Improving production of hyperthermostable and high maltose-forming α-amylase by an extreme thermophile Geobacillus thermoleovorans using response surface methodology and its applications

Bioresource Technology 98 (2007) 345–352

Improving production of hyperthermostable and high maltose-forming a-amylase by an extreme thermophile Geobacillus thermoleovorans using response surface methodology and its applications J.L. Uma Maheswar Rao, T. Satyanarayana

*

Department of Microbiology, University of Delhi South Campus, Benito Juarez Road, New Delhi 110 021, India Received 17 October 2005; received in revised form 22 December 2005; accepted 24 December 2005 Available online 10 February 2006

Abstract By cultivating Geobacillus thermoleovorans in shake flasks containing cane molasses medium at 70 C, the fermentation variables were optimized by ‘one variable at a time’ approach followed by response surface methodology (RSM). The statistical model was obtained by central composite design (CCD) using three variables (cane-molasses, urea and inoculum density). An overall 1.6- and 2.1-fold increase in enzyme production was achieved in the optimized medium in shake flasks and fermenter, respectively. The a-amylase titre increased significantly in cane-molasses medium (60 U ml1) as compared to that in the synthetic medium (26 U ml1). Thus the cost of enzyme produced in cane molasses medium (€0.823 per million U) was much lower than that produced in the synthetic starch–yeast extract-tryptone medium (€18.52 per million U). The shelf life of bread was improved by supplementing dough with a-amylase, and thus, the enzyme was found to be useful in preventing the staling of bread. Reducing sugars liberated from 20% and 30% raw pearl millet starch were fermented to ethanol; ethanol production levels attained were 35.40 and 28.0 g l1, respectively.  2006 Elsevier Ltd. All rights reserved. Keywords: Ca2+-independent a-amylase; Response surface methodology; Cane molasses; Antistaling; Ethanol

1. Introduction a-Amylase (EC 3.2.1.1) is one of the enzymes of worldwide interest in food, pharmaceutical and fermentation industries. This enzyme is used in the conversion of starch into different sugar syrups. Industrial applications generally require amylases with a very specific hydrolysis profile. A need for more thermostable a-amylases devoid of requirement for Ca2+ for their activity/stability in starch saccharification has been emphasized (Antranikian, 1992; Malhotra et al., 2000), since the added Ca2+ must be removed from the product streams by using ionexchangers.

*

Corresponding author. Tel.: +91 11 2112008; fax: +91 11 26885270. E-mail addresses: [email protected], [email protected] (T. Satyanarayana). 0960-8524/$ - see front matter  2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2005.12.022

The conventional practice of single factor optimization by maintaining other factors at an unspecified constant level does not depict the combined effect of all the factors involved. The method requires a large number of experiments to determine optimum levels, which is tedious and time consuming. Optimizing all the effecting parameters can eliminate these limitations of a single factor optimization process collectively by statistical experimental design using Response Surface Methodology (RSM). It is well documented that extracellular amylase production by microbes is greatly influenced by media components, especially carbon and nitrogen sources, minerals and physical factors such as pH, temperature, agitation, dissolved oxygen and inoculum density (Babu and Satyanarayana, 1993; Dey et al., 2001; Gigras et al., 2002). Statistical optimization not only allows quick screening of a large experimental domain, but also reflects the role of each of the components. Application of RSM has gained attention of

