Accepted Manuscript

Optimisation for high cell density cultivation of Lactobacillus salivarius BBE 09-18 withresponse surface methodology

Zixing Dong, Lei Gu, Juan Zhang, Miao Wang, Guocheng Du, Jian Chen, HuazhongLi

PII: S0958-6946(13)00202-1

DOI: 10.1016/j.idairyj.2013.07.015

Reference: INDA 3561

To appear in: International Dairy Journal

Received Date: 24 October 2012

Revised Date: 20 July 2013

Accepted Date: 29 July 2013

Please cite this article as: Dong, Z., Gu, L., Zhang, J., Wang, M., Du, G., Chen, J., Li, H., Optimisationfor high cell density cultivation of Lactobacillus salivarius BBE 09-18 with response surfacemethodology, International Dairy Journal (2013), doi: 10.1016/j.idairyj.2013.07.015.

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Optimisation for high cell density cultivation of Lactobacillus 1

salivarius BBE 09-18 with response surface methodology 2

3

4

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Zixing Dong a, c, Lei Gu a, c, Juan Zhang a, c, *, Miao Wang d, Guocheng Du a, c, Jian 6

Chenb, c, Huazhong Li a, c* 7

8

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a Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan 10

University, Wuxi 214122, China 11

b National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan 12

University, Wuxi 214122, China 13

c School of Biotechnology, Jiangnan University, Wuxi 214122, China 14

d School of Food Science and Technology, Jiangnan University, Wuxi 214122, China 15

16

* Corresponding authors. Tel: +86-510-85918307 17

E-mail addresses: zhangj@jiangnan.edu.cn (J. Zhang); hzhli@jiangnan.edu.cn (H. 18

Li). 19

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___________________________________________________________________23

Abstract 24

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Based on the nutritional and physiological requirements of lactic acid 26

bacteria (LAB), the effects of different carbon sources, nitrogen sources, buffer salts, 27

microelements and growth factors on the growth of Lactobacillus salivarius BBE 28

09-18 (L. salivarius BBE 09-18) were investigated, among which three key factors 29

were determined and optimised by response surface methodology. Estimated optimal 30

conditions of the factors for the growth of L. salivarius BBE 09-18 determined. 31

After cultivated in this optimised medium for 18 h at 37 °C, the viable cell count for 32

L. salivarius BBE 09-18 was 5.94×109 cfu mL-1, which was about 3 times higher 33

than that obtained in standard Man Rogosa Sharpe medium. This study will lay a 34

solid foundation for the high cell density cultivation of L. salivarius BBE 09-18 to 35

circumvent bottlenecks encountered in the production of LAB starters and probiotic 36

ingredients in the field of dairy. 37

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1. Introduction 39

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Lactobacillus salivarius is a homofermentative microorganism that is 41

commensal in the human vagina, intestines, and oral cavities. Due to its ability to 42

grow in non-ideal conditions, such as high salt conditions, L. salivarius is somewhat 43

unique among probiotics (Charteris, Kelly, Morelli, & Collins, 1998). The strain 44

used in this study, L. salivarius BBE 09-18, has been reported to produce bacteriocin 45

(Miao, Zhen, & Xiao, 2006), which might be employed by the food industry to 46

replace chemical preservatives in foods with limited shelf life, or those foodstuffs 47

exhibiting a high risk of being contaminated by pathogen (Corr et al., 2007). This 48

strain can also lower the cholesterol level in vitro (Miao et al., 2006), and this makes 49

oral administration of viable cells to control the serum cholesterol levels of 50

hypercholesterolaemic individuals seem promising. Furthermore, it has been 51

demonstrated that this bacterium can remove cyanobacterial toxin microcystin-LR 52

(MC-LR), which can be used to deal with the MC-LR contaminated foods (Wang, 53

Zhang, Wang, Du, & Chen, 2010). All of these features make L. salivarius BBE 54

09-18 a good candidate for use as starters and probiotic ingredients for the 55

production of yoghurt, cream, cheese, and other dairy products. 56

With the growing popularity of probiotic functional foods and beverages 57

among consumers, high cell density cultivation of lactic acid bacteria (LAB) such as 58

Lactobacillus is becoming increasingly important. The growth of lactobacilli is 59

greatly influenced by fermentation conditions such as medium composition, pH, 60

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temperature, dissolved oxygen tension (DOT) and the effects of metabolites 61

(Gilliland, 1985). As LAB are fastidious about nutritional requirements, a rich 62

medium is needed for good growth (Aasen, Møretrø, Katla, Axelsson, & Storrø, 63

2000). Factors to be considered in the formulation of rich medium are costs, ability 64

to produce a large number of cells and simple harvesting methods. 65

Response surface methodology (RSM) consisting of factorial design and 66

regression analysis is more appropriate to be applied to multifactor experiments. 67

