Optimization Of A Amylase Activity Biology Essay

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A novel lyophilization protocol has been explored by incorporating tungsten halogen irradiation in the freeze-dryer for freeze-drying of Bacillus subtilis MTCC 2396. The effects of operating process parameters viz. freeze-drying temperature (), freeze-drying time ( ) and initial weight of the sample ( ) on the final moisture content and enzyme activity have been evaluated and optimized through response surface methodology. The maximum reduction in moisture content 96.07% and minimum reduction in enzyme activity 1.02% corresponded to , and of 42.5â-¦C, 4h and 5g respectively. Enzyme activity with specific reference to α-amylase and final moisture content of optimally freeze-dried bacterial strain appears to be acceptable from the perspective of bio-preservation. The retention of bioremedial activity of the optimally freeze-dried bacterial strain with respect to removal of mercuric ion from mercury laden waste water was also demonstrated.

Thus the present study demonstrates significant intensification in freeze-drying methods which can advantageously be applied in commercial units for production of lyophilized bacterial strains with special reference to Bacillus subtilis MTCC 2396.

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Being a member of the genus Bacillus, Bacillus subtilis has the ability to form a tough, protective endospore, allowing the organism to tolerate extreme environmental conditions. The particular strain Bacillus subtilis MTCC 2396 is a hyperproducer of α-amylase- an important enzyme involved in starch degradation. Amylases- both α and β, are used in food, textiles, paper, brewing and distilling industries. Since, Bacillus subtilis is a hyperproducer of α-amylase it may serve as a potential source for the commercial production of the enzyme through microbial route [1]. Amylases are used in the textile and paper industries, in starch liquefaction, as a food additive and in sugar production [2]. Bacillus subtilis has been recognized as an oral probiotics- health promoting microorganisms which are recently been used as food additive and therapeutic supplement that enhance prophylaxis and digestion [3]. Bacillus subtilis MTCC 2396 are also characterized with the capability of removal of mercuric ions from waste water. Whatever may be the field of application of the microorganism, it should always be preserved in lyophilized form for its large scale, commercial utilization. Conventional lyophilization process involves severe conditions with respect to freezing temperature (-40oC or lower), dehydration temperature (15- 20oC) and pressure (200 mtorr) and a very long processing time (20 hours and more). The process conditions and the duration are, however, dependent on the type of microorganism under study. Decreasing of the severity of process parameters as well as the processing time are challenging tasks for the engineers to cut down the total energy cost of the overall process. It is apparent that new freeze drying technologies should be investigated using less thermo-sensitive microorganisms to explore the possibility of introducing more energy efficient lyophilization processes.

Freeze drying is one of the technologies most commonly used for the preservation and storage of biological samples [4]. It is suitable for production of concentrated bacterial cultures with the advantage that the dried material can be stored at ambient temperature. Different species display different degree of freeze-drying survival, with Gram negative bacteria showing lower survival than Gram positive bacteria. A work has been reported on optimisation of initial cell concentration that enhances freeze-drying tolerance of Pseudomonas chlororaphis [5]. Another research article demonstrated survival and preservation after freeze-drying process of thermoresistant acetic acid bacteria isolated from tropical products of Subsaharan Africa [6]. Freeze-drying of Lactobacillus gasseri and Lactobacillus delbrueckii has been reported in a literature. Optimization of the freeze-drying media and survival throughout storage of the freeze-dried bacterial strains has been studied which are having application as veterinarian probiotic [7]. Most of the literature reported a longer drying time required in conventional freeze-drying unit involving conductive heating systems. A very lengthy overall freeze-drying time of about 18h at -72â-¦C was reported for a Lactobacillus bulgaricus culture [8] for preservation. Although Bacillus subtilis is one of the promising microorganisms being used extensively in biotechnological industries for the production of enzymes like a and b amylase, for the fortification of food as a probiotic and can be used successfully for the removal of hazardous heavy metals like mercury etc., no systematic study has yet been reported on the optimization of its preservation through freeze drying method. As the said bacteria is Gram positive as well as a spore former, it is having a thick cell wall which gives its cell a mechanical strength and rigidity [9]. Thus, the cell can be subjected to a high temperature during vacuum drying phase. The present work thus attempts to reduce the time of lyophilization through application of thermal energy using different electromagnetic energy sources viz. tungsten halogen lamp. Under the present investigation, it has been attempted to optimize the process of preservation of the strain Bacillus subtilis MTCC 2396 by means of freeze-drying enzymatic through the maximization of moisture removal and retention of enzymatic activity with respect to α-amylase. The parametric conditions viz. temperature of the heat source, drying time and distance between heat source and sample corresponding to minimum moisture content and maximum enzyme activity of the freeze-dried bacteria has been evaluated through Response Surface Method (RSM) employing a three level-three factor central composite design maintaining viability of the cells intact.

