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International Biodeterioration & Biodegradation 63 (2009) 943–947

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International Biodeterioration & Biodegradation

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Cultural factors affecting biosurfactant production by Gordonia sp. BS29

Andrea Franzetti a, Paolo Caredda a,b, Paolo La Colla b, Manuela Pintus b, Elena Tamburini b,*,Maddalena Papacchini c, Giuseppina Bestetti a

a Department of Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1, Milano, Italyb Department of Biomedical Science and Technology, University of Cagliari, Cittadella Universitaria, SS554 Km 4.500, 09042 Monserrato (CA), Italyc ISPESL, Department for Production Premises and Interaction with Environment, via Fontana Candida 1, 00040 Monteporzio Catone (RM), Italy

a r t i c l e i n f o

Article history:Received 5 January 2009Received in revised form29 May 2009Accepted 2 June 2009Available online 30 June 2009

Keywords:Surface-active compoundBiosurfactantGordoniaDesign of experiments

* Corresponding author. Tel.: þ39 070 254030x203E-mail address: etamburini@unica.it (E. Tamburin

0964-8305/$ – see front matter � 2009 Elsevier Ltd.doi:10.1016/j.ibiod.2009.06.001

a b s t r a c t

Gordonia sp. BS29 is a hydrocarbon-degrading bacterium isolated from a site chronically contaminated bydiesel. The strain produces extracellular bioemulsifiers, able to produce stable emulsions, and cell-boundglycolipid biosurfactants, able to reduce surface tension. The aims of this work were to investigate thecultural factors affecting the production of the cell-bound biosurfactants by Gordonia sp. BS29 and to findthe optimal composition of growth medium for the production. The cultural factors which havea significant influence on surfactant biosynthesis, identified by a two level 2(8-2) Fractional FactorialDesign, were the type and concentration of the carbon source, the concentrations of phosphates andsodium chloride, and the interactions among these factors. On these factors, a flask-scale optimisation ofcultural conditions was carried out. Then, a steepest ascent procedure and a Central Composite Designwere applied to obtain a second order polynomial function fitting the experimental data near theoptimum. In the optimised cultural condition we obtained a 5-fold increase in the biosurfactantconcentration compared to the un-optimised medium (26.00), reaching a Critical Micelle Dilution value(129.43) among the highest in literature. The optimisation procedure did not change the number andtype of the glycolipid biosurfactants produced by Gordonia sp. BS29.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

Many prokaryotic and eukaryotic microorganisms synthesisea large variety of structurally different amphiphilic molecules; bothextracellular and cell-bound compounds are produced. Neu (1996)divided microbial surface-active compounds (SACs) into low-molecular-weight SACs, also termed biosurfactants, and high-molecular weight SACs, including amphiphilic and polyphilicpolymers. The formers exhibit lower surface and interfacialtensions, whereas the latter are usually more effective in stabilizingoil-in-water emulsions, and thus they are effective bioemulsifiers(Ron and Rosenberg, 1999).

Microbial ability to biosynthesize SACs is often coupled withtheir ability to grow on immiscible carbon sources, such ashydrocarbons. SACs have been demonstrated to play a role indifferent stage of the interaction between microorganisms andhydrocarbons by overcoming the low solubility of these substrates,accessing to hydrocarbons before transportation into cells, andregulating the adhesion–deadhesion of microbial cells from and to

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hydrocarbon surfaces (Van Hamme et al., 2006; Franzetti et al.,in 2008b).

Many microbial SACs exhibited equivalent activities of syntheticsurfactants, having the advantages of a lower toxicity and higherbiodegradability, and the possibility to be produced from renew-able and inexpensive substrates. These characteristics result ingreater acceptability of microbial SACs, especially in applicationsthat cause the dispersion of SACs in the environment. In recentyears, both low and high molecular weight SACs have been evalu-ated as substitutes for chemically synthesised surfactants toimprove the rate of oil and heavy metals removal in soil and waterremediation technologies. A wide range of other different potentialcommercial exploitations have been described in the oil industry,such as microbial enhanced oil recovery, oil transportation and tankcleaning, as well as in medicine, cosmetics and food industries(Rosenberg and Ron, 1997; Banat et al., 2000).

So far, microbial SACs have not found wide industrial applicationdue to their high production costs, particularly, for the extraction andpurification steps. Microbial SAC production is strongly influencedby the medium composition and cultural conditions (Desai andBanat, 1997). The identification and optimisation of the culturalconditions that affect the SAC production represent key points for thedevelopment of a cost-competitive process (Mukherjee et al., 2006).

Table 1Values of the higher and the lower levels for each variable in 2(8-2) FFD.

