Bioresource Technology 100 (2009) 3107–3112

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Bioresource Technology

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Optimization of growth media for obtaining high-cell density culturesof halophilic archaea (family Halobacteriaceae) by responsesurface methodology

Muthu Manikandan a, Lejla Pašic b,*, Vijayaraghavan Kannan a

a Centre for Advanced Studies in Botany, University of Madras, Guindy Campus, Chennai 600 025, Indiab Department of Biology, Biotechnical Faculty, University of Ljubljana, Vecna pot 111, 1000 Ljubljana, Slovenia

a r t i c l e i n f o a b s t r a c t

Article history:Received 8 October 2008Received in revised form 20 January 2009Accepted 21 January 2009Available online 24 February 2009

Keywords:Cultivation mediaHalobacterium salinarumResponse surface methodologyOptimizationHalophiles

0960-8524/$ - see front matter � 2009 Elsevier Ltd. Adoi:10.1016/j.biortech.2009.01.033

* Corresponding author. Tel.: +386 1 423 3388; faxE-mail addresses: bhagatmani@yahoo.co.in (M.

uni-lj.si (L. Pašic), kannanavo@yahoo.co.in (V. Kannan

Optimization of media components for the growth and biomass production of Halobacterium salinarumVKMM 013 was carried out using response surface methodology. A second order quadratic model wasestimated and media components were determined based on quadratic regression equation generatedby model. These were 6.35 g L�1 of KCl, 9.70 g L�1 of MgSO4, 13.38 g L�1 of gelatin and 12.00 g L�1 of sol-uble starch in nutrient broth supplemented with artificial seawater with 20% (w/v) of NaCl. In these opti-mal conditions, the obtained cell concentration of 0.746 g L�1 dry weight was in agreement with thepredicted cell concentration. The optimized media significantly shortened the time required for cell cul-ture to reach the stationary phase while providing a nearly 2.4-fold increase in biomass production. Fur-thermore, in cell cultures of three other halophilic archaea the use of optimized media enhanced growthrate and provided high-cell density.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

Halophilic archaea are obligate extreme halophiles, which re-quire at least 1.5 M NaCl for growth. In order to cope with high os-motic pressure extreme halophiles keep a very high concentrationof salts internally, thus remaining iso-osmotic with the environ-ment. Therefore, majority of haloarchaeal enzymes perform theirfunctions in vitro and in vivo at 4.0–5.0 M NaCl (Lanyi, 1974). Othercharacteristics of considerable biotechnological interest includebacteriorhodopsin – a light-driven proton pump, production of bio-polymers and carotenoid pigments and gas vesicles – recently rec-ognized as potential pathogen peptide delivery vehicle (Margesinand Schinner, 2001; Stuart et al., 2004; Sremac and Stuart, 2008).In food industry, halophilic archaea are involved in production ofvarious compounds that give the characteristic taste, flavor and ar-oma to salt fish products such as Thai fish sauce (nam pla) (Thong-tai and Sutinalert, 1991). Finally, the high-salt tolerance ofhaloarchaea enables their cultivation under non-sterile and thuscost-reducing conditions.

The optimal design of the culture media is a very important as-pect in the field of biotechnology. In case of halophilic archaea, fur-

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: +386 1 257 3390.Manikandan), lejla.pasic@bf.).

ther biotechnological advances are often hampered by low growthrates in pure culture with generation times ranging from 1.5 h forHaloterrigena turkmenica (Robinson et al., 2005) to up to 1–2 daysreported for Haloquadratum walsbyi (Burns et al., 2004). In addi-tion, several haloarchaeal species were found to exhibit longergeneration times in recommended media compared to other media(Robinson et al., 2005). Finally, although improvements of haloar-chaeal growth media were noted in early days of haloarchaeal re-search (Gouchnour and Kushner, 1969; Kauri et al., 1990;Rodriguez-Valera, 1995) there were no recent advances on thissubject.