Materials and Methods:

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2.1. Organism and Culture Condition:

The strain of Bacillus subtilis MTCC 2396 was procured from Microbial Type Culture Collection (MTCC), Chandigarh, India. The strain was grown in LB (Luria Bertani) broth containing Tryptone-2gm, Yeast extract-1gm, Sodium chloride-2gm dissolved in 200ml distilled water at 36â-¦ C for 18 h [10]. Overnight cultures with OD600 = 0.6 were inoculated in the said medium and grown at the same temperature for 24 h in an indigenous BOD Shaker at 150 rpm.

2.2. Preparation of sample for Freeze-drying:

The overnight grown culture of Bacillus subtilis MTCC2396 in the stationary phase of its growth was centrifuged at 10,000 rpm for 20 minutes. The supernatant was discarded and the pellet was dissolved in 2mL of lyoprotectant medium (12% sucrose and 10% glucose). A set of fifteen vials weighing 4g to 5g, according to the FCCD (Face centered composite design) table were prepared.

2.3. Pre-freezing

The sample with initial moisture content of 90.70% (wet basis) was taken in a glass vial and was frozen through conventional refrigeration by keeping it inside a deep freezer (Blue Star, India; model C8F320) maintained at -20 ± 0.1°C for a time span of 12 h to attain the desired temperature of -15 ± 1 °C [11].

2.4. Experimental set-up

The freeze-drying chamber (310x 320 x 310 mm3) was evacuated by a vacuum pump (150 dm3/min, and 5 x 10-3 mbar) through a low-temperature moisture trap. The pre-frozen bacterial sample that was being subjected to freeze-drying was weighed by a weighing balance (Citizen, CY 420, accuracy 1mg, USA) and the chamber pressure was measured using an electronic pirani gauge (WIKA Alexander Wiegand Gmbh & Co. Germany).

The tungsten halogen lamp was used as a radiating heat source. The radiation heater was operated at 90W, 220V and 50Hz frequency. The pre-frozen sample was kept directly beneath the tungsten halogen lamp. The distance between the heat source and the vial was 9cm. An insulating thermacol sheet (width 1cm) was used under the vial to provide thermal insulation to the sample so that no heat could get dissipated or accumulated through the metal surface of the drying chamber. The set point temperature of the tungsten halogen radiator was detected by Resistance Temperature Detector (RTD) I and controlled at 50 ± 0.1°C using Proportional-Integral-Derivative (PID) temperature controller (Honeywell, Taiwan; DC 1000 series).

2.5. Experimental design

Experiments were performed according to FCCD (Table 1) formulated through Design Expert software 8.1; in which % reduction in moisture content () and % reduction in enzymatic activity () were selected as response (dependent) variables while, freeze-drying temperature () , freeze-drying time () and initial weight of the sample () were chosen as the operating variables .Variation in sample weight corresponded to the varying distance of the sample from the heat source.

