Cyclodextrin

International Journal of Scientific & Engineering Research, Volume 4, Issue 12, December-2013 372 ISSN 2229-5518

An innovative approach to biotransformation of benzaldehyde to L-PAC via free cells of Saccharomyces cerevisae in the presence of β- Cyclodextrin

T. F. Adepoju1*, S.K. Layokun2, Ojediran, J. O3, Charles, O4

1Chemical Engineering Department, Landmark University, Omu-aran, P.M.B. 1001, Kwara State, Nigeria

2Chemical Engineering Department, Obafemi Awolowo University, Ile-Ife, Osun State, P.M.B, 2200055, Nigeria

3Agric&Biosystem Engineering Department, Landmark University, Omu-aran, P.M.B.1001, Kwara State, Nigeria

4Biological Sciences Department, Landmark University, Omu-aran, P.M.B. 1001, Kwara State, Nigeria

*Address of Corresponding Author: Chemical Engineering Department, Landmark University, Omu-aran,

P.M.B. 1001, Kwara State, Nigeria.

Email: [email protected], Tel: +234-803-9404673, Fax: +234 (36) 232401

…………………………………………………………………………………………………………………………………

Abstract- Response surface methodology (RSM) was employed to optimize L-Phenylacetylcarbinol (L-PAC) production form biotransformation of benzaldehyde via free cell of Saccharomyces cerevisae presence Beta- Cyclodextrin in this work. Specifically, response surface methodology was applied, and the effect of five variables, viz. cell weight, incubation time, acetaldehyde conc., benzaldehyde conc. and β-CD level and their reciprocal were determined.IJSER Central composite rotatable design was used to generate 50 individual experiments, which was designed to study the effects of these factors during biotransformation of benzaldehyde to L-PAC. A statistical model predicted the highest biotransformation yield of L-PAC to be 586.938 (mg/100 ml) at the following optimized variables conditions: cell weight of 5.17 g (wet. wt.), incubation time of 74.82 min, acetaldehyde conc. of 1594.05 (µg/100 ml), benzaldehyde conc. of 1300 (mg/100 ml) and β- CD level of 3.20 %. Using these variables under experimental condition in three independent replicates, an actual L-PAC yield of 587.00 (mg/100 ml) was obtained. The physical properties of the produced L-PAC suggested that its could serve as a key intermediate for the synthesis of L-ephedrine, pseudoephedrine, norephedrine, nor-pseudoephedrine as well as adrenaline, amphetamine, methamphetamine, phenylpropanolamine and phenylamine.

Keywords: Biotransformation, Saccharomyces cerevisae, optimization, Response surface methodology, L- PAC.

…………………………………………………………………………………………………………………………………

1.0 Introduction 1-hydroxy-1-phenyl-2-propanone or 1-

hydroxy-1-phenylacetone or α-hyroxybenzyl

methyl ketone also known as L- al., 1988). Biotransformation of benzaldehyde to

Phenylacetylcarbinol (L-PAC) has a molecular optically L-PAC was first experimented by

formula of C9H10 O2. It performance as a key Neuberg and Lieberman (1921) and the demand

intermediate for the synthesis of L-ephedrine, for industrial application of this process came

pseudoephedrine,norephedrine,norpseudoephedr- about when the chemical synthesis of ephedrine ne as well as adrenaline, amphetamine, using 1-acetyl phenyl carbinol was patented.

methamphetamine, phenylpropanolamine and Meanwhile, almost all the literature

phenylamine (Ellaiah and Krishna, 1988; Shukla concerning the synthesis of L-PAC and benzyl

and Kulkarni, 2002). alcohol by fermenting yeast deals with yield

optimization by free cells (Agrawal et al., 1986;

• Adepoju T.F is currently pursuing Cardillo et al., 1991; Zeeman et al., 1992). Studies master degree program in Chemical Engineering at Obafemi Awolowo revealed that the formation of L-PAC from University, Nigeria. He is a Lecturer in the department of Chemical benzaldehyde under normal fermentative Engineering, Landmark University, Email: [email protected] conditions using yeast, shows that the quantitative

conversion of benzaldehyde into L-PAC has never • S. K. Layokun is a professor in the DepartmentIJSER of Chemical Engineering, been achieved because of formation of by-products Obafemi Awolowo University, Nigeria. like benzyl alcohol, PAC-diol (Smith and Hendlin, • Ojediran O.J is a senior Lecturer from the Agric & Biosystem Engineering 1953; Gupta et al., 1979; Netraval and Vojtisek, Department, Landmark University 1982; Agrawal and Basu, 1989). The yeast cannot • C. Okolie is Lecturer in biological Sciences Department, Landmark be used for multiple batches because of the toxic University, Nigeria and inhibitory effects of substrate and products