ID Factors Coded variable

�1 þ1

xmin xmax

x1 NaNO3 (mg l�1) 425 4250x2 (NH4)2SO4 (mg l�1) 570 5700x3 K2HPO4:KH2PO4

(2:1 weight ratio)(mg l�1)

364 3640

x4 MgSO4 (mg l�1) 25 250x5 FeSO4$7H2O (mg l�1) 27 270x6 NaCl (mg l�1) 126 1260x7/1 Carbon source Glycerol (20 g l�1) n-hexadecane (20 g l�1)x8 Time of growth (days) 5 10

A. Franzetti et al. / International Biodeterioration & Biodegradation 63 (2009) 943–947944

In the last years, the factors affecting surfactant biosynthesishave been studied extensively, especially for Pseudomonas, Candidaand Rhodococcus (Suzuki et al., 1974; Syldatk et al., 1985; Guerra-Santos et al., 1986; Ramana and Karanth, 1989; Kosaric et al., 1990;Singh et al., 1990; Espuny et al., 1996). Biosurfactant production isoften produced under growth-limiting conditions of nitrogen.

We recently isolated three hydrocarbon-degrading bacterialstrains belonging to the genus Gordonia from a site chronicallycontaminated by diesel. Particularly, Gordonia sp. BS29 has beenextensively characterised (Franzetti et al., 2008a). This strainproduces at least two different types of SACs: extracellular bio-emulsifiers, able to produce stable emulsions but does not reducesurface tension, and cell-bound glycolipid biosurfactants, able toreduce surface tension. Moreover, SACs by Gordonia sp. BS29 haveshown interesting potential applications in environmental resto-ration techniques such as bioremediation and washing of hydro-carbon-contaminated soils (Franzetti et al., 2009). Gordonia isrecognised as an emerging genus in industrial and environmentalbiotechnology thanks to the catabolic and anabolic abilities ofseveral Gordonia strains (Arenskotter et al., 2004). Up to now, nostudy has been retrieved in literature regarding the relationshipbetween medium composition and biosurfactant production inGordonia strains.

The aims of this work were to investigate the cultural factorsaffecting the production of the cell-bound biosurfactants by Gor-donia sp. strain BS29 and to find the optimal composition of thegrowth medium for the production at flask-scale. The processinvolved three consecutive steps (Montgomery, 2005). In the firststep a two level 2(8-2) Fractional Factorial Design (FFD) was used toidentify cultural factors having a significant influence on thesurfactant biosynthesis. Then, on the selected factors, a steepestascent procedure and a Central Composite Design (CCD) wereapplied to obtain a second order polynomial function which fittedthe experimental data in the vicinity of the optimum. The factorstaken into account were the inorganic nutrient concentrations(phosphorous, ammonium and micronutrients), the type andconcentration of the carbon source, and the time of growth.

2. Materials and methods

2.1. Growth condition and culture preparation

The cultures of Gordonia sp. BS29 were incubated in a rotaryshaker at 250 rpm and 30 �C for 24 h in Luria-Bertani medium (perlitre): yeast extract 5 g, tryptone 10 g, NaCl 5 g (Maniatis et al.,1982). The cells were removed by centrifugation, washed twice andsuspended in mineral medium. Cultures were prepared with 20 mlof mineral medium in 100 ml Erlenmeyer flasks inoculating thecultures to an initial optical density at 600 nm (OD600) equal to 0.1and adding the necessary amount of carbon source. Excluding theinvestigated components, the basal composition of the mineralmedium was as follows: CaCO3 2.5 mg l�1; ZnSO4$7H2O 1.8 mg l�1;MnSO4$H2O 1.4 mg l�1; CuSO4$5H2O 0.31 mg l�1; CoSO4$7H2O0.35 mg l�1; H3BO3 0.075 mg l�1.

2.2. Quantification of biosurfactants

For each experimental design the dependent variable was theCritical Micelle Dilution (CMD) which was determined as thereciprocal of the dilution factor to achieve Critical Micelle Concen-tration (CMC) i.e. the minimal concentration of biosurfactant atwhich the formation of micelles occurs. This parameter is propor-tional to the amount of the biosurfactant produced in the culture.CMD was measured on the crude broth and according to the dilutionmethod previously described by Pagilla et al. (2002). Analyses were

carried out with De Nouy ring method using K-8 tensiometer (Kruss,Hamburg, Germany). All determinations were performed at least induplicate.

2.3. Design of experiments

2.3.1. Coding of the variablesIn each experimental design, the independent variables were

coded according to the following equation:

Ci ¼ 2��

xi � xmin

xmax � xmin

�� 1 (1)

where Ci is the coded value of ith variable, xi is the ith actual value ofith variable, xmax and xmin are the higher and the lower limit valuesof the range chosen for the ith variable.

