymer synthesis has been implemented including biomass (cell density), product concentration, single substrate utilizetion and limited nutrient sources [15,16]. In a biopolymer process, the kinetic model is substantially capable to predict product formation. Mathematical models facilitate data analysis and provide a strategy for solving problems encountered in fermentation processes. Information on fermentation process kinetics is potentially valuable for the improvement of process performances. Kinetic model has the potential to approximate and allows us to predict if the cell growth may contain biopolymer. One of the most widely used models to describe cell growth, known as the unstructured model, describes the single component as the sole source of energy for prediction of cell growth. It is common to assume the ideal case that is single substrate, and the rate is defined by the Monod growth rate model [17,18]. Similarly, rate models are successfully used to estimate kinetic parameters for growth expression in PHB production by W. eutropha, which is subsequently used in modeling the cell growth and biopolymer production [19,20]. In another investigation by Dhanasekar et al. [21], Monod, logistic and modified logistic models were successfully applied to describe the batch growth kinetics.

The Monod kinetic model used for PHBs production described by the following equation:

[pic] (1)

where ( is the specific growth rate (h-1), S is substrate concentration (g/l) and the terms KS and (m are defined as the Monod constant (g/l) and maximum specific growth rate, respectively. At the end of the lag phase, the growth of microorganisms is well adjusted to its new environment. Then the cells multiply rapidly. The most active part of the cell growth curve is the exponential (log) phase which is used for the determination of kinetic parameters. The log phase is a period of balanced growth, in which all components of a cell grow at the same rate [16]. Malthus model was also used for the cell growth behavior. The derivatives for biomass generation with respect to time, is related to specific growth rate which is defined as follows [16]:

[pic] (2)

where X is cell mass concentration (g/l) and t is time (h). Separation of variables and integrating Eq. (2) yields:

[pic] (3)

where X is biomass concentration with respect to time and X0 is the initial biomass concentration. The substrate and product inhibitory effect on cell growth has been investigated in the literature [18]. The cell growth rate was evaluated based on growth kinetics. Logistic equation was a suitable kinetic model for prediction of growth curve. The logistic equation is a substrate independent rate model, which is used for the determination of inhibition effect on biomass growth. It was theoretically proposed that the inhibition factor was proportional to microbial biomass growth [16]. The specific growth rate is predicted by the logistic model presented by Eq. (4):

[pic] (4)

where Xm is the maximum cell dry weight concentration (g/l). By substitution of Eq. (4) into Eq. (2) and performing integration, the following equation for the cell concentration was obtained [22]:

[pic] (5)

Several growth-related kinetic models such as Contois, Westerhoff, Herbert, Moser and Tessier models, simulate cell growth for PHB production using glucose as sole source of energy are summarized in Table 1. The Michaelis constant in Contois model is proportional to cell concentration; this leads to specific growth rate which is inversely proportional to cell concentration. Westerhoff has proposed a linear model for the cell specific growth rate. The Monod equation was also modified as the maintenance term was incorporated in the Herbert model [23]. The Monod rate was modified for substrate to the second power and the model is known as the Moser rate equation [17]. Finally, the Tessier model represents exponential substrate consumption [17].

The above equation was used to predict the cell growth in batch experiments. In this research, inoculation volumes were kept constant for batch experiments. The logistic model was a good approximation of the growth curve. Matlab (v7.1) computer software was used to define logistic growth kinetic parameters.

The main purpose of present research was to investigate the effect of various carbon sources such as glucose, fructose and molasses on biopolymer production, and in addition, to find a suitable cheap carbon source for PHB production. Kinetic parameters for the cell growth and PHB production by C. necator were determined.