RSM is a collection of statistical techniques for designing experiments, establishing 68

models, estimating the effects of factors, and finding optimal conditions of factors 69

for desirable responses (Montgomery, 2008). The relationships between a response 70

and some related factors are quantitative, which includes the interactions and covers 71

the experimental range tested. The models built can be employed to calculate any or 72

all combinations of variables, and their effects within the test range. This method has 73

been widely used for the optimisation of culture conditions (Teng & Xu, 2008) and 74

medium composition (Liew, Ariff, Raha, & Ho, 2005; Lim, Rahim, Ho, & 75

Arbakariya, 2007; Liu et al., 2010) for various fermentation processes. However, 76

because of the specific metabolic characters and nutritional requirements, RSM has 77

rarely been applied to the cultivation of L. salivarius. 78

The main purpose of this study was to find the optimal conditions of 79

significant factors that affected the cell concentration of L. salivarius BBE 09-18. 80

The effects of different carbon sources, nitrogen sources, buffer salts, microelements 81

and growth factors on the growth of L. salivarius BBE 09-18 were studied by 82

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“change one factor at a time” method. Consequently, three main factors that had 83

significant enhancement effect on the growth of this bacterium were determined by 84

factional factorial design and optimised with RSM. Finally, the optimal conditions 85

obtained were tested for the high density cultivation of L. salivarius BBE 09-18 that 86

can be used as starters and probiotic ingredients in the dairy industry. 87

88

2. Materials and methods 89

90

2.1. Bacterial strains, medium composition, and growth conditions 91

92

The bacterium, L. salivarius BBE 09-18, isolated from the faeces of infants and 93

proven to have ideal probiotic properties (Miao et al., 2006), was used throughout 94

the study. It was kindly provided by School of Food Science and Technology, 95

Jiangnan University. 96

The composition of standard de Man, Rogosa, Sharpe (MRS) medium, pH 97

6.1-6.2, is as follows (L-1): glucose, 20 g; peptone, 10 g; beef extract, 10 g; yeast 98

extract, 5 g; sodium acetate anhydrous, 5 g; K2HPO4, 2 g; ammonium citrate dibasic, 99

2 g; MgSO4·7H2O, 0.58 g; MnSO4·4H2O, 0.25 g; Tween-80, 1 mL. Uracil and 100

guanine were dissolved in boiling distilled water and acidified with enough HCl to 101

effect solution; folic acid and nicotinic acid were dissolved in 20% (v/v) ethanol in 102

water. All these solutions were filter-sterilised and kept at 4 °C in the dark. 103

The cells of L. salivarius BBE 09-18 were stored at -80 °C in 30% (v/v) glycerol. 104

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For inoculum preparation, the stock culture was sub-cultured in a 250 mL Erlenmeyer 105

flask containing 50 mL MRS broth at 37 °C for 16 h to give a final cell concentration 106

of approximately 107 colony forming units (cfu) mL-1. The cultivation experiments 107

were conducted in 250 mL Erlenmeyer flasks containing 100 mL culture medium and 108

2% (v/v) inoculum. The flasks were incubated at 37 °C for 18 h under stationary 109

conditions and no pH control was employed during the cultivation experiments. 110

Finally, the cells were harvested at the end of the cultivation for analysis. 111

112

2.2. Analytical determination 113

114

To determine the number of viable cells (cfu), serial 10-fold dilutions of each 115

sample in sterile saline solution were plated in triplicate onto MRS agar plates. The 116

plates were then incubated at 37 °C for 48 h before enumeration. Each colony was 117

derived from a single viable cell or a colony forming unit. The final pH of the medium 118

was measured by pH/mV meter (UB-7, Denver, USA). All the results are the average 119

of three replicates. 120

121

2.3. Optimisation of carbon sources, nitrogen sources, buffer salts, microelements 122

and growth factors 123

124

The “change one factor at a time” method widely used as a traditional 125

technique for multifactor experimental design (Lim et al., 2007) was employed in 126

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this study. Different carbon sources or nitrogen sources at the concentration of 2% 127

(w/v) were used to replace those already present in standard MRS medium, 128

respectively, while all other components were maintained at a fixed level. The 129

number of viable cells and the production cost were then analysed together to choose 130

the best medium component. The effectiveness of the components is the first 131

consideration. 132

After determining the optimal carbon source and nitrogen source, we studied 133

the effects of different buffer salts, microelements, and growth factors on the cell 134

concentration of L. salivarius BBE 09-18. Medium without supplementation was 135

used as a control. Promising medium components were then chosen for subsequent 136

research. 137

138

2.4. Response surface methods and statistical analysis 139

140

In the first step, a five-factor-2-level (2III5-2) factional factorial design (FFD) 141

was performed in triplicate to identify the most significant factors strongly affecting 142

the growth of L. salivarius BBE 09-18, while unimportant factors were discarded in 143

the following experiments. The linear model obtained can be expressed according to 144

the following equation: 145

0

1

n

i i

i

Y b b X=

= +∑ (1) 146

where b0 is the intercept term; bi is the regression coefficients; Xi is the 147

corresponding natural value and n is the number of the factors. The viable count of L. 148