L-PAC can be produced by chemical (Long et al., 1989; Coughlin et al., 1991).

synthesis from cyanohydrins, but the The use of cyclodextrin always decreased

biotransformation route for its production from the toxicity of benzaldehyde for bioconversion

benzaldehyde is preferred industrially (Brusse et using immobilized cells has been reported

(Coughlin et al., 1991; Mahmoud et al., 1990). In Kulkarni (2000) worked on L-PAC: biosynthesis

view of these, Vilas et al., 2002, worked on the and industrial application. Vrsalovic et al. (2006)

effect of addition of b -cyclodextrin on carried out research on modeling of transformation

biotransformation of benzaldehyde to L-PAC by processes using numerical method and the process

the cells of Torulaspora delbrueckii in order to was optimized using the Nelder-Mead algorithm.

increase the optimum yield of L-PAC. Agrwal et The numerical values of the parameters were

al., 1986, worked on the production of L-Acetyl evaluated by fitting the model to the experimental

Phenyl Carbinol by yeast employing benzaldehyde data with the “Scientist” software. The model

as precursor and the results was reported to be differential equations were solved numerically by

acceptable except that the experiment was not the fourth order Runge-Kutta algorithm, which is

optimized. also offered in the same software. The results

Production of phenyl acetyl carbinol by obtained were good except the complexity in the

yeast was carried out by Gupta et al., 1978, but no optimization steps. In this work, biotransformation

report was available showing high yields of L-PAC of benzaldehyde to L-PAC was carried out via the production by this IJSERmechanism. Biotransformation use of free cells of Saccharomyces cerevisiae. To of benzaldehyde to L-phenylacetylcarbinol (L- optimize the biotransformation conditions for the

PAC) by Torulaspora delbrueckii and conversion to production on L-PAC, RSM was applied to

ephedrine by microwave radiation was reported determine the effects of five -level-five factors and

by Vilas et al. (2002). The results obtained were their reciprocal interactions on the yield of L-PAC.

good, except the process condition was not

optimized. Shukla and Kulkarni (2001) worked on 2.0 Material and Methods

the process parameters and reusability of the free 2.1 Materials

cell mass of Torulaspora delbrueckii for the All the chemicals (diethyl ether, anhydrous sodium

production of L-PAC without optimization using sulphate, benzaldehyde, acetyladehyde, b-

statistical approach. In the same vein, Shukla and

cyclodextrin ((b- CD) etc.) used were of analytical 2.2.4 Biotransformation of benzaldehyde to L-PAC

grade and need no further purification. 100 ml of biotransformation medium

2.2 Methods containing 5% glucose, 0.6% peptone and had pH

2.2.1 Microorganisms 4.5 was inoculated with a known weight of cell

Saccharomyces cerevisae used in this study was mass (biomass) obtained. The reactor was

isolated locally. The culture was consistently incubated on a shaker at 30 oC and 240 rpm at

maintained on a medium containing 0.4% different time range for adaptation of cells to the

dextrose, 1% yeast extract, 1% malt extract, and 2% medium. Benzaldehyde and acetaldehyde was agar at pH 7.2 ( Agarwal et al., 1986). added and flasks were incubated again for the

2.2.2 The growth medium biotransformation on a shaker at 30 oC and 240

The growth medium for Saccharomyces cerevisae rpm.