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researchers for optimizing media components and process parameters (Stamford et al., 2001; Dey et al., 2002; Vohra and Satyanarayana, 2002; Kumar and Satyanarayana, 2003, 2004). The cost of enzyme production is a major obstacle in its successful industrial application (Haq et al., 2003). The importance of retrogradation of starch fraction in bread staling has been emphasized (Kulp and Ponte, 1981). A loss of more than US$1 billion is incurred in USA alone every year due to the staling of bread in peak winters. Conventionally various additives and enzymes are used to prevent staling and to improve the texture and shelf life of baked products (Hebeda et al., 1991; Pritchard, 1992). Ethanol produced from renewable sources by fermentation is the most promising biofuel and the starting material for various chemicals. In US, ethanol produced from cornstarch has already been used as biofuel and production volume has increased rapidly. However, processes to reduce the high production costs are required (Kondo et al., 2000). Ethanol producing microorganisms such as Saccharomyces cerevisiae and Zymomonas mobilis lack amylolytic enzymes and are unable to directly convert starch into ethanol. Traditionally, the starch is hydrolysed enzymatically into fermentable sugars via liquefaction and saccharification processes prior to ethanol fermentation (Kobayashi et al., 1998). We have recently attempted to develop an ideal starch saccharification process using thermostable amylolytic enzymes such as a-amylase in combination with debranching and saccharifying enzymes, amylopullulanase and glucoamylase (Satyanarayana et al., 2004). The moderate thermostability and Ca2+ requirement of a-amylases limit their industrial potential. This investigation was, therefore, carried out for optimizing the production of high maltose-forming, hyperthermostable and Ca2+-independent a-amylase by Geobacillus thermoleovorans using RSM in low-cost fermentation medium containing cane molasses, and testing its applicability in baking as an antistaling agent and saccharification of raw starch of pearl millet (Pennisetum typhoides) and subsequent fermentation of starch hydrolysate to ethanol. 2. Methods 2.1. Source of strain G. thermoleovorans NP54 was isolated from a water sample collected from a hot water spring of the Waimangu volcanic valley (New Zealand), and maintained as described earlier (Malhotra et al., 2000; Narang and Satyanarayana, 2001; Uma Maheswar Rao and Satyanarayana, 2003, 2004a,b).

Erlenmeyer flask containing 50 ml of starch–yeast extracttryptone (SYT) broth [g l1: soluble starch 20.0; yeast extract 3.0; tryptone 3.0; K2HPO4 1.0; MgSO4 Æ 7H2O 0.2; NaCl 1.0; pH 7], and incubating for 5 h at 70 C and 200 rpm. The culture was aseptically centrifuged at 8000g for 15 min at 4 C (Sorvall RC 5C plus, Kendro labs, USA). The cells thus sedimented were washed two times with sterile distilled water and resuspended in 50 ml sterile distilled water. This bacterial cell suspension was used as the inoculum for a-amylase production. 2.3. Optimization of enzyme production by applying RSM The cane molasses medium was optimized by ‘one variable at a time’ approach for a-amylase production, and further optimization was done by using RSM of CCD. The levels of three independent variables selected [cane molasses (A), urea (B) and inoculum density (C)] were optimized by RSM. Each factor in the design was studied at five different levels (Table 1). A set of 20 experiments was performed. All variables were taken at a central coded value considered as zero. The minimum and maximum ranges of variables were used, and the full experimental plan with respect to their values in actual and coded form is listed in Table 2. Upon completion of experiments, the average of a-amylase production was taken as the dependent variable or response (Y). 2.4. Statistical analysis and modeling The data obtained from RSM on a-amylase production were subjected to the analysis of variance (ANOVA). The results of RSM were used to fit a second-order polynomial equation (1), as it represents the behavior of such a system more appropriately Y ¼ b0 þ b1 A þ b2 B þ b3 C þ b1 b1 A2 þ b2 b2 B2 þ b3 b3 C 2 þ b1 b2 AB þ b1 b3 AC þ b2 b3 BC

where Y = response variable, b0 = intercept, b1, b2, b3 = linear coefficients, b1,1, b2,2, b3,3 = squared coefficients, b1,2, b1,3, b2,3 = interaction coefficients, and A, B, C, A2, B2, C2, AB, AC, BC = level of independent variables. Statistical significance of the model equation was determined by Fisher’s test value, and the proportion of variance explained by the model was given by the multiple coefficient of determination, R squared (R2) value. Design Expert (Ver.6.0) by STATEASE Inc., Minneapolis, USA was used in this investigation.