|Table 1. Kinetic models applied for PHB production using glucose as carbon source |

|Models |Non-linear models |Linear Models |Parameters |R2 |

|Monod |[pic] |[pic] |(max = 0.17 h-1 |0.976 |

| | | |Ks = 86 g l-1 | |

|Contois |[pic] |[pic] |(max = 0.17 h-1 |0.972 |

| | | |Ks = 93 g l-1 | |

|Westerhoff |[pic] |[pic] |a = 0.015 h-1 |0.971 |

| | | |b = 0.146 h-1 | |

|Herbert |[pic] |[pic] |(max = 0.14 h-1 |0.889 |

| | | |Ks = 34 g l-1 | |

| | | |m = -0.36 h-1 | |

|Moser (n=2) |[pic] |[pic] |(max = 0.1 h-1 |0.936 |

| | | |Ks = 54 g2 l-2 | |

|Tessier |[pic] |[pic] |(max = 0.12 h-1 |0.939 |

| | | |Ks = 28 g l-1 | |

| | | | | |

Materials and Methods

MICROORGANISM. THE MICROORGANISM USED IN THE PRESENT STUDY WAS CUPRIAVIDUS NECATOR DSMZ 545 (DEUTSCHE SAMMLUNG VON MIKROORGANISMEN UND ZELLKULTUREN) FOR CULTURE PROPAGATION. THE STOCK CULTURE WAS STORED AND MAINTAINED ON LURIA AGAR SLANTS AT 4 (C. THE ORGANISM WAS SUB-CULTURED EVERY 15 DAYS TO MAINTAIN ITS VIABILITY.

Media. Glucose and fructose were used as standard substrates and molasses was locally obtained from sugarcane molasses Industry (Sharivan, Iran). Molasses was pretreated with sulfuric acid solution (0.75 mass%, pH 1.1) and heat treated at 100, 115 and 130 (C for 15 min. The pretreatment of molasses was carried out to enhance sugar content and reduce any possible existing dimmers of invert sugar to single monomer. The solution was neutralized with 5 M NaOH solutions and the pH was adjusted to 7.0. Then, the neutralized solution was filtered, autoclaved at 121 °C for 15 min. Other sets of experiments with 10 g/l acetate as supplement to molasses were used. The mineral solution for batch culture experiments design was prepared by mixing the following chemicals: Na2HPO4, 3.57 g/l; KH2PO4, 1.5 g/l; (NH4)2SO4, 1.35 g/l. Trace element contents of the solution were MgSO4, 2.2 g; FeSO4, 0.1 g; MnSO4, 0.1 g; K2SO4, 2.2 g; H3BO3, 0.02 g; CuSO4, 0.08 g added to 1 liter of distilled water [16].

Experimental conditions. Stock culture in slants of C. necator was incubated at 30 °C for 24 h. The resultant cultures were transferred into 500 ml flasks containing 100 ml medium. The flasks were incubated at 30 °C and agitated at 250 rpm for 96 h. The inoculum size was 5% of the medium. For the above experimental conditions the dry cell weight (DCW) and PHBs accumulation inside the cells were investigated.

Cell dry weight. The cell concentration in the cultured media was determined by the cell optical density at wavelength of 620 nm using a spectrophotometer (UNICO2100, USA) with distilled water for suitable dilution rate. The cell dry weight was also measured based on a standard calibration curve. The standard curve was experimentally defined by filtration of exact volume of the broth containing C. necator. The cell optical density is defined as light absorbance of the culture as a function of cell dry weight was based on pure culture of C. necator. The cell dry weight measurements were quite accurate (mg cells l-1). The mean value of triplicate weight measurements had a standard deviation of less 3%.

Carbohydrate concentration. The supernatant obtained from centrifuged solution was used for residual nutrient analysis including total carbohydrates according to the method developed by reduced sugar analysis using 3,5-dinitrosalicilic acid (DNS) method [24].

Biopolymer analysis. For PHB quantification, 5 ml of culture broth was centrifuged at 3600 rpm for 20 min. A 2 ml solution of chloroform and 2 ml of acidified methanol (3% sulfuric acid) were added to the cell pellet in a vial with Teflon screw cap and heated at 100 (C for 3.5 h. The developed extraction method was based on experimental method developed by Braunegg et al. [25].