(Long et al., 1989) contained glucose 2%, peptone 2.2.5 Effect of b-cyclodextrin addition on

2%, yeast extract 1% and had pH 5.5. biotransformation of benzaldehyde

2.2.3 Culture growth Effect of 0.4 – 1.6% β-cyclodextrin (b-CD)

1 ml suspension of cells of the isolate Saccharomyces was studied at benzaldehyde and acetaldehyde

IJSER6 cerevisae containing 10 cells was inoculated into 9 levels ranging from 500 mg to 1600 mg/100 ml and

ml of growth medium and incubated on a rotary 400 µl to 1300 µl/100 ml, respectively. The reaction

shaker at 30 ± 2oC at 240 rpm for 24 h. The obtained was allowed to take place for 3 h at 30 ± 2oC and

culture was inoculated into 100 ml of the same 240 rpm. Semi-continuous feeding of different

medium and allowed to grow for 24 h. Under the levels of benzaldehyde and acetaldehyde was also

same conditions, cells were harvested by carried out according to design software (Table 1)

centrifuging at 10, 000 rpm for 15 min at 15 oC. The at different intervals in presence of β -CD.

biomass obtained was washed with water, 2.3 Analysis of biotransformation products

centrifuged and was used for biotransformation Once biotransformation, the medium was

studies. centrifuged at 10,000 rpm for 15 min. The

supernatant were extracted three times with equal L-PAC. Five-level-five-factors design was applied,

volumes of diethylether. The combined extract was which generate 50 experimental runs. This

dried over anhydrous sodium sulphate and included 32 factorial points, 10 axial points, and 8

concentrated over a temperature controlled water central points to provide information regarding the

bath. The residue obtained was dissolved in interior of the experimental region, making it

methanol and subjected to gas chromatography possible to evaluate the curvature effect. Selected

(GC) analysis. factors for biotransformation of benzaldehyde to L-

2.4 Gas Chromatography Analysis PAC were; cell weight g (wet. wt): X1, incubation

The conditions used for GC analysis were time (min): X 2, Acetaldehyde conc. (mg/100 ml):

as follows- GC model used was Chemito-8510 with X3, benzaldehyde conc. (mg/100 ml): X4 and β-CD

Oracle -1 computing integrator. A 4 meter long level (%): X5. Table 1 show the independent factors

column of 5% OV-17 was used. The injector and their five levels for Central Composite design,

temperature and detector temperature (FID) was and the combinations of five independent factors

maintained at 250 oC. Column programming was in a Central Composite experimental design.

as follows: 75 oC for 3 min, then 10 oC/ 1 min up to Depicted in Table 2 also are the L-PAC

o IJSER 250 C and holding time was for 5 min. Retention yields, the predicted yields and the residual values.

times of L-PAC was 17 min. The concentration of The effects of unexplained variability in the L-PAC

the compound was determined using peak area yield response due to extraneous factors were

method (Shukla and Kulkarni, 1999). The minimized by randomizing the order of

experiment was replicated in triplicate until it was experiments.

found to be reproducible within ± 3 percent limits. Table 1: Factors and their Levels for Composite Central Design 2.5 Experimental design Variab Sym Central Composite Rotatable Design le bol Coded factor levels -2 -1 0 1 2 (CCRD) experimental design was employed to CW X1 2 3 4 5 6 IT X2 40 50 60 70 80 optimize the biotransformation of benzaldehyde to AC X3 400 700 1000 1300 1600

BC X4 500 700 900 1100 1300 31 -1 1 1 1 1 574.00 574.04 -0.044 ß-CD X5 0.4 0.8 1.2 1.6 3.2 32 1 1 1 1 1 585.00 585.03 -0.027 level (%) 33 -2 0 0 0 0 345.00 345.61 -0.61 CW= Cell weight g (wet. wt), IT= Incubation time 34 2 0 0 0 0 369.00 368.46 0.54 (min), AC= Acetaldehyde conc. (µg/100 ml), BC= 35 0 -2 0 0 0 305.00 305.10 -0.097 Benzaldehyde conc. (mg/100 ml) 36 0 2 0 0 0 341.00 340.97 0.033