2.6. Experimental procedure

According to the experimental design layout the operating variables were pre-set at a predetermined design value (Table 1) for a particular experimental run. In all the experiments, temperature of the condenser (moisture trap) and average chamber pressure were maintained at - 43 °C and 2.0 ± 0.5 mm Hg respectively. The pre-frozen (-15 ± 1 °C) and pre-weighed sample was put in a screw capped glass vial of capacity 5mL and the vial was placed over a thermacol sheet to provide insulation as mentioned earlier. Immediately before subjecting the sample to vacuum and radiation, the cap of the vial was taken out so that the sample could get radiated properly over a specified time span (). At the end of freeze-drying, the chamber was brought back to ambient pressure through a simultaneous release of vacuum and admission of CO2 from into the drying chamber through a gas cylinder (6.894 X 103 N/m2). The presence of CO2 inhibits oxidative degradation of the sample. Subsequently, the final weight and moisture content of the freeze-dried bacterial strain was measured.

In order to ascertain reproducibility of the data, each experimental run was conducted in triplicate and the measurements of corresponding enzymatic properties were also repeated thrice. It was observed that variations in the magnitudes of the variables were negligibly small.

2.7. Determination of final moisture content ()

For all the experimental runs, moisture content of the control sample were measured using a digital moisture analyzer (Mettler Toledo, Model: MJ33). Depending on the initial moisture content, the final moisture content of the freeze-dried bacteria can be calculated. The of the freeze-dried bacteria was expressed in percentage on a wet basis. All the measurements were done in triplicate with acceptable repeatability. Equating the bone dry mass of the wet and dried samples,

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= initial weight of the sample

= final weight of the sample

= initial moisture content

= final moisture content

2.8. Measurement of product yields (y)

The percent yield of freeze-dried bacteria was measured in terms of the final weight of freeze-dried sample and that of the initial sample taken for freeze-drying and is expressed by Eq. (1):

(1)

2.9. Experimental design and optimization using response surface methodology

The face centered central composite design (FCCD) was created by entering the factors viz. ,, and in terms of ±1 levels (Table 1) to perform RSM using Design-Expert 8.0.7.1 (Stat-Ease, Inc., Minneapolis, USA). To avoid systematic biasness the experiments were conducted randomly. Accordingly, a design layout was created using 15 experimental runs, with six center points. In order to investigate the effects of individual parameters as well as their interactive effects on the response variable, a general second order polynomial response surface model [12-14] was selected and is expressed by Eq. (2):

(2)

where is response variable when k =1,2,3; is a constant intercept; , , and are the linear, quadratic and interaction regression coefficients, respectively, and represent the coded values of the process variables (factors). The regression Eq. (2) was considered for simultaneous multiple optimizations in order to maximize and minimize using the numerical optimization program of the same Design Expert software. For optimization purpose, Myers and Montgomery [15] developed a method for simultaneous optimization of multiple responses which uses a composite objective function, called the overall desirability function. It reflects the desirable range of each desirability function . In this study, has been expressed as a geometric mean of the transformed response variables () as given by Eq. (3):

(3)

Where denotes the number of responses, the desirability function, is expressed as [32]:

If

If

If

where and are constant values (the constraints of the response), s is a positive constant , the ranges from zero to one (least to most desirable, respectively); closer to 1 indicates a satisfactory optimal value. To elaborate further when = 1, the response is at its goal or target, and when = 0, the response is outside a tolerable region. The numerical optimization finds a point that maximizes or minimizes the desirability function. The goal-seeking starts at a random starting point and proceeds up to maximum or minimum. By starting from several points in the design space, the probabilities for finding the best local maximum or minimum were enhanced.

