optimization of natural fermentative medium for selenium-enriched

8/3/2019 Optimization of Natural Fermentative Medium for Selenium-Enriched

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Optimization of natural fermentative medium for selenium-enrichedyeast by D-optimal mixture design

Hongfei Yin, Zhigang Chen, Zhenxin Gu*, Yongbin Han

College of Food Science & Technology, Nanjing Agricultural University, Nanjing 210095, PR China

a r t i c l e i n f o

Article history:

Received 13 September 2007

Received in revised form 7 April 2008

Accepted 9 April 2008

Keywords:

Yeast

Se

Medium optimization

D-optimal mixture design

a b s t r a c t

Natural fermentative medium for selenium-enriched yeast (Saccharomyces cerevisiae) culture was in-vestigated using response surface methodology (RSM). The medium with a concentration of 15mg/mL

Na2SeO3, contained various ratios of juices from germinated brown rice (0.40w 0.80, 12 Brix), beerwort(0.10w0.50, 12 Brix) and soybean sprout (0.10w0.50, 12 Brix), which were optimized by applying D-

optimal mixture design (DMD). The effects of their ratios on biomass yield and total selenium (Se) yieldwere analyzed. The results showed that when the mixed ratio of the components was 4:4:2 (v:v:v), the

maximum value of biomass yield and total Se yield were 8.5 g/L and 3.53 mg/L, respectively. Verificationexperimental trials were performed for validating the models, and it indicated that the above mixture of

these natural materials can be used as proper medium for the growth of selenium-enriched yeast andaccumulation of Se. 2008 Swiss Society of Food Science and Technology. Published by Elsevier Ltd. All rights reserved.

1. Introduction

The trace element selenium (Se) is an essential nutrient for thegrowth of animals and humans. This has become increasingly ob-vious as new researches have shown a hitherto unsuspected role

for this element to human health (Neve, 1998; Zheng & Ouyang,2001). It is shown that Se has a cancer protective effect (Chen,Zhang, Hou, & Chai, 1999; Clark et al., 1996; Combs, 1997; Kleinet al., 2003) and a profound effect on survival of HIV infected pa-

tients (Bologna et al., 1994). It is generally believed that theingestion of organic Se compounds is better and safer than thatcontained inorganic Se. A variety of selenium-enriched biologicalderivatives, such as garlic (Yang, Wang, & Li, 1993) and broccoli

(Davis, Zeng, & Finley, 2002) have been developed as dietsupplements.

It is known that some microorganisms (Chasteen & Bentley,

2003), mainly yeast, can utilize soluble sugars and organic acids,producing biomass with high protein content and meanwhiletransform inorganic Se (low bioavailability, potentially toxic) intoorganic form (safer and highly bioactive). The Se supplementationusing microorganisms has received much attention in recent years.

Previous works have shown that yeast was a good carrier for Sebiotransformation (Chanda & Chakrabatri, 1996; Choi et al., 2002).Hence, one of the most economic sources of organic Se is yeastgrown in selenium-enriched medium. However, most previous

works on Se enrichment of yeast were carried out in biochemical

medium and simplex nutrition inhibited growth of the cell. Thuslow yield of biomass and conversion rate of inorganic Se weremajor obstacles to the successful commercialization of this organ-ism in the health food industry (Demirci, Pometto, & Cox, 1999;

Suhajda, Hegoczki, Janzso, Pais, & Vereczkey, 2000). Moreover, theproportion of organic Se in cells was still little explored while totalSe content was more concerned.

Response surface methodology (RSM) is a collection of mathe-

matical and statistical techniques useful for designing experiments,building models and analyzing the effects of several independentfactors (Garrido-Vidal, Pizarro, & Gonzalez-Saiz, 2003; Li & Fu,2005). The main advantage of RSM is the reduced number of ex-

perimental trials needed to evaluate multiple factors and their in-teractions. Also, study of the individual and interactive effects ofthese factors will be helpful in effort to find the target value. Hence,

RSM provides an effective tool for investigating the aspects af-fecting the desired response if there are many factors and in-teractions in the experiment. To optimize the process, RSM can beemployed to determine a suitable polynomial equation for de-scribing the response surface.