Table 2: Experimental design matrix by central 37 0 0 -2 0 0 277.00 276.49 0.51 composite rotatable design (CCRD) for five-level- 38 0 0 2 0 0 339.00 339.58 -0.58 five-factors response surface study 39 0 0 0 -2 0 216.00 216.09 -0.086 SR X1 X2 X3 X4 X5 L-PAC Pv Res. 40 0 0 0 2 0 370.00 369.98 0.022 1 -1 -1 -1 -1 -1 212.00 211.89 0.11 41 0 0 0 0 -2 52.00 52.14 -0.14 2 1 -1 -1 -1 -1 220.00 220.12 -0.12 42 0 0 0 0 2 664.00 663.92 0.079 3 -1 1 -1 -1 -1 211.00 210.72 0.28 43 0 0 0 0 0 386.00 386.51 -0.51 4 1 1 -1 -1 -1 210.00 210.33 -0.33 5 -1 -1 1 -1 -1 209.00 209.04 -0.038 44 0 0 0 0 0 387.00 386.51 0.49 6 1 -1 1 -1 -1 213.00 212.90 0.10 45 0 0 0 0 0 386.00 386.51 -0.51 7 -1 1 1 -1 -1 211.00 210.74 0.26 46 0 0 0 0 0 387.00 386.51 0.49 8 1 1 1 -1 -1 206.00 205.98 0.022 9 -1 -1 -1 1 -1 205.00 205.22 -0.22 47 0 0 0 0 0 386.00 386.51 -0.51 10 1 -1 -1 1 -1 206.00 205.57 0.43 48 0 0 0 0 0 387.00 386.51 0.49 11 -1 1 -1 1 -1 205.00 205.42 -0.42 49 0 0 0 0 0 386.00 386.51 -0.51 12 1 1 -1 1 -1 197.00 197.16 -0.16 50 0 0 0 0 0 387.00 386.51 0.49 13 -1 -1 1 1 -1 201.00 200.49 0.51 PV=predicted value (mg/100 ml), Res. = Residual, SR= Standard Runs 14 1 -1 1 1 -1 196.00 196.47 -0.47 2.5.1 Statistical Data Analysis 15 -1 1 1 IJSER1 -1 204.00 203.57 0.43 16 1 1 1 1 -1 191.00 190.93 0.068 The data obtained from biotransformation 17 -1 -1 -1 -1 1 332.00 332.23 -0.23 of benzaldehyde to L-PAC was analysed 18 1 -1 -1 -1 1 364.00 364.09 -0.091 19 -1 1 -1 -1 1 368.00 367.94 0.060 statistically using response surface methodology 20 1 1 -1 -1 1 391.00 391.17 -0.17 (CCRD), so as to fit the quadratic polynomial 21 -1 -1 1 -1 1 392.00 391.51 0.49 22 1 -1 1 -1 1 419.00 418.99 0.01 equation generated by the Design-Expert software 23 -1 1 1 -1 1 430.00 430.09 -0.091 version 8.0.3.1 (Stat-Ease Inc., Minneapolis, USA). 24 1 1 1 -1 1 449.00 448.95 0.051

25 -1 -1 -1 1 1 477.00 476.69 0.31 To correlate the response variable to the 26 1 -1 -1 1 1 500.00 500.67 -0.67 27 -1 1 -1 1 1 514.00 513.77 0.23 independent variables, multiple regressions was 28 1 1 -1 1 1 529.00 529.13 -0.13 used to fit the coefficient of the polynomial model 29 -1 -1 1 1 1 534.00 534.09 -0.087 30 1 -1 1 1 1 554.00 553.70 0.30 of the response. The quality of the fit of the model

was evaluated using test of significance and remarkably significant and have very strong effects

analysis of variance (ANOVA). The fitted on the L-PAC yield witt p< 0.05 (Table 3).

quadratic response model is described by Eqn 1: Nevertheless, the linear term X5 with F-

value of 3.61x106 and p-value of <0.0001, was the = + 푘 + 푘 + 푘 + (1) 2 0 푖 푖 푖푖 푖 푖푗 푖 푗 most significant model term. In order to minimize 푌 푏 � 푏 푋 � 푏 푋 � 푏 푋 푋 푒 푖=1 푖=1 푖<푗 Where: Y is L-PAC yield (response factor), bo is the error, all the coefficients were considered in the

intercept value, bi (i= 1, 2,……… k) is the first order design. The results of the second-order response

model coefficient, bij is the interaction effect, and surface model fitting in the form of ANOVA are