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salivarius BBE 09-18 was defined as dependent variable or response (Y). 149

To arrive in the domain of the optimum of the significant factors, the 150

steepest ascent method was used. This design whose direction was parallel to the 151

response of Eq. (1) began from the centre point of the factorial design and increased 152

as direction ratio of regression coefficient βi. The experiments were conducted until 153

no further increase of the response and the point in the expected experimental scope 154

was used as the centre point for further optimisation studies. 155

Finally, a central composite design (CCD) containing 6 centre runs, 8 156

factorial runs, and 6 axial runs was applied to allocate treatment combinations in this 157

experiment. With the viable count of L. salivarius BBE 09-18 as response, a 158

quadratic model was generated, which was made up of trials plus a star configuration 159

to determine quadratic effects, and central points to estimate the pure process 160

variability and reassess gross curvature. The quadratic model obtained can be 161

expressed as follows: 162

2

0 i i ii i ij i jY X X X Xβ β β β= + + +∑ ∑ ∑ (2) 163

where β0, βi, βii, and βij are the regression coefficients variables for intercept, linear, 164

quadratic, and interaction terms, respectively. Xi and Xj are the coded values of the 165

factors chosen. Y represents the response variable. 166

All designs and calculations were carried out by Design Expert Software 167

(Version 8.0.5.0, State-Ease, Minneapolis, MN, USA). The results were analysed to 168

estimate the effects of factors and the analysis of variance (ANOVA) technique was 169

employed to identify the statistically significant factors. 170

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171

3. Results and discussion 172

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3.1. Optimisation of carbon sources and nitrogen sources 174

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Different carbon sources and nitrogen sources at a concentration of 2% (w/v) 176

were used in this study, which was determined according to the results of 177

preliminary experiments (data not shown). As shown in Fig.1, the 178

growth-stimulating effects of monosaccharides and disaccharides were better than 179

those of polysaccharides. Among the carbon sources tested, maltose was the best for 180

the cultivation of L. salivarius BBE 09-18 with viable count of 1.88×109 cfu mL-1, 181

and α-lactose was second only to it, with 1.83×109 cfu mL-1. Nevertheless, starch 182

and other polysaccharides were not easily metabolised by this strain. Considering the 183

higher cost of maltose, α-lactose was chosen as the best carbon source. 184

Fig. 2 illustrates the effects of various nitrogen sources (2%, w/v) on the 185

biomass of L. salivarius BBE 09-18. In this study, peptone, soya, peptone, tryptone, 186

yeast extract, beef extract, ammonium sulphate, sodium nitrate, and urea were 187

separately chosen as main nitrogen source. The results showed that organic nitrogen 188

sources could significantly enhance the cell concentration, while inorganic nitrogen 189

sources were ineffective in stimulating the cell growth. Yeast extract was the best 190

among various nitrogen sources (the number of viable cells was 2.31×109 cfu mL-1), 191

which is due to its abundant nitrogen compounds, vitamins, purine and pyrimidine 192

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bases (Liu et al., 2010; Yoo, Chang, Lee, Chang, & Moon, 1997). Among the 193

vitamins found in yeast extract, niacin, pantothenic acid, riboflavin, folic acid, and 194

pyridoxine are the required B vitamins for stimulating the growth of lactobacilli 195

(Yoo et al., 1997). This bacterium was unable to grow in the medium with urea as 196

main nitrogen source, which was in agreement with the finding that the nitrogen of 197

nitrites, nitrates, or urea could not be metabolised by the Birch strain of 198

Lactobacillus (Hassinen, Durbin, Tomarelli, & Bernhart, 1951). Although the cost of 199

yeast extract is very high, its effect on cell growth is incomparable (Yoo et al., 1997); 200

inexpensive nitrogen sources with excellent effectiveness to replace yeast extract 201

remain to be found. Consequently, yeast extract was determined to be the optimal 202

nitrogen source. 203

204

3.2. Choosing the best buffer salts 205

206

LAB can metabolise carbohydrates to produce lactic acid in the process of 207

growth, which decreases the medium pH and inhibits bacterial propagation (Yáñez, 208