D-optimal mixture design (DMD) is an effective technique of

RSM for optimizing complex processes. It is widely used in opti-mizing the culture medium (Caroline, Marina, Ricardo, & Hector,2007). The basic theoretical and fundamental aspects of DMD havebeen reviewed (Cornell, 1990; Kowalsky, Cornell, & Vining, 2000,

2002). In this design, the total amount of the components is heldconstant when proportions of the mixture components change.Several approaches have been presented to deal with problems that

* Corresponding author. Tel./fax: 86 25 8439 6293.

E-mail address: [email protected] (Z. Gu).

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0023-6438/$34.00 2008 Swiss Society of Food Science and Technology. Published by Elsevier Ltd. All rights reserved.doi:10.1016/j.lwt.2008.04.002

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involve mixtures (Dingstad, Egelandsdal, & Naes, 2003; Omer &Sukru, 2006), and mixtures of two or more major components

(categories or factors), each of which may be a mixture of one ormore minor components (Piepel, 1999).

In this study, germinated brown rice juice, beerwort and sprout

soybean juice were used as natural medium components to pro-duce selenium-enriched yeast. The DMD was applied to optimizethe composition of culture medium, find the most significant factoraffecting biomass yield and total Se yield, and establish a quadratic

polynomial regression model, so that to provide scientific basis forindustrialization.

2. Materials and methods

2.1. Materials

Yeast (Saccharomyces cerevisiae) was obtained from fermen-tation with a concentration of 15 mg/mL Na2SeO3 by comparingthe selenium-enrichment ability of 17 strains, which were chosen

by resistance screening with a concentration of 50 mg/mLNa2SeO3.

Na2SeO3 purchased from Sigma was of analytical grade. Na2SeO3standard solution was purchased from Jiangsu center for diseasecontrol and prevention. All other chemicals used in this work werealso from commercial sources. Germinated brown rice, malt andsoybean sprout were bought from the local market.

2.2. Fermentative medium preparation

2.2.1. Preparation of germinated brown rice juice

Germinated brown rice was pulverized and then added withdeionized water to reach a ratio of 1:4 (w/v). Initial pH value wasadjusted to 4.0 by citric acid. The mixture was gelatinized (90 C,

30 min), liquefied (60 C, 1 h) by adding glucoamylase (1.25 g/L,100,000 U/g) and then homogenized through the colloid mill twice(30 MPa). For further saccharification, the mixture was incubated at

60 C for 2 h by adding the same amount of glucoamylase. Germi-nated brown rice juice was obtained by centrifugation (1900g,5 min) and the soluble solid was adjusted to 12 Brix.

2.2.2. Preparation of beerwort

Malt was pulverized and four volumes of deionized water wereadded to the powder. The mixture was kept at 37 C for 30 min, at50 C for 1 h and at 65 C for 3 h in turn. The saccharified substancewas boiled for5 min and then refrigerated at 4 C for 12 h. Beerwort

was obtained by centrifugation (1900g, 5 min) and the soluble solidwas adjusted to 12 Brix.

2.2.3. Preparation of soybean sprout juice

Soybean sprout was boiled with deionized water at a ratio of 1:4

(w/v) to deactivate its enzymes, and then wet-milled twice(30 MPa). Soybean sprout juice was obtained by centrifugation

(1900g, 5 min) and the soluble solid was adjusted to 2 Brix.Several main nutritional characteristics of three different

culture components were shown in Table 1.

2.3. Fermentation conditions

Yeast cells were pre-grown aerobically for 24 h in PDB (potato,dextrose, broth) nutrient medium. Fermentative medium was in-oculated with 10% (v/v) seed liquid and then cultivated for 48 h on

a rotary shaker. The starter and fermentative conditions of volume,

temperature and shaking speed were fixed at 50 mL/250 mL,28 0.5 C and 160 rpm, respectively.

Inorganic Se was added to the sterile medium before the start of

yeast cultivation as a solution of Na2SeO3, at a concentration of10 mg/mL. Initial Na2SeO3 concentrations in medium were 0 mg/mLin control and 15 mg/mL in experimental treatments.

2.4. Determination of total Se, inorganic Se and organic Se yield

The yeast cells were obtained by centrifugation (1900g, 10 min).To remove unbound Se, the cells were washed with deionizedwater thoroughly and then centrifugated at 1900g for 10 min. Thecells were dried under vacuum to a constant weight.

The Se determination was carried out according to the hydride

generation atomic fluorescence spectrometry (HG-AFS) methoddescribed by Wu, Jin, Shi, and Bi (2007) with some modifications.The instrumental operating conditions were given in Table 2.