Gas chromatography (GC) was performed using a gas chromatograph (Philips PU4400, US) equipped with a flame ionization detector (FID) and data acquisition system with computer software (Clarity 4.2, Data Apex, Czech Republic). The GC was used for the methyl ester of 3-hydroxybutyric acid (3HB) analysis. The GC was equipped with capillary column (BP20 SGE, Australia) of 0.33 mm internal diameter and 25 m length. The column temperature was initially maintained at 80 (C for 4 min, followed by the temperature programming at a rate of 8 (C/min till it reached to 160 (C, maintained for 3 min and then at a rate of 30 (C/min increased to 200 (C. The detector and injector temperatures were 280 and 250 (C, respectively. The carrier gas used was helium with a flow rate of 1.5 ml/

/min. Hydrogen and air flow rates were 30 and 300 ml/min, respectively. The injection volume size was 1 (l of the prepared samples.

Results and Discussion

|TABLE 2. KINETIC PARAMETERS FOR THE PHB PRODUCTION WITH VARIOUS CARBON SOURCES |

|CARBON SOURCE |GLUCOSE |FRUCTOSE |MOLASSES |

|SUGAR CONSUMED, % |45 |57 |55 |

|MAXIMUM BIOMASS YIELD PER G SUBSTRATE CONSUMED, G/G |0.53 |0.5 |0.55 |

|MAXIMUM PRODUCT YIELD, G/G |0.18 |0.27 |0.06 |

|MONOD CONSTANT, KS / G L–1 |86 |30 |108 |

|MONOD, µMAX / H-1 |0.17 |0.125 |0.42 |

|LOGISTIC, µMAX / H-1 |0.11 |0.12 |0.32 |

|[pic] |

|Figure 1. The concentration profiles of cell growth, consumption of glucose and biopolymer (PHB) production |

|at 30 °C and agitation rate of 250 rpm. |

PHB production was carried out in batch fermentation by C. necator. Glucose, fructose and molasses were employed to provide the desire concentrations of substrate in the fermentation media. Growth kinetic data for C. necator was obtained. The kinetic parameters for the PHB production with various carbon sources are summarized in Table 2.

Figure 1 shows glucose consumption and PHB production and CDW with respect to incubation time, for maximum duration of 96 hours. At 30 °C, agitation rate of 250 rpm and incubation period of 48 h, maximum PHB concentration of 3.3 g/l was obtained.

Fructose as a carbon source was experimented for PHB production. At stated above media composition and mentioned conditions, with incubation time of 72 h, maximum PHB concentration of 5.8 g/l was obtained (Figure 2).

Figure 3 depicts PHB production with molasses as carbon source. At the mentioned media conditions and incubation time of 72 h, maximum PHB concentration of 1.3 g/l was obtained. At 30 °C and agitation rate of 250 rpm, among various carbon sources, fructose and molasses produces the highest and lowest concentrations of PHB, respectively.

|[pic] |

|Figure 2. The concentration profiles of cell growth, consumption of fructose and biopolymer (PHB) production |

|at 30 °C and agitation rate of 250 rpm. |

|[pic] |

|Figure 3. The concentration profiles of cell growth, consumption of molasses and biopolymer (PHB) production |

|at 30 °C and agitation rate of 250 rpm. |

Figure 4 shows that the Malthus kinetic model was well fitted with the experimental data. The fitted line for fructose and molasses were very close to each other but the line for glucose was slightly separated. This graph corresponds to Eq. (3) which represents the variation of the logarithm of cell concentration with respect to incubation time.

The Lineweaver-Burk plot, double reciprocal plot for the Monod kinetic model is shown in Figure 5. The model was used based on experimental data obtained for substrate consumption with respect to incubation time. There was good agreement with experimental data. The rate data for fructose was more promising while maximum PHB production rate (0.37 g l–1 h–1) was obtained.

The growth pattern for the microorganism was exactly followed by the Logistic model, as the fitted data are presented in Figure 6. Maximum cell concentration was about 11 g/l for fructose incubated at 96 h.

[pic]

Figure 4. Malthus kinetic model fitted with experimental data.

[pic]

Figure 5. Lineweaver-Burk plot fitted with experimental data.

[pic]

Figure 6. Logistic kinetic model fitted with experimental data.

Figure 7 shows the experimental data fitted with several non-linear rate models. The kinetic parameters obtained for all models are summarized in Table 1. The maximum specific growth rate was devoted to Monod and Contoise models.