2.10. Modeling of drying kinetics at optimal condition

In order to determine the suitable drying kinetic model for the present study, the experimental results of variation of moisture ratio as a function of drying time under optimal operating conditions was fitted with four well known empirical drying models (Table 3). Moisture content was determined as per the following equation:

The moisture ratio was simplified to instead of . Because in infrared drying, sample may be dried as much as dry matter content. Regression analyses of these equations were done by STATISTICA routine. The regression coefficient () was primary criterion for selecting the best equation to describe the freeze-drying kinetics of the bacteria Bacillus subtilis MTCC 2396. The predictive ability of all the models was evaluated using various statistical parameters such as the mean bias error (), the root mean square error () and the modeling efficiency (), in addition to the regression coefficient (). These parameters can be calculated as follows:

(6)

(7)

(8)

2.11. Evaluation of specific growth rate:

The growth kinetics of both the control and the freeze-dried Bacillus subtilis MTCC 2396 was studied. For the measurement of the specific growth rate, a batch study was conducted with both the control and the freeze-dried bacteria. The freeze-dried bacteria was revived by adding the dried and powdered bacteria to 100mL LB broth and incubated at 37â-¦C for 18 hours. The rest of the experiment was performed by the revived culture of the freeze-dried bacteria. Two sets of conical flasks were prepared each containing 25mL LB broth and inoculated with 50μl of broth culture of both control and the freeze-dried bacteria respectively. Both the sets were incubated at 37â-¦C. At every 2 hours interval a conical flask was removed from both the sets and the optical density was measured in a spectrophotometer (-------------) at 600nm.

2.12. Demonstration of α-amylase activity:

Both the control and the freeze-dried bacteria, Bacillus subtilis MTCC 2396 was grown in amylase extraction media (Bacteriological peptone-0.3gm, MgSO4.7H20- 0.025gm, KCl-0.025gm, Starch-0.05gm, Distilled water-50mL) for 24 hours at 37˚C in an indigenously fabricated BOD shaker (G.B. Enterprises, Kolkata, India).The crude enzyme extract was obtained by centrifuging the broth of both control and freeze dried cells at 10,000 rpm for 20 minutes. The pellet was discarded, the supernatant was collected and was assayed for amylase activity. 1mL of 1% starch solution was added to each of the two test tubes containing 1mL of enzyme extracts obtained from broth of control and freeze dried cells. The solution was mixed and incubated for exactly 3minutes at 20˚C. A coloring reagent solution (Solution 1) was prepared by taking 12g of sodium potassium tartarate dissolved in 8ml of 2M NaOH by direct heating and constant stirring. Another solution was prepared (solution 2) by taking 0.1 M of 3,5-dinitrosalicylic acid and dissolved in 20 mL of deionized water by direct heating and constant stirring. Solution 1 was added slowly into solution 2 and stirred well. The solution was dissolved to 100ml with deionized water. The solution was then stored in a colored bottle at room temperature and from there 1ml was added to both of the test tubes. The test tubes were cotton plugged and placed in a boiling water bath for exactly 15 minutes and cooled on ice to room temperature. Finally 9mL of deionized water was added, mixed well by inversion and the optical density was determined at 540nm, using spectrophotometer (Varian---------) against blank.

2.13. Demonstration of mercuric reductase activity:

Mercuric reductase converts soluble inorganic Hg2+ to Hg0, which is rapidly eliminated from aerobic microbial cultures as a gas, and organomercurial lyase, which cleaves the Hg-C bond of more toxic methylmercury, phenylmercury, and other organomercurials to less toxic inorganic Hg2+ [16]. The measurement of mercuric reductase activity corresponds to the depletion of mercury from water. A comparative study was performed between the control and the freeze-dried bacterial strain with respect to the enzyme mercuric reductase which is expressed by the merA gene present in the bacteria mostly in the plasmids [17]. For the study, 1ppm mercury solution was prepared from a 1000ppm stock. The 1ppm solution was added to 50mL broth (composition: sucrose-1g, sodium chloride-3g, yeast extract-1g dissolved in 100mL distilled water, pH maintained at 7) in several conical flasks of volume 100mL. 1mL culture broth of both control and freeze-dried Bacillus subtilis MTCC 2396 was added to the respective conical flask as labeled and was kept in the BOD shaker incubator for batch study. At an interval of 24hours a flask with control bacteria and one with freeze-dried bacteria was taken out of the incubator, the content was centrifuged at 10,000 rpm for 20 minutes. The supernatant was collected and analysed for the depletion of mercury.