Statistical experimental design techniques are useful tools forscreening for nutrients with significant impact on growth rate asthey can provide statistical models, which aid in understandingthe interactions among the process parameters at varying levels.Furthermore, calculations of the optimal level of each parameterfor a given target can be performed. To this aim, response surfacemethodology (Myers and Montgomery, 2002) is widely used in or-der to improve product yield, reduce development time and overallprocess costs (Ren et al., 2008; Kammoun et al., 2008; Pan et al.,2008). In this study, we have applied response surface methodol-ogy in order to optimize growth media composition for obtaininghigh-cell density cultures of model halophilic archaeon Halobacte-rium salinarum VKMM 013. In addition, we report the influence ofoptimized media on the growth rate and biomass production inthree other haloarchaeal species.

3108 M. Manikandan et al. / Bioresource Technology 100 (2009) 3107–3112

2. Methods

2.1. Microorganisms and culture media

Haloarchaeal isolates H. salinarum VKMM 013, Haloferax sp.VKMM 026, Halogeometricum borinquense VKMM 001 and Haloru-brum sp. VKMM 017 were obtained from the haloarchaeal culturecollection maintained at centre for advanced studies in Botany atthe University of Madras, India. Their 16S rRNA sequences weredeposited in GenBank under the accession numbers DQ915820,DQ915833, DQ853414 and DQ915824. The microorganisms wereisolated from brine samples of Kelambakkam solar salterns locatedin Tamilnadu, India.

For the optimization of media components and their concentra-tion, the basal media was used. It was prepared by dissolving24.320 g of NaCl, 5.140 g of MgCl2, 4.060 g of Na2SO4, 0.200 g ofNaHCO3, 0.027 g of H3BO3, 0.100 g of KBr, 0.690 g of KCl, 1.140 gof CaCl2, 0.026 g of SrCl2, 0.003 g of NaF, 0.002 g of NaSiO3,0.001 g of FeSO4 and 13 g of nutrient broth (Himedia Inc., India)in 1L of distilled water (Kester et al., 1967).

The effect of temperature, NaCl concentration and tryptone andyeast extract on the growth was studied by cultivating the organ-ism in basal media at different temperatures (20 �C–60 �C), differ-ent concentration of NaCl (5–30% (w/v)) and in basal media inwhich nutrient broth was replaced with tryptone and yeast extract(Himedia Inc., India) in 1% (w/v) concentration, respectively. Next,27 media components (Fig. 1) were tested using the one at a timeapproach at concentration levels of 0.5% (w/v), 1.0% (w/v) and 1.5%(w/v).

For growth comparison experiments, additional two mediawere used. Media JCM 168 was prepared by dissolving 10 g of lac-tose, 2 g of starch, 10 g of yeast extract (Himedia Inc., India), 1 g ofNa-glutamate, 2 g of KCl, 3 g of Na3-citrate, 20 g of MgSO4 � 7H2O,100 g of NaCl, 0.36 g of FeCl2 � 4H2O and 0.36 mg of MnCl2 � 4H2Oin 1 L of distilled water. Media DSM 372 was prepared by dissolv-ing 5 g of yeast extract (Himedia Inc., India), 5 g of casamino acids(Himedia Inc., India), 1 g of Na-glutamate, 2 g of KCl, 3 g Na3-cit-rate, 20 g of MgSO4 � 7H2O, 200 g of NaCl, 36 mg of FeCl2 � 4H2O

Fig. 1. Effect of nutrient sources in the culture media on Halobacterium salinarum VKM

and 0.36 mg of MnCl2 � 4H2O in 1 L of distilled water. The pH wasalways adjusted to 7.2. For solid media, Difco Bacto agar (Difco)was added to a final concentration of 2% (w/v).

The microorganisms were grown in 125 mL Erlenmeyer flaskscontaining 25 mL growth media at 50 �C at 200 rpm in a thermo-static orbital shaker (Sub zero Inc., Chennai, India). The cell concen-tration was measured as amount of dry weight (g L�1) obtained.The rate of increase of cell growth over time is given by Eq. (1):

ln X ¼ ln X0 þ lðt � t0Þ ð1Þ

where X0 is the cell concentration (g L�1) at the beginning of expo-nential growth phase, t0 (h); and X is the cell concentration (g L�1)after a time interval t (h). The intrinsic rate of growth of the micro-organism under the conditions used was expressed as the specificgrowth rate in exponential growth phase, l, and was calculatedas the slope of the plot between (ln X � ln X0) versus (t � t0).