Conclusion

|[pic] |

|Figure 7. Comparison of specific growth rates obtained from various models with linear and non-linear regressions. |

Several kinetic models for predicting cell growth were investigated. Among the models and substrate utilized by C. necator, the best model fits well (R2 =

= 0.96) with glucose utilization by the Logistic equation to predict biomass growth. Besides that, any inhibition may be predicted by the same model. C. necator showed high growth rate in fructose-based medium as compared to the media contained glucose or molasses. In the medium containing fructose as a carbon source, the maximum specific growth rate was projected by the Monod kinetic model. The PHB yield was 0.27g PHB/g of Fructose. As molasses was the carbon source, maximum specific growth rate was 0.42 h-1. It was concluded that the maximum biomass yield was obtained with molasses as a cheap co-product of sugar industry; moreover it may facilitate economically feasible production of PHB.

Acknowledgement

The authors gratefully acknowledge the research and development committee of Noushirvani University of Technology, for the support and facilities provided in Biotechnology research lab.

Nomenclature

Symbol

S – Substrate concentration (g l−1)

S0 – Initial substrate concentration (g l−1)

t – Fermentation time (h)

X – Cell concentration (g l−1)

Xm – Maximum cell concentration (g l−1)

X0 – Initial cell concentration (g l−1)

KS – Monod constant (gl-1)

YX/S – Yield factor for cells on carbon substrate (g cells (g substrate)−1)

YP/S – Yield factor for product on carbon substrate (g PHB (g substrate)−1)

Greek symbol

(m – Maximum specific growth rate (h−1)

( – Specific growth rate (h−1)

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|M. SHARIFZADEH BAEI1 | | |Kinetički parametri rasta C. necator DSMZ 545 i biosinteze polihidroksibutirata na izabranim |

|G.D. NAJAFPOUR2 | | |supstratima |

|H. YOUNESI3 | | |U radu je razvijen kinetički model rasta Cupriavidus necator u šaržnoj kulturi na glukozi, |

|F. TABANDEH3 | | |fruktozi i melasi kao izvorima ugljenika. Eksperimentalni podaci su, takođe, fitovani sa |

|H. ISSAZADEH2 | | |modifikofanom logističkom jednačinom koja može adekvatno opisati biosintezu PHB pomoću C. |

|M. KHODABANDEH4 | | |necator. Kinetički koeficijenti uprošćenog Monod-ovog modela određeni pomoću |

|1Islamic Azad University, Ayatollah Amoli | | |Lineweaver-Burk-ovog grafika. Za podloge sa glukozom, fruktozom i melasom određene su sledeće|

|Branch, Department of Chemical | | |vrednosti specifične brzine rasta, redom: 0,18, 1,25 i 0,42 h–1, dok su odgovarajuće |

|Engineering, Amol, Iran | | |vrednosti Monod-ove konstante: 107,53, 30,34, 188,16 g/l. Vrednosti kinetičkih konstanti su |

|2Faculty of chemical engineering, | | |izračunate pomoću metode nelinearne regresije koristeći program MATLAB. Dobro slaganje između|

|Noshirvani University of Technology, | | |eksperimentalnih i izračunatih vrednosti ukazuje da model sa diferencijalnim jednačinama |

|Babol, Iran | | |dobro opisuje biosintezu PHB. |

|3Department of Environmental Science, | | |Ključne reči: PHB; Cupriavidus necator; logistički model; Monod-ov model; biopolimer. |

|Faculty of Natural Resources and Marine | | | |

|Sciences, Tarbiat Modares University, | | | |

|Noor, Iran | | | |

|4Biotechnology Department, National | | | |

|Institute of Genetic Industrial | | | |

|Engineering and Biotechnology (NIGEB), | | | |

|Tehran, Iran | | | |

|Naučni rad | | | |

26]

*Correspondening author: G.D. Najafpour, Faculty of chemical engineering, Noshirvani University of Technology, Babol, Iran.

E-mail: najafpour@nit.ac.ir; najafpour8@

Paper received: 16 February, 2010

Paper revised: 26 June, 2010

Paper accepted: 26 July, 2010

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