Table 1 Range of values for the response surface methodology Independent variables

Levels a

1

0

+1

+a

Cane molasses (% v/v) Urea (%) Inoculum level (%)

5.32 0.10 0.15

6.00 0.15 0.75

7.00 0.22 1.63

8.00 0.30 2.50

8.68 0.35 3.10

2.2. Inoculum preparation The inoculum was prepared by transferring a loopsful from a fresh culture of G. thermoleovorans into a 250 ml

ð1Þ

J.L. Uma Maheswar Rao, T. Satyanarayana / Bioresource Technology 98 (2007) 345–352

347

Table 2 Experimental design and results of CCD of response surface methodology

2.7. Assay of a-amylase

Exp. no.

The saccharogenic a-amylase activity was determined by the modified method of Bernfeld (1955) by incubating the reaction mixture at 100 C for 10 min (pH 8.0). One saccharogenic a-amylase unit is defined as the amount of enzyme required for the liberation of one lmol of reducing sugars ml1 min1 under the assay conditions.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Cane molasses (%)

Urea (%)

1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 a +a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.00 0.00 a +a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Inoculum level (%)

1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.00 0.00 0.00 0.00 a +a 0.00 0.00 0.00 0.00 0.00 0.00

a-Amylase production (U l1) Experimental

Predicted

15,000 25,000 23,000 28,000 26,000 25,000 24,000 28,000 22,000 28,000 35,000 40,000 16,000 28,000 45,310 45,230 45,300 45,150 45,200 45,100

16,600 27,930 22,970 29,210 27,690 27,930 26,060 29,300 20,230 25,670 32,200 38,700 15,250 24,650 45,330 45,330 45,330 45,330 45,330 45,330

2.5. a-Amylase production in starch–yeast extract-tryptone medium a-Amylase was produced in starch–yeast extract-tryptone (SYT) broth (Uma Maheswar Rao and Satyanarayana, 2003) by inoculating with 5 h old bacterial culture (2% or 1.8 · 108 CFU ml1) and incubating at 70 C and 200 rpm for 12 h (Uma Maheswar Rao and Satyanarayana, 2004a,b). The cultures were harvested by centrifugation at 8000g for 15 min at 4 C and the cell-free supernatants were used in a-amylase assay. 2.6. a-Amylase production in cane molasses medium Erlenmeyer flasks (250 ml) containing 50 ml of cane molasses medium prepared in tap water [g l1: cane molasses v/v (variable); urea (variable) pH 7.0] were inoculated with 5 h old bacterial culture (1.8 · 108 CFU ml1) [variable] and incubated at 70 C for 12 h and 200 rpm. The culture was harvested by centrifugation and the cell-free supernatant was used as the source of extracellular aamylase. The bacterial strain was also cultivated in 0.25, 0.5, 1.0 and 2.0 l Erlenmeyer flasks and Biostat C fermenter (B. Braun, Germany) containing 0.05, 0.1, 0.2, 0.4 and 10 l of the medium optimized by RSM [g l1: cane molasses 70 (v/v); urea 2.2; pH 7.0], respectively, and then inoculated with 1.63% of 5 h old inoculum (1.8 · 108 CFU ml1). The fermenter was operated at 65 C, 200 rpm and 1 vvm of aeration. The pH of the medium was maintained at 7.0 using sterile 1 M NaOH/HCl. The samples were withdrawn at the desired intervals and assayed.