Marques, Gírio, & Roseiro, 2008). In this case, buffer salts in the medium can be 209

used to balance the pH and promote bacterial growth. In this study, typical buffer 210

systems at different concentrations were investigated according to the nutritional 211

requirements of LAB. As can be seen in Fig. 3, the cell growth initially increased 212

with the concentrations of buffer salts, but it then decreased with them. All of the 213

buffer salts could increase the final pH of the medium (data not shown). In addition, 214

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0.16 mol L-1 CH3COOH/CH3COONa system permitted excellent growth of the cells 215

(viable cell count was 3.26×109 cfu mL-1), and the final pH of the medium 216

containing this buffer salt (pH 4.50) was higher than that of medium without any 217

supplementation (pH 3.57). Thus 0.16 mol L-1 CH3COOH/CH3COONa was used as 218

the optimal buffer salt for the subsequent experiments. Some other reports also 219

demonstrated that the medium supplemented with proper amounts of sodium acetate 220

greatly stimulated the growth of many LAB (de Man, Rogosa, & Sharpe, 1960; Snell, 221

1945; Thorne & Kodicek, 1962). This is due to the fact that acetate acts not only as a 222

buffer, but also as a starting material for the synthesis of steroid and lipid compounds 223

that can duplicate the action of acetate when added to media sufficiently buffered 224

with phosphate (Snell, 1945). Phosphate is an important buffer and the source of 225

inorganic phosphorus, but the fast acid accumulation would soon impair growth 226

(Ledesma et al., 1977), which may be the reason for the low counts of viable cells. 227

228

3.3. Mineral requirements 229

230

Mg2+, Mn2+, Cu2+, Fe2+, and other microelements are indispensable for the 231

propagation of microorganisms, and can serve as the activator of enzyme or the 232

composition of bioactive substance (MacLeod & Snell, 1947). Fig. 4 shows the 233

effects of different microelements on the growth of L. salivarius BBE 09-18. The 234

medium containing Mn2+ showed the most significant enhancement effect on the cell 235

growth (Fig. 4a). In detail, the highest cell concentration was 3.27×109 cfu mL-1, 236

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which was 20% more than that of control, and the optimum level of MnSO4·H2O 237

was 190 mg L-1. As a constituent of lactate dehydrogenase to improve lactate 238

productivity and lactose utilisation under anaerobic conditions, manganese was 239

found to be essential for the growth of L. casei (Fitzpatrick, Ahrens, & Smith, 2001; 240

Krischke, Schröder, & Trösch, 1991; Senthuran, Senthuran, Mattiasson, & Kaul, 241

1997). Manganese supplementation could decrease the amount of yeast extract 242

required (Fitzpatrick et al., 2001), indicating that it is one of the key factors for the 243

growth of LAB. 244

Interestingly, after magnesium supplementation no significant enhancement 245

effect on the biomass of the cells was observed (Fig. 4b). This is similar to the 246

magnesium requirements of L. casei, which is at low levels if it exists (MacLeod & 247

Snell, 1947). A low concentration of copper slowly enhanced the cell concentration, 248

while it significantly inhibited the biomass at higher concentrations (Fig. 4c). As 249

copper seems to be a nonessential component for the growth of lactobacilli 250

(Bruyneel, Vande Woestyne, & Verstraete, 1989), the low demand of L. salivarius 251

BBE 09-18 for copper may be due to its specific metabolic characters. However, 252

medium containing iron hindered the propagation of the bacterium (Fig. 4d). As 253

LAB are catalase-negative and grow anaerobically without harbouring cytochrome, 254

they do not necessarily require iron as a cofactor for reproductive and redox 255

reactions, and if the requirement of iron exists, it will be only at extremely low levels 256

(Bruyneel et al., 1989; MacLeod & Snell, 1947). 257

Although many investigations have been done on the mineral requirements of 258

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LAB, the requirements may be determined by the metabolic characters and 259

physiological information of the specific bacterium (MacLeod & Snell, 1947). In 260

this study, manganese greatly promoted the growth of L. salivarius BBE 09-18, 261

while other three ions showed no significant growth-stimulating effect on the strain. 262

These findings are somewhat in disagreement with those of others. 263

264

3.4. Growth factors requirements 265

266

As LAB cannot produce the important precursors or intermediates under 267

anaerobic growth conditions (Liu et al., 2010), they require for complex growth 268

factors including several amino acids, B vitamins, purine and pyrimidine bases 269

(Fitzpatrick et al., 2001; Kitay, McNutt, & Snell, 1950; Ledesma et al., 1977; Snell, 270

1945), and unsaturated fatty acids (Kitay & Snell, 1950; Partanen, Marttinen, & 271