About 0.2 g dried samples were digested (170 C, 0.5 h) with 5 mLof a mixture of concentrated HNO3, HClO4 and H2SO4(v:v:v 10:4:5) in a digestive flask. Se (6) was reduced to Se(4) by addition of 1 mL concentrated HCl. To avoid the volatil-ization loss of Se, a reflux equipment was employed during di-

gestion process.After digesting, the solution was cooled and made a constant

volume with ultra-pure water. The blank was digested in thesame way. The digested product was used for total Se de-

termination. For inorganic Se determination, the biomass mixedwith ultra-pure water was extracted in boiling bath for 1 h and

made a constant volume. Then the mixture was centrifugated at8300g for 15 min. The supernatant liquor was filtrated and the

filtrate could be analyzed directly. Organic Se yield was calculatedfrom the difference between the total Se yield and inorganic Seyield.

Table 1

Main nutritional characteristics of different culture components

Nutritional

characteristics

Germinated brown

rice juice

Beerwort Soybean sprout

juice

Total sugar (g/L) 112.5 0.2 105.0 1.4 2.6 0.1

Reducing sugar (g/L) 105.5 1.8 70.4 0.1 2.0 0.1

Soluble protein (mg/mL) 1646.6 43.7 923.1 21.4 1472.3 28.6

Free amino acid (mg/mL) 94.1 3.3 449.3 17. 6 350. 4 42.7

Table 2

Instrumental operating conditions for HG-AFS

Parameters Value

High voltage of PMT (V) 300

Lamp current (mA) 80

Atomizer temperature (C) 200

Atomizer height (mm) 8

Gas type Argon

Carrier gas flow rate (mL/min) 400Shield gas flow rate (mL/min) 900

Injection volume (mL) 2

Dwell time (s) 1

Read time (s) 10Read method Peak area

Measurement method Stand curve

Table 3

Independent variables and their coded and actual levels used for optimization in D-

optimal mixture design experiment

Variable factors Symbol Proportional level

1 2/3 1/2 1/3 1/6 0

Germinated brown

rice juice

X1 0.80 0.67 0.60 0.53 0.47 0.40

Beerwort X2 0.50 0.37 0.30 0.23 0.17 0.10

Soybean sprout juice X3 0.50 0.37 0.30 0.23 0.17 0.10

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2.5. Experimental design

DMD was used to determine the optimum mixture ratio foryeast growth and Se accumulation. The experimental design andstatistical analysis were performed using the software of DesignExpert version 6.0.10 (Stat-Ease, Inc.). A six-level three-factor de-sign was chosen to evaluate the combined effects of three in-

dependent variables, germinated brown rice juice, beerwort andsoybean sprout juice, coded as X1, X2 and X3, respectively. Based onthe preliminary trials, the proportion of the above three materialswas 0.40X10.80, 0.10X2 0.50, and 0.10X3 0.50, re-

spectively (Table 3). The response values were yeast biomass yieldand total Se yield. The design consisted of 14 combinations in-cluding four replicates (trials 11w14) (Table 4). The responsesfunction (Y) of the special cubic model was partitioned into linear,

interactive and cubic components:

Y Xn

j1

bjxj Xh


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The absolute value for the coefficient ofX2 is larger than those ofX1and X3. This indicated that the linear term influence ofX2 was more

significant than those ofX1 and X3. The function was not linear andindicated the importance of interactions among X1, X2 and X3. Thecoefficients ofX1X3 and X2X3 are obviously larger than that of X1X2.This meant that the effects of former two (X1X3, X2X3) combinations

were main factors influencing Se productivity. According to ANOVAshown in Table 6, the obtained model 2 is very significant (P< 0.01).On the basis oft-test and P-values, the interaction between X2 and

X3 is significant (P< 0.01) as well as that between X1 and X3(P< 0.05). However, the interaction between X1 and X2 is not sig-nificant (P> 0.05).

3.2. Response surfaces analyses

To obtain more detailed interrelations and interactions, contour

maps are shown in Figs. 1 and 2 for the effects of the independentvariables on biomass yield and total Se yield. The diagrams describethe variation on the responses as a function of the mixture com-position. Giving an overall curvilinear effect, biomass yield and total

Se yield enhance mainly by an increased ratio of beerwort. A lowerquantity of germinated brown rice juice is better for the growth of

yeast.Although it was noted that the optimum conditions for accu-

mulation of biomass and total Se were slightly different, the cor-relation of their observed values (Table 4) is positive and thecorrelation coefficient is 0.89. Hence, on the basis of medium op-timization evaluated from the model 1 and model 2, the predicted

largest biomass yield and total Se yield were 8.5 g/L and 3.53 mg/L,when the proportion of germinated brown rice juice, beerwort andsoybean sprout juice were 0.4, 0.4 and 0.2, respectively.