2.8. Determination of total sugars Anthrone reagent was used to estimate total sugars in the culture fluid according to Brink et al. (1960). 2.9. Applications of a-amylase in bread baking Wheat flour (500 g) was mixed with dry yeast (4.5 g), 1.5% NaCl, 2.0% sucrose, 10 ml (v/w) sunflower oil and 2.5 ml of a-amylase of G. thermoleovorans (65.0 U), blended with 60% water, and thoroughly mixed mechanically for 30 min to produce dough. This was allowed to undergo proofing by fermenting for an extended period of up to 2 h, followed by baking at 275 C for 30 min, shaping and cutting. This process was performed with/ without a-amylase of G. thermoleovorans. The breads were assessed for shelf life and softness at different time intervals. 2.10. Starch saccharification The slurry of 20% and 30% (w/v) raw starch of pearl millet (P. typhoides) was prepared in phosphate buffer (0.1 M, pH 7.0), gelatinized at 105 C for 5 min, followed by treatment with a-amylase (5 U g1) for 3 h at 100 C. This was followed by treatment with amylopullulanase (5 U g1) of G. thermoleovorans NP33 for 4 h at 80 C and glucoamylase (5 U g1) of Thermomucor indicae-seudaticae at 60 C for 12 h. The percent starch saccharification was determined according to Mishra and Maheshwari (1996). The reducing sugars in the hydrolysae were fermented to ethanol using S. cerevisiae. 2.11. Bioethanol production and its estimation by gas chromatography The ethanol production medium (hydrolysate containing reducing sugars 20%, (NH4)2SO4 0.3, CaCO3 0.05, MgSO4 Æ 7H2O 0.1, yeast extract 0.2, pH 5.0) was inoculated with 2% inoculum of S. cerevisiae (3.0 · 106 CFU ml1) and incubated at 30 C for 12 h at 200 rpm and then shifted to static conditions at 30 C for 24 h. Ethanol concentration in the cell-free fermented broth was determined by gas chromatography. A gas chromatograph (Model Gc-81; Shimadzu, Kyoto, Japan) fitted with a flame ionization detector was operated under the following conditions: glass column (3.2 mm · 3.0 m) packed with Thermon-3000 (Shimadzu); temperature of column,

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injector and detector, 180 C, and nitrogen carrier gas flow rate of 25 ml min1. All the experiments were conducted in triplicates and the mean values are presented. 3. Results The results of CCD experiments for studying the effect of three independent variables are presented along with the mean predicted and observed responses. The regression equations obtained after the analysis of variance (ANOVA) presented the level of a-amylase production as a function of the initial values of cane molasses, urea and inoculum size. The final response equation that represented a suitable model for a-amylase production is given below:

Response surface curves were generated by plotting the response (a-amylase production) on the Z-axis against any two independent variables while keeping the other independent variables at their ‘O’ levels. Fig. 1 depicts three-dimensional diagram and a contour plot of calculated response surface from the interaction between cane molasses and urea while keeping all other variables at their ‘O’ level. A linear increase in a-amylase production was observed when cane molasses concentration was increased up to 7%, and thereafter, it declined sharply. When the level of urea concentration was increased from 0.1% to 0.22%, a linear increase in the a-amylase production was recorded. At the ‘O’ level of inoculum, the response between inoculum

Y ¼ 45:33 þ 1:62  A þ 1:93  B þ 2:80  C Enzyme titre (U ml-1)

 7:91  A2  3:49  B2  8:97  C 2 þ 0:75  AB  0:75  AC  200  BC

se

s 6.50 ola 6.00 em n

Ca

Enzyme titre (U ml-1)

45.6001 40.0203 34.4406 28.8608 23.2810

2.50 8.00

2.06 7.50

1.63 1.19

) %

/v )v (% s 6.50 sse ola m 6.00 ne Ca 7.00

e(

Mean of three values, SD with in 10%.