Alatossava, 2001). The effects of different growth factors at the concentration of 25 272

mg L-1 on the viable count of cells were investigated in this study (Fig. 5). Vitamin C, 273

guanine, uracil, and nicotinic acid had no significant stimulating effect on the cell 274

growth, while glycine and folic acid inhibited the propagation of the bacterium. This 275

may be because yeast extract already contains some B vitamins and amino acids to 276

meet the growth requirements of the cells (Yoo et al., 1997), and high concentrations 277

of these compounds inhibit the growth of the bacterium. The amounts of these B 278

vitamins present in 30 g L-1 yeast extract can be calculated (Yoo et al., 1997), thus 279

the importance and real levels of them can be determined. To better evaluate the 280

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importance of mineral requirements and growth factors, a simple medium as a 281

starting point for investigation and removal of trace impurities (as described by 282

MacLeod & Snell, 1947) will be undertaken in a further study. 283

Interestingly, Tween-80 had a very significant beneficial effect on the cell 284

growth, and the cell concentration was approximately 1.79×109 cfu mL-1. Tween-80, 285

which is a water soluble derivative of oleic acid (cis-9-octadecenoic acid), can 286

stimulate the growth of many LAB. Most LAB grown in medium containing 287

Tween-80 can incorporate oleic acid into their membranes and then transform it into 288

cyclopropane fatty acids. Cyclopropane fatty acids can act like polyunsaturated fatty 289

acids to increase the fluidity of membrane, and protect LAB from bad environmental 290

effects such as deleterious effects of oxygen, entering stationary growth phase, and 291

low pH caused by lactic acid accumulation (Partanen et al., 2001). Consequently, 292

Tween-80, which can also replace the biotin requirement of some strains, is regarded 293

as a growth-stimulating factor for LAB (Hassinen et al., 1951). As other growth 294

factors were less effective in promoting the growth of L. salivarius BBE 09-18, 295

Tween-80 was chosen as the optimal growth factor in further studies. 296

297

3.5. 2III5-2 factional factorial design 298

299

A 2III 5-2 factional factorial design (FFD) consisting of eight runs was applied 300

to identify the significant factors from the five components α-lactose, yeast extract, 301

MnSO4·H2O, CH3COONa, and Tween-80. According to the results of single-factor 302

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investigation, the coded factor levels, the real values of the five factors, and the 303

results of the response (viable count) are listed in Table 1. The linear regression 304

equation as a function of the coded values of significant factors was expressed as 305

follows: 306

307

Y1 = 9.465602 + 0.058515X1 + 0.03169X2 + 0.025162X3 + 0.009449X4 + 0.027123X5 (3) 308

309

where Y1 is the predicted response of viable count and X1, X2, X3, X4, and X5 310

represent the coded values of α-lactose, yeast extract, MnSO4·H2O, CH3COONa, and 311

Tween-80, respectively. 312

The ANOVA results showed that this model was statistically significant as 313

indicated by the low P-value (P>F, 0.0143). Both the determination coefficient 314

(R2=0.994) and the adjusted determination coefficient (adjusted R2=0.980) were high, 315

which also demonstrated the good fit and a high significance of the model. In 316

conclusion, this model could successfully predict the growth of L. salivarius BBE 317

09-18 and the coefficients obtained could be the direction ratio of the steepest ascent 318

method. As can be seen from the P-values of the five variable factors (data not 319

shown), their effects on the cell growth followed a descending order as: α-lactose, 320

yeast extract, Tween-80, CH3COONa, and MnSO4·H2O. Therefore, factors α-lactose, 321

yeast extract, and Tween-80 were chosen for further investigation. 322

323

3.6. Steepest ascent method 324

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325

The steepest ascent method was then employed to quickly reach the optimal 326

region, and its direction was determined by the coefficients of linear regression 327

model [eq. (3)] obtained in FFD. In eq. (3) the coefficients of α-lactose, yeast extract 328

and Tween-80 were all positive, which indicated that the viable count of L. salivarius 329

BBE 09-18 would increase with the concentrations of these compounds. The steepest 330

ascent experiment design and response results are presented in Table 2. The highest 331

viable count was obtained in the fourth step, but the number of living cells decreased 332

beyond this point. These results indicated that 40 g L-1 α-lactose, 50 g L-1 yeast 333

extract, and 2 mL L-1 Tween-80 had approached the neighbourhood of the optimum. 334

Therefore, the central points for the CCD were determined as follows: 40 g L-1 335

α-lactose, 50 g L-1 yeast extract, and 2 mL L-1 Tween-80. 336

337

3.7. Central composite design 338

339

A rotatable central composite design with points equidistant from the centre is 340

one of the efficient central composite designs (Ortega, Albillos, & Busto, 2003), and 341

it is applied to explore the optimal conditions for the high cell density cultivation of 342