bii represents the quadratic coefficients of Xi, and e presented in Table 4. The model F-value (terms is the random error. used to estimate effects) of 2.156 x105 with low p- 3.0 Results and Discussion value (<0.0001) implied a high significance for the Table 2 shows the coded factors regression model (Yuan et al., 2008). The goodness considered in this study with L-PAC yield, of fit of the model was checked by the coefficient of predicted value as well as the residual values determination (R2). R2 should be at least 0.80 for the obtained. Design Expert 8.0.3.1 software was good fit of a model (Guan and Yao, 2008). In this employed to evaluate and determine the IJSER2 case, the R value of 1.00 indicated that the sample coefficients of the full regression model equation variation of 100% for the L-PAC production is and their statistical significance. Table 3 described attributed to the independent factors (cell weight, the results of test of significance for every incubation time, acetaldehyde conc., benzaldehyde regression coefficient. Considering the large F- conc. and β-CD level). The value of the adjusted values (the test for comparing the variance determination coefficient (Adj. R2 of 1.00) was also associated with all terms with the residual identical, supporting a high significance of the variance) and low corresponding p-values (the model (Akhnazarova and Kefarov, 1982; Khuri and probability value that is associated with the F - Cornell, 1987) and all p-values were less than 0.05, value for all terms), all the model terms are implying that the model proved suitable for the

adequate representation of the actual relationship in Table 5. The low values of standard error

among the selected factors. The lack-of-fit term of observed in the intercept and all the model terms

0.8317 was not significant relative to the pure error. showed that the regression model fits the data

In this case, a non-significant lack of fit is good. well, and the prediction is good (Table 5). The

Hence, the model could be used in theoretical variance inflation factor (VIF) obtained in this

prediction of the L-PAC production. The study showed that the 8-centre points are

developed regression model equation describing orthogonal to all other factors in the model. The

the relationship between the L-PAC yield (Y) and model also proved suitable for the adequate

the coded values of independent factors of cell representation of the real relationship among the

weight (X1), incubation time (X2), acetaldehyde selected independent factors.

conc. (X3), benzaldehyde (X4) and β-CD level (X5) Usually, the three-dimensional (3D) and their respective interactions is described in Eq. response surface plots are graphical (2). representations of the regression equation for the ( 100 ) = 386.51 + 4.80 + 7.54 optimization of the reaction variables, and they are 푌 푚푔⁄ 푚푙 + 13.26 + 32푥.135 + 128푥2 .61 2.16 푥3 1.09 푥4 1.97 푥5 represented in Figure 2. The curvatures’ nature of +IJSER 5.91 1 2 + 0.72 1 3+ 0.34 1 4 − 푥 푥 − 푥 푥 − 푥 푥 3D surfaces in Figure 2a, b, e, f, and h suggested + 9.22푥1푥5 0.47푥2푥3 푥2푥4 + 15.532 5 + 37.783 4 5.21 푥 푥 − 푥 푥 reciprocal interaction of cell weight with 2 11.22 3 5 13.87 4 165 .52 1 푥 푥 푥 푥 − 푥 2 2 2 incubation time, cell weight with acetaldehyde − 5.03 푥 2 − 푥 3 (2)− 푥4 2 5 − 푥 conc., incubation time with acetaldehyde conc.,

Where Y= ( 100 ) incubation time with benzaldehyde conc. and

All퐿 −negative푃퐴퐶 푦푖푒푙푑 and푚푔 positive⁄ 푚푙 values in the acetaldehyde conc. with benzaldehyde conc.,

equation shows that the variables have negative respectively. On the other hand, the nature of

and positive effect on the yield of L-PAC curvatures’ of 3D surfaces in Figure 2c, d, g, i, j

production, respectively. The model coefficients indicated moderate interactions of cell weight

and probability values i.e. coded value are shown with benzaldehyde conc., cell weight with β-CD