Result and Discussion:

3.1. Effects of process parameters (factors) on final moisture content

The FCCD was carried out to determine the model equation to predict the effects of process parameters on the reduction in moisture content, . In accordance with the statistical model fit summary (Table 4), a quadratic model was selected as the best fitted model with, lower standard deviation () and lower PRESS value (1.51), higher adjusted and predicted values (0.9973 and 0.9918) and adequate precision >4 in comparison with other models viz. linear and 2FI. ANOVA (Table 5) for quadratic model shows insignificant lack of fit (p-value 0.16 > 0.05), high value (0.99), low C.V. value (1.42 < 10), acceptable model p-value < 0.0001; which finally proves the adequacy of the proposed quadratic model. Moreover, ANOVA (Table 5) elucidates the model insignificant terms (p > 0.05) which are neglected to yield the final model equation in coded form as expressed by Eq. (9):

(9)

It is evident from Eq. (9) as well as from ANOVA (Table 5) that is the most prominent factor followed by and influencing moisture content of Bacillus subtilis MTCC 2396. All the three parameters have positive effects on the reduction of moisture content. The two factor interaction terms viz. , and are significant in governing the .The relative weightage of these terms are in the order (F-value 115.53)> ( F-value 0.42)> (F-value 0.40). At both lowest and highest level of freeze-drying temperature 20â-¦C to 50â-¦C increase in operating time from 4h to 8h could render an increase in from 85.6746 to 86.6332 and from 95.3265 to 96.05 respectively. Likewise, at both lowest and highest level of freeze-drying temperature 20â-¦C to 50â-¦C increase in the initial weight of the sample from 4g to 5g could render an increase in from 86.5006 to 86.5395 and 94.9473 to 95.0235 respectively. And, at both the minimum and maximum values of operating time marginal enhancement in could be observed It can also be elucidated from Eq. (9) that longer freeze-drying time () results lower moisture content of the product. Evidently, as freeze-drying time increases the sample receives excess amount of radiation energy which increases moisture transfer rate resulting into reduced final moisture content.

3.2. Effects of process parameters (factors) on enzyme activity ()

The FCCD was carried out to determine the model equation to predict the effects of process parameters on enzyme activity (). In accordance with the statistical model fit summary (Table 4), a quadratic model was selected as the best fitted model with, lower standard deviation () and lower PRESS value (1.51), higher adjusted and predicted values (0.9973 and 0.9918) and adequate precision >4 in comparison with other models viz. linear and 2FI. ANOVA (Table 5) for quadratic model shows insignificant lack of fit (p-value 0.16 > 0.05), high value (0.96), low C.V. value (1.42 < 10), acceptable model p-value (Prob > F) < 0.0001; which finally proves the adequacy of the proposed quadratic model. Moreover, ANOVA (Table 5) elucidates the model insignificant terms (p > 0.05) which are neglected to yield the final model equation in coded form as expressed by Eq. (10):

=++0.0110.054+0.051+0.18

0.0370.052 (10)

From the above equation (10) and ANOVA (Table 5) it is evident that freeze-drying temperature is the most influential factor followed by the freeze-drying time and the initial weight of the sample in the reduction of enzyme activity of Bacillus subtilis MTCC 2396. The three factors, , and have positive effect on the reduction of enzyme activity. The two factor interaction terms, viz. , and are significant in governing the . The relative weightage of these terms are in the order (F-value 34.60)> ( F-value 14.18)> (F-value 2.67). At the lowest and highest levels of operating time increase in freeze-drying temperature from 20â-¦C to 50â-¦C could provide enhanced from 1.12525 to 1.39802 and 4.7858 to 5.0202 respectively.

Similarly, at the lowest and highest levels of freeze-drying temperature increase in the initial weight of the sample renders increase in from 86.5006 to 86.5395 and 94.9473 to 95.0235 respectively. And, at the lowest and highest levels of operating time increase in the initial weight of the sample renders increase in from 2.67611 to 2.75661 and from 2.92518 to 3.04096 respectively.