0.15

)

a

/v

45,330 47,200 48,600 45,000 60,000

0.19

/v

)v

% s(

Fig. 1. Three-dimensional curve showing the effect of cane molasses and urea on amylase production in the RSM-optimized medium.

siz

12 12 12 12 5

)v

250 500 1000 2000 22,000 (Fermenter)

7.00

m

50 100 200 400 10,000

7.50

0.22

lu

Enzyme titre (U l1)a

8.00

0.26

(%

Fermentation time (h)

0.30

u oc

Volume of flask (ml)

31.6178

In

Medium volume (ml)

35.1702

ea

Table 3 a-Amylase production in the cane molasses medium optimized by RSM in flasks and fermenter

42.275 38.7226

Ur

where Y = enzyme production, A = cane molasses (% v/v), B = urea (%) and C = inoculum level (%). The coefficient of determination (R2) was calculated as 0.9765 for a-amylase production (Table 3), indicating that the statistical model can explain 97.65% of variability in the response. The R2 value was always between 0 and 1 and the closer the R2 was to 1.0, the stronger the model and the better it predicted the response (Haaland, 1989). The purpose of statistical analysis was for determining the experimental factors, which generated signals that were large in comparison to the noise. An adequate precision of 18.63 for aamylase production was recorded. The predicted R2 of 0.8214 was in reasonable agreement with the adjusted R2 of 0.955. This indicated a good agreement between the experimental and predicted values for a-amylase production. The adjusted R2 corrected the R2 value for the sample size and for the number of terms in the model. If there are many terms in the model and the sample size is not very large, the adjusted R2 may be noticeably smaller than the R2. The model F-value of 46.25, and values of prob > F (<0.05) indicated that the model terms were significant. For a-amylase production, A, B, C, A2, B2, C2 and BC were a significant model. The lack of fit F-value of 1525.43 implied that the lack of fit was significant.

45.8274

0.75

Fig. 2. Three-dimensional curve showing the effect of cane molasses and inoculum level on a-amylase production in the RSM-optimized medium.

J.L. Uma Maheswar Rao, T. Satyanarayana / Bioresource Technology 98 (2007) 345–352

level and cane molasses indicated that a lower inoculum level (1.63%) was desirable with 7% (v/v) cane molasses. The response surface was mainly used to find out the optima of the variables for which the response was maximized (Fig. 2). An interaction between the remaining two parameters (inoculum level and urea) suggested a little difference with the earlier responses. As compared to other responses, this response graph gave a lower enzyme yield. 3D plots of cane molasses concentration and inoculum level (Fig. 2) showed that a higher level of both parameters led to a negative impact on a-amylase production. The 3D plot proved the significance of earlier responses, i.e. of cane molasses with inoculum level and urea (Figs. 1 and 2). Thus, urea (0.22%), cane molasses (7% v/v) and inoculum density (1.63%) were adequate for attaining a maximum enzyme titre (45,330 U l1). The optimum levels of inoculum and cane molasses were chosen to achieve maximum yield of a-amylase. Fig. 3 suggested that a cane molasses concentration of 7% and inoculum level of 1.63% should be selected since these supported a high secretion of aamylase. The total sugars in cane molasses medium were

50

Enzyme titre (U ml-1)

45 40 35 30 25 20 15 1.2

1.4

1.6

1.8

5

6

7

2.2

2.4

8

9

10

reduced with increasing time till 12 h, and thereafter, a plateau in sugar levels was recorded (Fig. 4A). 1.8

30

80

70

20

Total sugars (%)

1.4 90

1.2 1.0 0.8 0.6

60

Optical density at 600 nm

1.6

40

0.4

10 50

0

0.2

40

0.0

70

110

3.0

60

100

2.5

2

4

6

(A)

8

10

12

14

90

40 80 30 70

2.0

1.5

1.0

20 60

0.5

50

0.0

10 0

Optical density at 600 nm

50

Total sugars (%)

Time (h)

40 0

(B)

1

2

3

11

Fig. 3. One factor plot showing the effect of cane molasses and inoculum level on a-amylase production at 1.63% inoculum level.

110

0

2.6

Cane molasses (%) (v/v)

100

Enzyme titre (U ml-1)

2.0

Inoculum size (%)

50

Enzyme titre (U ml-1)

349

4

5

6

7

Time (h)

Fig. 4. a-Amylase production and growth profile in optimized cane molasses medium in (A) shake flasks and (B) fermenter.