The optimum medium of mixed juices could provide more nu-

trition for cells growing and Se producing than a single kind ofmedium and synthetic medium. Firstly, the medium had amplecarbon and nitrogen sources. Secondly, there were plenty of vita-

mins in the optimum mediumwhich were necessary for the growth

of yeast. Brown rice contains more vitamin E and B than the ordi-nary polished rice (Kenichi, Keitaro, Yuji, & Takafumi, 2005). Maltextract had various vitamins, such as biotin, pantothenate, thia-mine, pyridoxine, riboflavin, folic acid, nicotinic acid, etc. Soybean

was rich in ascorbic acid and phytic acid (Mohamed & Rangappa,1992). Moreover, the medium could supply various minerals. Thecontent of Ca, K, P, Mg, Fe, Mn and Zn in germinated brown rice ishigher than in polished. It was showed that the minerals were

beneficialnot only to the growth of yeastbut also to the synthesis oforganic Se in yeast. As Se was a biomass related product, the in-crease of biomass enhance the activity of the most importantselenic enzyme Glutathione Peroxidase (GSH-Px) (Abdel Rahim,

2005; Bayse, Baker, & Ortwine, 2005), which is critical for survivaland function of aerobic organisms because it can effectively inhibitoxidation and prolong life of the organism.

3.3. Verification of model

Within the scopes of the variables investigated in experimental

design, additional experiments with different conditions werecarried out in order to assess the validity of model 1 and model 2.

The arrangement and results of the confirmatory trials were shownin Table 7. The experimental values were found to be reasonablyclose to the predicted ones, which confirmed the validity and ad-equacy of the predicted models. Our observed yield of biomass

(9.86 g/L) and total Se (3.86 mg/L) under the optimal conditionswas higher than that under all the other conditions.

4. Conclusion

The statistical methodology, D-optimal mixture design is dem-onstrated to be effective and reliable in finding the optimal ratio ofcomponents in fermentative medium for selenium-enriched yeast

production. It was showed that when the mixed ratio of germinatedbrown rice juice, beerwort and soybean sprout juice was 4:4:2, the

X1: germinated brown rice juice0.80

X2: beerwort

0.50

X3: soybean sprout juice

0.50

0.10 0.10

0.40

total Seieldm/L

2.75

2.91

2.91

3.07

3.22

3.38

Fig. 2. Contour plot for the effects of germinated brown rice juice (X1), beerwort (X2)

and soybean sprout juice (X3) on total Se yield.

7.3

X1: germinated brown rice juice

0.80

X2: beerwort

0.50

X3: soybean sprout juice

0.50

0.10 0.10

0.40

biomass ield/L

6.6

7.0

7.7

7.7

8.1

7.3

Fig. 1. Contour plot for the effects of germinated brown rice juice (X1), beerwort (X2)and soybean sprout juice (X3) on biomass yield.

H. Yin et al. / LWT - Food Science and Technology 42 (2009) 327331330


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maximum biomass yield and total Se yield were 8.50 g/L and3.53 mg/L respectively. Confirmatory trials suggested that there begood fit degree between the observed values in experiment and the

values predicted by equation. All of these illuminated that themethod and results were feasible and efficacious. The optimummedium obtained in this paper would be expected to be useful onfurther development for functional food and pharmaceuticals.

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Table 7

Arrangement and result of confirmatory trials

Trials Proportion of components Biomass yield (g/L) Total Se yield (mg/L) Proportion of organic Se

X1 X2 X3 Obser ved value P redicted value Observed value Pr edicted value

Optimum medium 0.4 0.4 0.2 9.86 0.06a 8.49 3.86 0.02a 3.89 0.91

Random medium 1 0.4 0.5 0.1 9.86 0.02a 8.34 3.40 0.05b 3.19 0.90

Random medium 2 1 0 0 8.49 0.33b 3.17 0.12c 0.89

Random medium 3 0 1 0 8.52 0.17b 2.99 0.06d 0.91

Within the same column, values followed by different letters (a, b, c.) differ significantly at P< 0.05.

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