3.3. Evaluation of specific growth rate:

The specific growth rate of the control and the freeze-dried bacteria are 0.139 h-1 and 0.132 h-1. The calculation was done according to ---------------------------. From the result it is obvious that tungsten halogen assisted freeze-drying of Bacillus subtilis MTCC 2396 has a very negligible detrimental effect on the specific growth rate. The growth of the freeze-dried bacteria remained almost same as the control bacteria.

3.4. Estimation of α-amylase activity:

The specific activity of the enzyme of the control and the freeze-dried bacterial sample is found to be 0.0496 U and 0.0476U which means, which means 0.0496 µmol and 0.0476µmol of glucose was produced in a 1% starch solution of pH 7 and at temperature 20â-¦C.

3.5. Estimation of mercuric reductase activity:

3.4. Optimization

In the present study an attempt has been made to find the optimal process conditions for the freeze-drying of the bacteria Bacillus subtilis MTCC 2396 using tungsten halogen lamp as a source of radiation. Here, the simultaneous maximization of and the minimization of has been done. For both the response variables viz. and , the process factors were kept within the range of data as given in FCCD (Table 1) and different importance was assigned to both process and response variables (Table 6). The numerical optimization program was run to find out the optimal parametric values as presented in Table 7. Solution number 1 computed by the software having maximum D was selected. At optimal conditions the required drying time is 6 h which is less than 40 h reported by D.A. Tessema et al. [18] keeping the moisture content in the appreciable value 4.8 and the α-amylase activity intact.

3.4.1. Freeze-drying kinetics at optimal conditions

An attempt has been made to describe freeze-drying kinetics at optimal conditions using four drying models [19]. The model equations representing time evolution of moisture ratio of the bacteria subjected to freeze-drying are presented in Table 9. Using the experimental data taken under identical conditions, four different models namely Newton model, Handerson and Pabis model, Wang and Sing model and Page model have been used for the purpose of testing their suitability for prediction of system dynamics. Fig. 3a shows the comparison of these models. It is observed that the Wang and Sing model has maximum regression coefficient () and modeling efficiency (EF) along with lowest RMSE and MBE values amongst these models. Hence, the Wang and Sing model could represent the freeze-drying of Bacillus subtilis MTCC 2396 more closely compared to other models (Fig. 3.a). It may be mentioned here that the freeze-drying rate computed in the present case is the global drying rate incorporating the effects of multiple parameters on this global rate. Vapor diffusion is one such parameter, thus individual contribution of vapor diffusion has not been considered in the present case. The rate of decrease of normalized moisture content (Fig. 3b) presents an interesting result. Unlike conventional drying operation no constant drying rate period is observed in this situation, as a result critical moisture content does not play any role in freeze-drying operation. The shape of the curves in Fig. 3a and the variation of the drying rate in Fig. 3b also indicate that the internal diffusion of water vapor inside the sample is controlling the freeze-drying process. The phenomenon can be explained briefly as follows: at the initiation of freeze-drying (MR = 1.0), the sublimation front (moving boundary) is situated at the surface of the test sample. With the progress of freeze-drying, the sublimation front recedes from the surface towards the center of the sample resulting in increased diffusion path for the sublimed moisture originated at the sublimation (ice) front; which in turn renders increased resistance to internal diffusion of water vapor inside the sample. Thus, the internal diffusion rate of moisture is found to decrease with time (as well as with MR) and approaches towards equilibrium moisture content.

Conclusion:

The present study explores a novel method of lyophilization involving tungsten halogen irradiation that could significantly reduce the time of operation in comparison with conventional lyophilization protocol. The product lyophilized bacteria Bacillus subtilis MTCC 2396 possessed acceptably low final moisture content and could exhibit acceptable enzyme activity. The reduction in operating drying time of the freeze-dryer (lyophilizer) can render significant reduction in operating cost while maintaining acceptable product quality thus making the whole process economically viable.