2.2. Experimental design

The steps of this experimental design included performing fac-torial experiment, estimating the coefficients in a mathematicalmodel, predicting the response and checking the applicability ofthe model. In a factorial experiment, 27 different media compo-nents were screened to select the nutrients that significantly influ-enced growth of model organism. These were considered asexplanatory variables at concentration levels of 0.5% (w/v), 1.0%(w/v) and 1.5% (w/v), respectively. A response variable, cell con-centration of H. salinarum VKMM 013, was measured as dry weight(g L�1) obtained after 40 h of incubation. The experiments werecarried out in triplicates. To determine the response pattern andsynergy of variables central composite design was followed withfour variables, found to influence significantly model organism’sgrowth, examined at five levels. The coded and actual values ofthe variables are presented in Table 1. Cell concentration, mea-sured as dry weight (g L�1) obtained after 40 h of cultivation, wasconsidered as response variable. According to this design, 30 runsreplicated six times at central points were performed and experi-mental and predicted responses were obtained. The relationship

M 013 cell concentration. Each bar represents the mean ± SD of three replicates.

Table 1Coded and uncoded values of experimental variables used in the central compositeexperiment design.

Independent variables Coded levels

�2 �1 0 +1 +2

X1, KCl (g L�1) 0.0 2.5 5.0 7.5 10.0X2, MgSO4 (g L�1) 0.0 3.0 6.0 9.0 12.0X3, gelatin (g L�1) 0.0 5.0 10.0 15.0 20.0X4, soluble starch (g L�1) 0.0 2.5 5.0 7.5 10.0

M. Manikandan et al. / Bioresource Technology 100 (2009) 3107–3112 3109

of variables was determined by fitting a second order polynomialequation to data obtained from the 30 runs.

Next, a second-degree quadratic model was established as Eq.(2) as follows:

Y ¼ b0 þX4

i¼1

bixi þX4

i¼1

biix2i þ

X4

i;j¼1

bijxixj ð2Þ

where Y is the predicted response (cell concentration of H. salina-rum obtained in growth media and measured as dry weight), b0 isa constant; bi, linear terms coefficients; bii, quadratic terms coeffi-cients and bij, interaction coefficients. The relation of between thecoded forms of the input variable and the actual values of chosenvariables are described as Eq. (3).

xi ¼Xi � X0

dXi ¼ 1;2; � � � ; k ð3Þ

where xi is the coded value and Xi the actual value of an indepen-dent variable, X0 is the value of Xi at the centre point and dX isthe step change of the variable.

2.3. Statistical analysis

The calculations were performed using Design Expert 7.0, (Stat-Ease, Minneapolis, USA). Linear, quadratic and interaction effects ofthe independent variables were evaluated. The Fisher’s F-test foranalysis of variance (ANOVA) was performed on experimental datato evaluate the statistical significance of the model. The statisticalsignificance of regression coefficients was evaluated using Stu-dents t-test. Three-dimensional surface plots were drawn to illus-trate the main and interactive effects of the independent variableson cell concentration of test organism. The optimum values of theselected variables were obtained by solving the regression equa-tion and by analyzing the response surface contour plots (Myersand Montgomery, 2002). Experimental validation of the predictedmodel has also been performed.

3. Results and discussion

3.1. Optimization of growth conditions

The effect of temperature on growth of H. salinarum VKMM 013was observed in the temperature range 20 �C–60 �C. In theseexperiments, the thermophilic nature of H. salinarum became evi-dent as the growth rate peaked at 50 �C ± 2 �C. This data was inaccordance with optimum growth temperature of 49 �C–50 �C re-ported for H. salinarum by Robinson et al. (2005). Likewise, in con-sistence with previous results (Zeng et al., 2005), the growth ofmodel organism was found optimal in media supplemented with20% NaCl. In this study, the amount of biomass obtained was high-er in media supplemented with peptone-containing nutrient agar,compared to media with yeast extract and tryptone. As peptone isoften contaminated with bile salts, known to inhibit haloarchaealgrowth, both yeast extract and tryptone were repeatedly reportedas preferred substrates for haloarchaeal growth (Charlebios et al.,

1987; Kamekura et al., 1988). The effect observed was especiallyprofound in peptone-containing media supplemented with starch,known to nullify the bile effect on haloarchaeal growth (Oren,1990).