L. salivarius BBE 09-18. To build a statistical model, we let Y represent viable cell 343

count (log10 cfu mL-1) and determined coded factor levels as follows: X1 = (α-lactose 344

– 40)/20, X2 = (yeast extract – 50)/25, and X3 = (Tween-80 – 2). The actual factor 345

levels corresponding to the coded factor levels, treatment combinations and response 346

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results are shown in Table 3. By fitting the experimental data with the least squares 347

method, a second-order polynomial regression model containing 3 linear, 3 quadratic 348

and 3 interaction terms was obtained and formulated as follows: 349

Y =9.71511 + 0.034819X1 + 0.103384X2 + 0.015094X3﹣0.052792X12 ﹣350

0.065087X22﹣0.004437X3

2 + 0.005825X1X2﹣0.00503X1X3 + 0.005508X2X3 351

(4) 352

where Y is the predicted response of viable count, and X1, X2, and X3 are the coded 353

values of the tested variables of α-lactose, yeast extract, and Tween-80, respectively. 354

The ANOVA was conducted to assess the adequacy and significance of the 355

model. The F-value (5.09) and the significant P-value (P>F, 0.009) could prove the 356

high significance and good fit of the model, respectively. Despite of the low R2 357

(0.895) and adjusted R2 (0.802), the high significance of the model could also be 358

demonstrated by the plot of predicted versus actual experimental values of viable 359

cell count (Fig. 6a). As shown in Fig. 6a, all the points clustering around the 360

diagonal line meant that this model could adequately predict the experiments. In 361

addition, the plot of the internally studentised residuals versus the predicted response 362

presented in Fig. 6b showed small residuals (<30%), indicating that this model could 363

well describe the response of bacterial growth out of the experimental region tested. 364

To understand the interaction and determine the optimum levels of the 365

variables for maximum response, the 2D contour plots and the 3D response surface 366

that are the graphical representations of the regression equation were used in this 367

study (Liu et al., 2010) (Fig. 7). The response surface of Fig. 7a represented the 368

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combination between α-lactose and yeast extract. In detail, well-defined optimum 369

variables were indicated by the convex response surface, which could also be proved 370

by the negative quadratic coefficients in Eq. (4). Furthermore, the elliptical contour 371

also demonstrated a strong interaction between α-lactose and yeast extract (data not 372

shown). Fig. 7b and Fig. 7c described the response surface of reciprocal effects to 373

the growth of L. salivarius BBE 09-18 by α-lactose and Tween-80, and yeast extract 374

and Tween-80, respectively. The optimum concentrations calculated from the 375

equation were: α-lactose = 43.8 g L-1, yeast extract = 79.5 g L-1 and Tween-80 = 5.15 376

mL L-1. Therefore, estimated optimal medium for the growth of L. salivarius BBE 377

09-18 was as follows: α-lactose 43.8 g L-1, yeast extract 79.5 g L-1, sodium acetate 378

anhydrous 13.12 g L-1, acetic acid 9.16 mL L-1, MnSO4·H2O 190 mg L-1 and 379

Tween-80 5.15 mL L-1. And the estimated maximum response corresponding to the 380

optimum factor levels was 6.01×109 cfu mL-1. Verification experiments were 381

performed with L. salivarius BBE 09-18 grown in estimated optimal medium for 18 382

h at 37 °C. The actual cell concentration was 5.94×109 cfu mL-1, which was nearly 383

three times higher than that in standard MRS medium. 384

At present, the high cell density culture of LAB is centred on reducing the 385

growth inhibition caused by lactic acid accumulation (Schiraldi et al., 2003). There 386

have been several methods to achieve this aim. In this research, we used buffer salts 387

to prevent the pH from lowering, and obtained a viable cell count of 5.94×109 cfu 388

mL-1, which was better than fed-batch fermentation (the final cell concentration was 389

4.7 g L-1, about 5.62×109 cfu mL-1; Zhang, Cong, & Shi, 2010) and immobilisation 390

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of Bifidobacterium longum in gellan gum gel beads (the highest cell concentration 391

was 4.9×109 cfu mL-1; Doleyres, Paquin, LeRoy, & Lacroix, 2002). We also 392

combined several optimisation methods and optimised the medium compositions 393

based on the specific metabolic characters and nutritional requirements of L. 394

salivarius BBE 09-18, which was more effective than only using RSM (Liew et al., 395

2005; Lim et al., 2007) (final cell concentrations obtained were 2.75×109 and 396

3.2×109 cfu mL-1, respectively). Although much work has to be carried out for the 397

high concentration cultivation of L. salivarius BBE 09-18, this optimised medium 398

can be used as a basal medium for the high cell density culture studies of L. 399

salivarius BBE 09-18 and the production of high effective starter concentrates. 400