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Table 4 Saccharification (%) of raw starch (P. typhoides) by amylolytic enzymes and fermentation of starch hydrolysate to ethanol Raw starch concentration (%)

% Starch saccharification Raw starch hydrolysed after 3 h with a-amylase (5 U g1)

a-Amylase treatment followed by amylopullulanase for 4 h (5 U g1)

Amyopullulanlase treatment followed by glucoamylase for 12 h (5 U g1)

Ethanol production (g l1)

20 30

68.0 55.8

85.0 80.0

98.0 92.4

38.2 28.0

3.1. Validation of the model The model was validated by carrying out experiments in shake flasks under conditions predicted by it. The experimental values were found to be very close to the predicted values, and hence, the model was successfully validated. Validation of the statistical model and regression equation were derived by taking A (7% v/v), B (0.22%) and C (1.63%) in the experiment. The predicted response for a-amylase production was 45,330 U l1, while the actual (experimental) response was 45,310 U l1, thus proving the validity. The production of a-amylase was sustainable in shake-flasks up to 1 l followed by a marginal decline, and enhanced in the fermenter (Table 3). A peak in enzyme production was attained in 5 h in the fermenter as compared to that of 12 h in the flasks (Fig. 4B). The supplementation of dough with a-amylase resulted in improved bread quality. Further more, the bread was stable and remained soft for five days in contrast to the bread made without a-amylase that showed staling within three days of storage in winter season. When 20% and 30% raw pearl millet starch were treated with crude a-amylase for 3 h, the sugar yields were 68% and 55.8%, respectively. On subsequent treatment with hyperthermostable amylopullulanase of G. thermoleovorans for 4 h, 85% and 80% starch saccharification rates were attained from 20% and 30% raw starch, respectively. It further enhanced to 98% and 92.4%, respectively, when the hydrolysate was treated with glucoamylase of Thermomucor indicae-sedaticae for 12 h (Table 4). On fermentation of reducing sugars in the hydrolysates, ethanol production levels were 35.40 and 28.0 g l1. 4. Discussion The extracellular enzymes produced by various Bacillus species play a vital role in the present day biotechnology (Priest, 1984). The estimated value of the world enzyme market in 2005 is about US$2.0 · 109 (Godfrey and West, 1996), and a half of this is produced by Bacillus species (Meima and Van Dijl, 2003). Amylolytic enzymes alone account for almost US$225 million (Walsh, 2002). a-Amylase from B. licheniformis and B. amyloliquefaciens used in the liquefaction of starch requires Ca2+ for its stability and/or activity (Koch et al., 1990, 1991). While G. thermoleovorans secretes a novel a-amylase, which is hyperther-