3.2. Screening for optimal growth media components

The average maximal cell culture concentrations of H. salinarumVKMM 013 as influenced by different nutrient sources in the cul-ture media are presented in Fig. 1. When different carbon sourceswere tested maximal cell concentration was obtained in mediawith soluble starch (0.42 g dry weight L�1), while addition ofmonosaccharides induced poor growth. We hypothesize that thelower biomass production observed in monosaccharide-supple-mented media could be due to repression of metabolic activity asinduced by monosaccharides at high concentrations. The enhancedgrowth observed in the presence of starch is likely due to the activ-ity of extracellular amylase, which at substrate concentrationsused, could supply sugar moieties in quantities below metabolicrepression threshold level, thus stimulating higher biomassproduction.

In general, various nitrogen sources tested induced good growthof model organism. Unsurprisingly, the biomass obtained usingpartially hydrolyzed casein in the form of casamino acids, reportedas a good substrate for haloarchaeal growth (Charlebios et al.,1987), was 0.39 g dry weight L�1. Finally, maximal impact on thecell concentration was noted when gelatin was used asnitrogen source with maximum cell concentration of 0.48 g dryweight L�1 recorded at both 1.0% (w/v) and 1.5% (w/v) gelatinconcentrations.

The concentrations of different salts in the media affected thetime needed to reach stationary phase of growth and to observethe maximal cell concentration. Among the substances tested,potassium chloride and magnesium sulphate exhibited a profoundinfluence on H. salinarum VKMM 013 growth. Potassium chlorideamended to basal media supported maximal cell concentration of0.43 g dry weight L�1 in 0.5% (w/v) concentration. Potassium ionsare, in general, required in high concentration for halophilic pro-tein stability and activity of some halophilic enzymes (Gouchnourand Kushner, 1969). Magnesium in its sulphate form supportedmaximal cell concentration production of 0.46 g dry weight L�1

at 1% (w/v) concentration. This magnesium requirement could beattributed to the nature of halophilic habitats, where the MgSO4

concentration can be very high (i.e. 22.2 g L�1 as measured inKelambakkam solar salterns).

3.3. Development of high-cell density growth media using responsesurface methodology

Using experimental design described above gelatin, MgSO4, KCland soluble starch were found to increase significantly biomassproduction by model organism. To examine the combined effectsof these independent variables thirty treatments were establishedby using computer simulation with Eq. (3). The central compositedesign of the experiment and respective experimental cell concen-trations are presented in Table 2.

In accordance with their predicted values, the experimentalrun responses showed that the maximal cell concentration ofmodel organism was expected in the growth media in whichthe concentrations of all four tested variables were at +1 concen-tration level.

Tables 3 and 4 summarize the analysis of variance for the modeland the variables tested. The ANOVA of the quadratic regressionmodel demonstrated that the computed F-value of 13.39 was sev-eral times greater of tabulated F-value of 3.56 indicating that themodel was significant at a high confidence level. The probability

� 7:208� 10 x4 ð4Þ

Table 2Central composite design and experimental cell concentration obtained.

STD order Run order X1 X2 X3 X4 Cell concentration (g dry weight L�1)

KCl MgSO4 gelatin starch Actual Predicted

1 24 �1 �1 �1 �1 0.540 0.5462 6 1 �1 �1 �1 0.591 0.6083 4 �1 1 �1 �1 0.521 0.4954 21 1 1 �1 �1 0.620 0.6225 17 �1 �1 1 �1 0.545 0.5366 25 1 �1 1 �1 0.550 0.5617 19 �1 1 1 �1 0.539 0.5578 23 1 1 1 �1 0.631 0.6489 15 �1 �1 �1 1 0.554 0.53110 14 1 �1 �1 1 0.550 0.55111 18 �1 1 �1 1 0.543 0.55012 26 1 1 �1 1 0.633 0.63613 3 �1 �1 1 1 0.570 0.58614 5 1 �1 1 1 0.550 0.57015 30 �1 1 1 1 0.700 0.67716 2 1 1 1 1 0.715 0.72717 8 �2 0 0 0 0.509 0.53018 9 2 0 0 0 0.677 0.64119 27 0 �2 0 0 0.518 0.50320 13 0 2 0 0 0.610 0.60921 1 0 0 �2 0 0.50 0.51122 12 0 0 2 0 0.618 0.59223 10 0 0 0 �2 0.639 0.62624 11 0 0 0 2 0.691 0.68925 7 0 0 0 0 0.700 0.68626 20 0 0 0 0 0.700 0.68627 16 0 0 0 0 0.691 0.68628 29 0 0 0 0 0.700 0.68629 28 0 0 0 0 0.700 0.68630 22 0 0 0 0 0.629 0.686