401

4. Conclusions 402

403

According to the metabolic characters and physiological information of L. 404

salivarius BBE 09-18, the combinations of “change one factor at a time” method, 405

factional factorial design, steepest ascent method and central composite design were 406

used to determine optimal medium compositions for the high cell density cultivation 407

of this bacterium. This study demonstrated that RSM was useful in designing, 408

analysing, searching for the optimum points and evaluating the effects of factors 409

leading to a higher cell concentration of L. salivarius BBE 09-18. Through the 410

verification experiment, we ascertained that the optimised medium gave higher 411

counts of viable cells than the standard MRS medium. This will help to produce high 412

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cell density cultures of L. salivarius BBE 09-18, high effective starter concentrates 413

and probiotic ingredients in the dairy industry. 414

415

Acknowledgements 416

417

This work was financially supported by the Key Program of National Natural 418

Science Foundation of China (No. 20836003), the National Natural Science 419

Foundation of China (No. 30900013), the National High Technology Research and 420

Development Program of China (863 Program, 2011AA100901), the National Key 421

Technology R&D Program of China (2011BAK10B03), and the Priority Academic 422

Program Development of Jiangsu Higher Education Institutions. 423

424

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Figure legends

Fig. 1. Effects of different carbon sources (Gal, D(+)-galactose; Mlt, maltose; Fru, D-fructose;

Glu, glucose; Suc, sucrose; Lac, α-lactose; Sta, starch; Dex, dextrin; Xyl, xylose) at a

concentration of 2% (w/v) on the growth of L. salivarius BBE 09-18. Results are the mean

values of three replicates, and the error bars indicate standard deviations.

Fig. 2. Effects of 2% (w/v) of different nitrogen sources (PS, peptone, soya; Pep, peptone;

Try, tryptone; YE, yeast extract; BE, beef extract; AS, ammonium sulphate; SN, sodium

nitrate; U, urea) on the cell concentration of L. salivarius BBE 09-18.

Fig. 3. Effects of different buffer systems (�, HAc/NaAc; , NaH2PO4/Na2HPO4; ,

KH2PO4/Na2HPO4) at different concentrations (0.00-0.24 mol L-1) on the propagation of L.

salivarius BBE 09-18.

Fig. 4. Effects of different microelements on the viable count of L. salivarius BBE 09-18: a,

MnSO4·H2O (0-200 mg L-1); b, MgSO4 (0-800 mg L-1); c, CuSO4 (0-40 mg L-1); d,

FeSO4·7H2O (0-100 mg L-1).

Fig. 5. Effects of different growth factors (C, control; VitC, vitamin C; Gua, guanine; Ur,

uracil; NA, nicotinic acid; FA, folic acid; T80, tween 80) at 25 mg L-1 on the cell density of L.

salivarius BBE 09-18.

Fig. 6. Diagnostics of Eq. (4): (a) predicted values versus actual experimental values of

viable bacterium count and (b) plot of the residuals versus predicted values of viable count.

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Fig. 7. Response surfaces for the effects of: a, α-lactose and yeast extract on the cell

concentration of L. salivarius BBE 09-18 with Tween-80 at 2.0 mL L-1; b, α-lactose and

Tween-80 on the growth of L. salivarius BBE 09-18 with yeast extract at 50.0 g L-1; c, yeast

extract and Tween-80 on the growth of L. salivarius BBE 09-18 with α-lactose at 40.0 g L-1.

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Table 1

2III5-2 factorial design matrix and results of the dependent variable viable count.

Factors and levels a Run X1 (g L-1) X2 (g L-1) X3 (g L-1) X4 (g L-1) X5 (mL L-1)

Y (log10 cfu mL-1)

1 -1 (10) -1 (20) -1 (6.56) 1 (0.19) 1 (1.25) 9.390 2 1 (30) -1 (20) -1 (6.56) -1 (0.15) -1 (0.75) 9.438 3 -1 (10) 1 (40) -1 (6.56) -1 (0.15) 1 (1.25) 9.428 4 1 (30) 1 (40) -1 (6.56) 1 (0.19) -1 (0.75) 9.525 5 -1 (10) -1 (20) 1 (13.12) 1 (0.19) -1 (0.75) 9.379 6 1 (30) -1 (20) 1 (13.12) -1 (0.15) 1 (1.25) 9.528 7 -1 (10) 1 (40) 1 (13.12) -1 (0.15) -1 (0.75) 9.431 8 1 (30) 1 (40) 1 (13.12) 1 (0.19) 1 (1.25) 9.625 a -1 and 1 are coded levels.

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Table 2

Results of the steepest ascent path experiments.