mostable (T1/2 of 3 h at 100 C), high maltose-forming and independent of Ca2+ for its activity/stability (Uma Maheswar Rao and Satyanarayana, 2003). There is no general defined medium for a-amylase production by different microbial strains (Pandey et al., 2000). Every microorganism has its own peculiar physio-chemical and nutritional requirements for a-amylase production. In view of the commercial utility of the enzyme, formulation of a cost-effective media becomes a primary concern. Molasses, a by-product of sugar industry, is one of the cheapest sources of carbohydrates. Besides a large amount of sugar [50% (sucrose 33.5%, invert sugar 21.2%)], molasses contain nitrogenous substances (0.4–1.5%), vitamins such as thiamine (830 lg per 100 g dry weight), pyridoxine (650 lg per 100 g), folic acid (3.8 lg per 100 g), biotin (120 lg per 100 g), pantothenic acid (2140 lg per 100 g), and trace elements (CaO 0.1–1.1%; MgO 0.03–0.1%; K2O 2.6–5.0%) (Crueger and Crueger, 2000). Response surface methodology applied to optimize the production of a-amylase in this investigation suggested the importance of various factors at different levels. A high similarity was observed between the predicted and experimental results that reflected the accuracy and applicability of RSM to optimize the process for enzyme production. A 2-fold increase in a-amylase production was reported in B. circulans GRS 313 (Dey et al., 2001) and Aspergillus oryzae (Gigras et al., 2002) by using response surface methodology; yeast extract and soybean meal concentrations significantly influenced the enzyme production. Among three variables tested in this investigation, the concentration of cane molasses and inoculum density influenced the enzyme secretion. The enzyme yield attained was higher than that at concentrations considered to be optimal by ‘one variable at a time’ approach, and further, the concentrations of variables considered to be optimum by the approach were actually higher than those actually required for maximum enzyme secretion. The inoculum age and size are known to affect microbial growth and enzyme production. An inoculum size of 1.63% supported a high enzyme secretion. At higher inoculum levels, the enzyme production levels declined, which could be due to the competition for nutrients as observed in Bacillus coagulans (Babu and Satyanarayana, 1993). The production of a-amylase in flasks was sustainable up to 1 l, and it declined in a 2 l flask. This could be the due to improper mixing of nutrients and inadequate aera-

J.L. Uma Maheswar Rao, T. Satyanarayana / Bioresource Technology 98 (2007) 345–352

tion on increasing the volume of the medium (Narang and Satyanarayana, 2001). The enzyme production increased in a laboratory fermenter. The reduction in the enzyme production time and enhancement in amylase secretion in the bioreactor has been attributed to uniform distribution of nutrients, improved aeration and maintenance of pH (Narang and Satyanarayana, 2001). Improvements in product yields are expected in the fermenter due to better control of process parameters (Humphrey, 1998). a-Amylase synthesis was growth associated in shake flasks. Its production ceased in the fermenter before cessation of the growth with concomitant secretion of other enzymes such as acid protease and xylanase (data not shown). Due to maintenance of pH and better aeration in the fermenter, the growth was not affected. Similar observations were recorded during penicillin production (Bu’Lock et al., 1965). Growth and enzyme production in shake flasks attained a plateau after approximately 50% sugar consumption. The remaining substrate could not be metabolized due to lowering of pH from 7.0 to 4.5 that affected growth and enzyme production. Similar findings were recorded by Babu and Satyanarayana (1993) in B. coagulans. The baking industry has made use of several enzymes for hundreds of years to manufacture a wide variety of high quality products. Upon storage, the crumb becomes dry and firm, the crust loses its crispness and the flavor of the bread deteriorates. All these undesirable changes in the bread are together known as staling. The supplementation of wheat flour with a-amylase of G. thermoleovorans not only enhanced the rate of fermentation and reduced the viscosity of dough resulting in the improvement of volume and texture of bread, but also increased its shelf life and softness as reported by Gupta et al. (2003). The most important use of a-amylase is in the starch industry, and hence, an attempt was made to find the applicability of this enzyme in raw-starch saccharification. Soni et al. (1995) and Mishra and Maheshwari (1996) used glucoamylases of fungal origin for starch saccharification; the former used acid for liquefaction of starch to obtain a high glucose syrup, while the latter used a-amylase; a 70% starch saccharification was achieved. The addition of specific debranching enzymes like pullulanase augments the a1,6 activity of glucoamylase (Bentley and Williams, 1996). When glucose liberated from 20% and 30% of raw pearl millet starch were fermented using S. cerevisiae, 35.40 and 28.0 g l1 ethanol were attained from the hydrolysates. These values are higher than those reported by other workers (Kobayashi et al., 1998; Kondo et al., 2000). A significant enhancement in the production of a-amylase by G. thermoleovorans was achieved in cane molasses medium as compared to that in SYT medium. Cane molasses medium is also very cost-effective because the cost of amylase production in cane molasses medium (€0.823 per million U) was much lower than that in synthetic SYT medium (€18.52 per million U). The use of this enzyme in starch hydrolysis eliminates the addition of Ca2+ in