Table 3ANOVA for response surface quadratic model.

Source Sum of squares Degree of freedom Mean squares F-value P > F

Model error 0.11 14 9.561 � 10�3 13.39 <0.0001 SignificantResidual error 0.13 15 7.140 � 10�4

Lack of fit 6.654 � 10�3 10 6.654 � 10�4 0.82 0.6319 Not significantPure error 4.055 � 10�3 5 8.111 � 10�4

Cor. total 0.14 29

Table 4ANOVA response for linear, quadratic and interactive effect of factors used in themodel.

Model term Coefficient estimate Standard error P-value

Intercept 0.690 0.011X1 0.028 5.454 � 10�3 0.0001X2 0.026 5.454 � 10�3 0.0001X3 0.020 5.454 � 10�3 0.0022X4 0.016 5.454 � 10�3 0.0106X1

2 �0.025 5.102 � 10�3 0.0007X2

2 �0.032 5.102 � 10�3 <0.0001X3

2 �0.034 5.102 � 10�3 <0.0001X4

2 �7.208 � 10�3 5.102 � 10�3 0.1781X1 X2 0.017 6.680 � 10�3 0.0260X1 X3 �9.000 � 10�3 6.680 � 10�3 0.1979X1 X4 �0.010 6.680 � 10�3 0.1412X2 X3 0.018 6.680 � 10�3 0.0166X2 X4 0.018 6.680 � 10�3 0.0325X3 X4 0.016 6.680 � 10�3 0.0325

3110 M. Manikandan et al. / Bioresource Technology 100 (2009) 3107–3112

P-value was also very low, indicating the significance of the model(P < 0.0001). The ‘lack of fit F-value’ of 0.82 implies that the lack offit was not significant relative to pure error. The value of the deter-mination coefficient (R2 = 0.9259) indicates a high correlation be-tween the experimentally observed and predicted values and

indicates the degree of precision with which the treatments werecompared. The value of adjusted determination coefficient (AdjR2 = 0.8568) was also high enough to advocate for a high signifi-cance of the model (Khuri and Cornell, 1987). Finally, the lower va-lue of coefficient of variation (CV = 4.40%) showed that theexperiments were precise and reliable (Box et al., 1978).

In general, P-value determines the significance of each coeffi-cient in the model (Table 4). The independent variables MgSO4

and gelatin (X2, X22, X2

3) had significant effect on the growth of mod-el organism and were followed in P-values by linear and quadraticeffect of KCl. On the contrary, the interactive effect coefficients ofKCl and gelatin and KCl and starch showed less interactive effect,whereas P-values of the coefficient of quadratic effect of starchand the interactive effect of KCl and gelatin indicated little signif-icant effect on the model.

Finally, the ‘Design Expert’ software was used to find out thequadratic mathematical model, which included all terms regard-less of the level of their significance. It can be given as Eq. (4):

Y ¼ 0:69þ 0:028x1 � 0:026x2 � 0:020x3 þ 0:016x4

� 0:017x1x2 � 9:000� 10�3x1x3 � 0:010x1x4 þ 0:018x2x3

� 0:018x2x4 � 0:016x3x4 � 0:025x2 � 0:032x22 � 0:034x2

3�3 2

M. Manikandan et al. / Bioresource Technology 100 (2009) 3107–3112 3111

where Y is the predicted cell concentration and x1, x2, x3 and x4, thecoded variables of KCl, MgSO4, gelatin and soluble starch,respectively.