level, incubation time with β-CD level, were found to be 170 ± 2 and 251± 2 0C, acetaldehyde conc. with β-CD level, and respectively. benzaldehyde conc. with β-CD level, respectively. Table 3: Test of significance for all regression coefficient terms The optimal values of the independent Sourc SS df MS F-value p-value e factors selected for the biotransformation of X1 999.64 1 999.64 5031.47 <0.0001 benzaldehyde to L-PAC were obtained by solving X2 2463.02 1 2463.02 12397.0 <0.0001 9 the regression equation (Equation. 2) using the X3 7618.98 1 7618.98 38348.5 <0.0001 1 Design-Expert software package. The optimal X4 45333.7 1 45333.7 2.282x <0.0001 7 7 105 conditions for this process were statistically X5 7.164x 1 7.164x 3.61x <0.0001 105 105 106 predicted as X1 = 5.17 g (wet. wt.), X2 = 74.82 (min), X1X2 148.78 1 148.78 748.86 <0.0001 X1X3 38.28 1 38.28 192.68 <0.0001 X3 = 1594.05 (µl/100 ml), X4 = 1300 (ml/100 ml) and X1X4 124.03 1 124.03 624.28 <0.0001 X1X5 1116.28 1 1116.28 5618.56 <0.0001 X5 = 3.20 %. The predicted L-PAC yield under the X2X3 16.53 1 16.53 83.21 <0.0001 X2X4 3.78 1 3.78 19.03 <0.0001 above set conditions was 586.938 (mg/100 ml). In X2X5 2719.53 1 2719.53 13688.1 <0.0001 8 order to verify the prediction of the model, the X3X4 7.03 1 7.03 35.39 <0.0001 X3X5 7719.03 1 7719.03 38852.1 <0.0001 optimal conditions were applied to three 0 X4X5 45677.5 1 45677.5 2.299x <0.0001 IJSER 5 independent replicates, and the average L-PAC 3 3 10 2 X1 1508.47 1 1508.47 7592.59 <0.0001 yield obtained was 587.00 (mg/100 ml), which is

2 X2 6996.22 1 6996.22 35213.9 <0.0001 well within the predicted value for the model 8

2 10693.6 1 10693.6 53824.1 <0.0001 equation. X3 3 3 2

2 X4 15172.4 1 15172.4 76367.4 <0.0001 Qualities of L-PAC 8 8 6

2 1407.85 1 1407.85 7086.11 <0.0001 In order to ascertain the quality of the L- X5

PAC produced, the physical appearance was found SS= Sum of Square, MS= mean square

to be in powder form, the density was determined Table 4: Analysis of variance (ANOVA) of regression equation to be 1.115 g/cm3, the melting and boiling points Sum of d Mean F- p-value Source Squares f Square value

2 Model 5.568 x 2 42838. 2.156 <0.0001 X5 -5.03 1 0.060 -5.16 -4.91 1.05 105 0 92 x 105

Residu 5.76 2 0.20 al 9 Lack 3.76 2 0.17 0.60 0.8317

of fit 2 Predicted vs. Actual

Pure 2.00 7 0.29 700.00 error 600.00

Cor 8.568 x 4 500.00 5 total 10 9 400.00 44 2 2 R = 100% R (adj.) = 100% Std. Dev. = 300.00 Predicted 0.45 Mean = 341.58 C.V. % = 0.13 200.00

100.00 Table 5: Regression coefficients and significance 0.00 of response surface quadratic 0.00 100.00 200.00 300.00 400.00 500.00 600.00 700.00

Fact. CE df Standard 95% CI 95% VIF Actual

error Low CI

high

Interce 386.51 1 0.16 386.19 386.83 - 580 X1 4.80 1 0.068 4.67 4.94 1.00 570

560 X2 7.54 1 0.068 7.40 7.68 1.00 550 540 X3 13.26 1 0.068 13.12 13.12 1.00 530 520 X4 32.35 1 0.068 32.21 32.21 1.00 L-PAC (mg/100 L-PAC ml)

X5 128.61 1 0.068 128.47 128.75 1.00 1.00 1.00 0.60 0.50 0.20 IJSER 0.00 -0.20 X1X2 -2.16 1 0.079 -2.32 -2.00 1.00 Incubation time (min) -0.60 -0.50 Cell weight (wet .wt) -1.00 -1.00 X1X3 -1.09 1 0.079 -1.25 -0.93 1.00 (a) X1X4 -1.97 1 0.079 -2.13 -1.81 1.00

1 5 X X 5.91 1 0.079 5.75 6.07 1.00

X2X3 0.72 1 0.079 0.56 0.88 1.00 210.745 X2X4 0.34 1 0.079 0.18 0.50 1.00 230

X2X5 9.22 1 0.079 9.06 9.38 1.00 224

X3X4 -0.47 1 0.079 -0.63 -0.31 1.00 218

X3X5 15.53 1 0.079 15.37 15.69 1.00 212

X4X5 37.78 1 0.079 37.62 37.94 1.00 206 2 X1 -5.21 1 0.060 -5.33 -5.09 1.05 200

(mg/100 L-PAC ml)