Steps α-lactose (g L-1)

Yeast extract (g L-1)

Tween-80 (mL L-1)

Viable count (log10 cfu mL-1)

Origin 20 30 1 9.605 � 5 5 0.25 Origin+� 25 35 1.25 9.613 Origin+2� 30 40 1.50 9.615 Origin+3� 35 45 1.75 9.622 Origin+4� 40 50 2.00 9.626 Origin+5� 45 55 2.25 9.624

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Table 3

Treatment combinations and responses of central composite design.

Factors and levels a Run X1 α-lactose (g L-1)

X2 Yeast extract (g L-1)

X3 Tween-80 (mL L-1)

Y response b

(log10 cfu mL-1)

1 -1 (20) -1 (25) -1 (1) 9.556 2 -1 (20) -1 (25) 1 (3) 9.568 3 -1 (20) 1 (75) -1 (1) 9.663 4 -1 (20) 1 (75) 1 (3) 9.713 5 1 (60) -1 (25) -1 (1) 9.563 6 1 (60) -1 (25) 1 (3) 9.571 7 1 (60) 1 (75) -1 (1) 9.709 8 1 (60) 1 (75) 1 (3) 9.723 9 -1.682 (6.36) 0 (50) 0 (2) 9.400 10 1.682

(73.64) 0 (50) 0 (2) 9.643

11 0 (40) -1.682 (7.96) 0 (2) 9.230 12 0 (40) 1.682 (92.04) 0 (2) 9.743 13 0 (40) 0 (50) -1.682 (0.32) 9.647 14 0 (40) 0 (50) 1.682 (3.68) 9.719 15 0 (40) 0 (50) 0 (2) 9.714 16 0 (40) 0 (50) 0 (2) 9.719 17 0 (40) 0 (50) 0 (2) 9.717 18 0 (40) 0 (50) 0 (2) 9.716 19 0 (40) 0 (50) 0 (2) 9.721 20 0 (40) 0 (50) 0 (2) 9.719

a -1.682, -1, 0, 1 and 1.682 are coded levels.

b Viable count of L. salivarius BBE 09-18, and the results are the average of three replicates.

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1

D(+)-Galactose

Maltose

D-Fructose

Glucose

Sucrose

α-Lactose

StarchDextrin

Xylose7.50

8.00

8.50

9.00

9.50

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

1

Fig. 1 2

Gal Mlt Fru Glu Suc Lac Sta Dex Xyl

Via

ble

coun

t (lo

g 10 cf

u m

L-1

)

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2

Peptone,soyaPeptone

Tryptone

Yeast extract

Beef extract

Ammonium sulfate

Sodium nitrate Urea

0.00

2.00

4.00

6.00

8.00

10.00

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

3

Fig. 2 4

Via

ble

coun

t (lo

g 10 cf

u m

L-1

)

PS Pep Try YE BE AS SN U

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0.00 0.04 0.08 0.12 0.16 0.20 0.248.75

9.00

9.25

9.50

9.75

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

Concentration (mol L-1)

HAc/NaAc NaH

2PO

4/Na

2HPO

4

KH2PO

4/Na

2HPO

4

5

Fig. 3 6

Via

ble

coun

t (lo

g 10 cf

u m

L-1

)

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0 50 100 150 2009.10

9.20

9.30

9.40

9.50

9.60

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

MnSO4 H

2O (mg L-1).

a

0 200 400 600 800

9.10

9.20

9.30

9.40

9.50

9.60

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

MgSO4 (mg L-1)

b

7

0 10 20 30 409.10

9.20

9.30

9.40

9.50

9.60

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

CuSO4 (mg L-1)

c

0 20 40 60 80 100

9.10

9.20

9.30

9.40

9.50

9.60

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

FeSO4 7H

2O (mg L-1).

d

8

Fig. 4 9

10

11

12

13

Via

ble

coun

t (lo

g 10 cf

u m

L-1

) V

iabl

e co

unt (

log 1

0 cf

u m

L-1

)

Via

ble

coun

t (lo

g 10 cf

u m

L-1

) V

iabl

e co

unt (

log 1

0 cf

u m

L-1

) a b

c d

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Control

Vitamin CGuanine

Uracil

Nicotinic acidGlycine

Folic acid

Tween-808.50

8.75

9.00

9.25

9.50

Via

ble

coun

t (lo

g 10 C

FU

mL-1

)

14

Fig. 5 15

16

17

18

19

20

21

22

23

24

25

26

27

28

Via

ble

coun

t (lo

g 10 cf

u m

L-1

)

C VitC Gua Ur NA Gly FA T80

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29

Fig. 6 30

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31

Fig. 7 32

33

Via

ble

coun

t (l

og10

cfu

mL

-1)

Via

ble

coun

t (l

og10

cfu

mL

-1)

Via

ble

coun

t (l

og10

cfu

mL

-1)