The Eq. (4) was solved according to Myers and Montgomery(2002). Maximal cell concentration of 0.76 g dry weight L�1 waspredicted to be obtained in basal growth media containing6.35 g L�1 of KCl, 9.70 g L�1 of MgSO4, 13.38 g L�1 of gelatin and12.00 g L�1 of soluble starch.

To assess further the effect of independent variables on thegrowth of H. salinarum VKMM 013, three-dimensional responsesurfaces plots were generated from the regression equation bykeeping the two variables at zero and changing the other two vari-ables with different combination. Interactions between KCl andMgSO4, MgSO4 and gelatin, soluble starch and MgSO4 and starchand gelatin indicated that previously predicted media concentra-tion values were optimal for maximal biomass production. Theoptimal growth media concentrations of KCl obtained by studyingthe interaction between KCl and gelatin was 6.25 g L�1 and thusslightly lower than predicted by the model. To obtain the maximalcell concentration in the presence of KCl at concentration of6.25 g L�1 the starch levels should be higher than predicted bymodel. This value was found to be present outside of the designspace.

3.4. Applicability

To confirm the applicability of the model, confirmation runsusing the calculated levels of the variables were carried out inexperimental conditions. The maximal cell concentration of0.746 g dry weight L�1 obtained experimentally was very close tothe predicted growth response of 0.762 g dry weight L�1. Similarly,repeating the experiment at central points yielded the predictedcell concentration of 0.700 g dry weight L�1.

Next, the growth of H. salinarum VKMM 013 in the optimizedmedia was compared to the growth in recommended JCM 168media (Fig. 2a.). In JCM 168, the microorganism entered exponen-tial phase of growth after 16 h of incubation where it remained un-

Fig. 2. Growth of Halobacterium salinarum VKMM 013 (a), Halogeometricumborinquense VKMM 001 (b), Haloferax sp. VKMM015 (c) and Halorubrum sp. VKMM017 (d) in recommended and optimized media.

til 56 h of incubation. By using optimized media, the time requiredfor growing culture of H. salinarum VKMM 013 cells to reach expo-nential and stationary phase was shortened to 8 and 24 h, respec-tively. Consequently, the specific growth rate of 0.091 h�1

observed in JCM 168 media increased to 0.185 h�1 in optimizedmedia. Most importantly, nearly 2.4-fold increase in biomass pro-duction was observed when the optimized media was used insteadof recommended JCM 168 media.

In subsequent experiments, we found that the optimized mediasupported rapid and enhanced growth of three other halophilic ar-chaea in comparison with their respective recommended media. Incomparison with recommended DSM 372 media, the specificgrowth rate of H. borinquense VKMM 001 cell culture increasedto 0.102 h�1 in optimized media. At the same time, the time re-quired for the growing culture to reach exponential and stationaryphase was shortened from 36 h to 24 h from 72 h to 48 h, respec-tively. This resulted in 3.3-fold increase in biomass production inoptimized media (Fig. 2b). The growth of two more halophilic ar-chaea was observed. Both Haloferax sp. VKMM 026 and Halorubrumsp. VKMM 017 reached the exponential phase of growth at thesame time in both media tested (Fig. 2c, and d). However, the spe-cific growth rates increased in optimized media from 0.049 h�1 to0.071 h�1 in Haloferax sp. VKMM 026 culture and from 0.069 h�1 to0.074 h�1 in Halorubrum sp. VKMM 017 culture. Again, substantialincreases in biomass production were noted in optimized mediaand were 1.8 and 1.9-fold, respectively.

4. Conclusions

The experimental design presented in this study effectively de-fined optimal media composition, which supported high-cell den-sities in cultures of test organism H. salinarum VKMM 013.Furthermore, the optimized media enhanced the specific growthrates and amount of biomass obtained in cultures of other halo-philic archaea tested. Given the simplicity and low-cost of prepara-tion of optimized media, we consider the results of this studyuseful for highly efficient production of halophilic archaea on a bio-reactor scale.

Acknowledgements

This work was supported by a grant from Government of IndiaMinistry of Science and Technology to Centre for Advanced studiesin Botany, University of Madras and Ministry for School and Sportsof the Republic of Slovenia research program P1-0198.

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