-1.00 2 -11.22 1 0.060 -11.34 -11.10 1.05 -1.00 X2 -0.50 -0.50

0.00 0.00

0.50 0.50 2 etaldehyde conc. (µg/100 ml) Cell weight (wet .wt) X3 -13.87 1 0.060 -13.99 -13.75 1.05 1.00 1.00

2 X4 -16.52 1 0.060 -16.65 -16.40 1.05 (b)

240

230 230

220 222

210 214

200 206

198 190 L-PAC (mg/100 L-PAC ml) 190

L-PAC (mg/100 L-PAC ml) 1.00 0.50 -1.00 -1.00 -1.00 -0.50 0.00 0.00 -0.50 -0.50 cubation time (min) -0.50 0.50 0.00 0.00 -1.00 1.00 Benzaldehyde conc. (mg/100 ml) 0.50 0.50 aldehyde conc. (mg/100 ml) Cell weight (wet .wt) 1.00 1.00 (f)

(c)

600 600

500 500

400 400

300 300

200 200 L-PAC (mg/100 L-PAC ml) L-PAC (mg/100 L-PAC ml)

1.00 1.00 0.50 0.50 1.00 1.00 0.00 0.00 0.50 0.60 0.20 -0.50 -0.50 0.00 ß- CD l evel ( %) Cell weight (wet .wt) -0.20 -1.00 -1.00 ß- CD l evel ( %) -0.50 -0.60 Incubation time (min) -1.00 -1.00

(d) IJSER

(g)

210.745 240

230 210.745 220 245

210 234

200 223

190 212 L-PAC (mg/100 L-PAC ml)

201 1.00 0.50 -1.00 -0.50 190 0.00 0.00 L-PAC (mg/100 L-PAC ml) ncubation time (min) -0.50 0.50 -1.00 1.00 Acetaldehyde conc. (µg/100 ml) -1.00 -1.00 -0.50 -0.50 (e) 0.00 0.00 0.50 Acetaldehyde 0.50 conc. (µg/100 ml) nzaldehyde conc. (mg/100 ml) 1.00 1.00

(h)

Beta- Cyclodetrin, indicate that RSM is a good 450

400 210.745 optimization tools for L-PAC production. The

350

statistical model predicted that the optimal 300

250 conditions for the selected biotransformation 200

L-PAC (mg/100 L-PAC ml) variables as cell weight of 5.17 g (wet. wt),

-1.00 1.00 -0.50 0.50 incubation time of 74.82 min, acetaldehyde conc. of 0.00 0.00 dehyde conc. (µg/100 ml) 0.50 -0.50 ß- CD l evel ( %) 1.00 -1.00 1594.05 (µl/100 ml), benzaldehyde conc. of 1300

(ml/100 ml) and β-CD level of 3.20 % with an (i)

actual L-PAC yield of 587.00 (mg/100 ml). Hence, 210.745 600 this work established the usefulness of RSM for the

500

400 optimum biotransformation of benzaldehyde to L-

300 PAC and also the quality of L-PAC produced

200

L-PAC (mg/100 L-PAC ml) suggested that it could be used effectively as

-1.00 1.00 -0.50 precursor for the production of L-ephedrine and 0.50 0.00 0.00 dehyde conc. (mg/100 ml) 0.50 -0.50 D-pseudoephedrine. 1.00 -1.00 ß- CD l evel ( %) IJSER

(j)

Figure 2: The curvatures’ nature of 3D surfaces Acknowledgement

Conclusions The Authors acknowledge the effort of the technical staff of biology and chemistry The results obtained in this study using laboratories of Landmark University. The effort of response surface methodology to determine the Chief Technology of ABU, Zaria is highly

effects of five reaction variables, namely, cell appreciated.

weight, incubation time, acetaldehyde conc., References benzaldehyde conc. and β-CD level on Agarwal S.C., Basu, S.K., Vora, V.C, Mason, J.R.

biotransformation of benzaldehyde to L-PAC yield Pirt, S.J. (1986). Studies on the production of Acetyl

via free cells Saccharomyces cerevisae presence of Phenyl Carbinol by yeast Employing

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