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starch liquefaction and its subsequent removal by ion exchangers from the product streams (Satyanarayana et al., 2004). The enzyme was found to be applicable in bread making as well as ethanol production from cheaper starch sources such as pearl millet. Acknowledgements The authors thank Mr. Vijay Kumar Gupta (Tushar Nutritive Food Industry, New Delhi) for extending help in assessing the applicability of a-amylase in bread manufacture. Thanks are due to Mr. Ezhilvannan and Mr. Pardeep Kumar for kindly providing amylopullulanase and glucoamylase, respectively. References Antranikian, G., 1992. Microbial degradation of starch. In: Winkelmann, G. (Ed.), Microbial Degradation of Natural Products. VCH, Weinheim, Germany, pp. 27–51. Babu, K.R., Satyanarayana, T., 1993. Parametric optimization of extracellular a-amylase production by thermophilic Bacillus coagulans. Folia Microbiol. 38, 77–80. Bentley, I.S., Williams, E.C., 1996. Starch conversion. In: Godfrey, T., West, S. (Eds.), Industrial Enzymology. Macmillan Press, London, UK, pp. 339–357. Bernfeld, P., 1955. Amylases, a and b. In: Colowick, S.P., Kaplan, O.N. (Eds.), Methods in Enzymology. Academic Press, New York, pp. 140– 146. Brink, R.H., Dubach, P., Lynch, D.L., 1960. Measurement of carbohydrate in soil hydrolysates with anthrone. Soil Sci. 89, 157–166. Bu’Lock, J.D., Hamilton, D., Hulme, M.A., Powell, A.J., Shepherd, D., Smalley, H.M., Smith, G.N., 1965. Metabolic development and secondary biosynthesis in Penicillium urticae. Can. J. Microbiol. 11, 765–778. Crueger, W., Crueger, A., 2000. Substrates for industrial fermentation. In: Crueger, W., Crueger, A. (Eds.), Biotechnology, A textbook of Industrial Microbiology. Panima Publisher Corporation, New Delhi, pp. 59–62. Dey, G., Mitra, A., Banerjee, R., Maiti, B.R., 2001. Enhanced production of amylase by optimization of nutritional constituents using response surface methodology. Biochem. Eng. J. 7, 227–231. Dey, G., Palit, S., Banerjee, R., Maiti, B.R., 2002. Purification and characterization of maltooligosaccharide-forming amylase from Bacillus circulans GRS 313. J. Ind. Microbiol. Biotechnol. 28, 193–200. Gigras, P., Sahai, V., Gupta, R., 2002. Statistical media optimization and production of its ITS alpha amylase from Aspergillus oryzae in a bioreactor. Curr. Microbiol. 45, 203–208. Godfrey, T., West, S.I., 1996. Introduction to industrial enzymology. In: Godfrey, T., West, S.I. (Eds.), Industrial Enzymology, second ed. Macmillan Press Limited, London, p. 3. Gupta, R., Gigras, P., Mohapatra, H., Goswami, V.K., Chauhan, B., 2003. Microbial a-amylases: a biotechnological perspective. Process Biochem. 38, 1599–1616. Haaland, P.D., 1989. Statistical problem solving. In: Haaland, P.D. (Ed.), Experimental Design in Biotechnology. Marcel Dekker Incorporation, New York, pp. 1–18. Haq, I., Ashraf, H., Iqbal, J., Qadeer, M.A., 2003. Production of alpha amylase by Bacillus licheniformis using an economical medium. Bioresour. Technol. 87, 57–61. Hebeda, R.E., Bowles, L.K., Teague, W.M., 1991. Use of intermediate temperature stability enzymes for retarding staling in baked goods. Cereal Foods World 36, 619–624. Humphrey, A., 1998. Shake flask to fermenter: What have we learnt? Biotechnol. Prog. 14, 3–7.

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