2.3.2. Fractional Factorial Design (FFD)Based on previous literature, the concentrations of six major

inorganic components, the carbon source and the time of growthwere evaluated in order to determine the cultural factors havinga significant influence on biosurfactant production (Table 1). Wehave previously demonstrated that Gordonia sp. BS29 synthesisesbiosurfactant during the exponential phase and biosurfactantconcentration increases above the CMC during the following lineargrowth (Franzetti et al., 2008a). Thus, in this study we chose thehigher and lower levels of the variable time of growth that fall inthe linear phase (5 days and 10 days).

According to the full factorial design at two levels, 28 experi-ments should have been carried out. The number of the experi-ments was reduced by using a one-quarter fractional design byassuming that the three- and higher–order interactions amongfactors were neglectable. The selected design was the two levelfractional factorial one with a resolution of V (2(8-2) R ¼ V)composed by 64 different experiments which other 4 centre pointexperiments were added to. Each factor was fixed in the experi-mental design at two different levels and the values of the levelswere chosen based on previous studies (Table 1).

2.3.3. Steepest Ascendant Method (SAM)A two level Full Factorial Design (2(3)) with three centre points

was then applied, centred on the best conditions found in theprevious design. This design was built with the significant factorsNaCl and phosphates, testing, also, two different concentrations ofn-hexadecane as carbon source. Table 2 shows the ranges tested inthis design. The aim of this design was to explore the response inthe region of the current optimum and find the direction in theexperimental field which most rapidly the response increases in.

Then, starting from the centre of the full factorial design, eightexperiments were conducted along the linear steepest ascent

Table 4Values of the levels for each variable in CCD.

ID Factors Coded variable

�1.682 �1.000 þ1.000 þ1.682

a xmin xmin xmax a xmax

x3 K2HPO4:KH2PO4

(2:1 weight ratio) (mg l�1)1893 2600 4680 5387

x6 NaCl (mg l�1) 94 101 127 134x7/2 n-hexadecane (g l�1) 25.7 32.5 52.5 59.3

Table 2Values of the higher and the lower levels for each variable in 2(3) Full FactorialDesign.

ID Factors Coded variable

�1 þ1

xmin xmax

x3 K2HPO4:KH2PO4 (2:1 weight ratio) (mg l�1) 1822 5465x6 NaCl (mgl�1) 36 189x7/2 n-hexadecane (g l�1) 5 35

A. Franzetti et al. / International Biodeterioration & Biodegradation 63 (2009) 943–947 945

calculated by the first order function best fitting the Full FactorialDesign data. Table 3 shows the performed experiments.

2.3.4. Central Composite Design (CCD)The aim of this experimental set was to develop an empirical

model to quantify the production of biosurfactants and maximise itin the selected operating region for the most significant factors.This approach is called response surface methodology. A CCD wasdesigned using as centre the best conditions found in SAM. Theindependent variables were NaCl, phosphates and n-hexadecaneconcentrations. Table 4 shows the values of the four levels for eachfactor and their coded values. The design is composed by a two level2(3) FFD (eight experiments), six axial experiments (a ¼ 1.682) andtwo centre point experiments.

2.3.5. Data analysisThe ANOVA analyses of the experimental design results and the

regression analyses were performed using STATISTICA� software.

2.4. Chemical characterisation of biosurfactants

The chemical type and number of biosurfactants produced in theun-optimised and optimised cultural conditions were compared bysolvent extraction and thin layer chromatography (TLC) analysis aspreviously reported (Franzetti et al., 2008a). Briefly, the cultureswere prepared in un-optimised medium (M1 broth) with 20.0 g l�1

(w/v) of n-hexadecane and in the mineral medium with the opti-mised concentrations of salts and carbon source.

The bacterial cells were centrifuged at 6000 rpm for 15 min andthe cell layer, located on the aqueous surface, was extracted withchloroform–methanol (2:1). The extract was dried and suspendedin chloroform. Samples were then spotted on TLC silica gel plates(60 F254 Merck). Plates were developed in chloroform/methanol/water (65:20:2). Silica plates were sprayed with a-naphthol solu-tion (Molish reagent) to detect glycolipids (Arino et al., 1998).

3. Results

3.1. Identification of significant factors by FFD

Among the several cultural factors that can potentially affect theproduction of biosurfactants, we chose to analyse the concentrationsof six inorganic nutrients and the time of culture growth. For each of

Table 3Values for each variable in the experiments performed in SAM.

Factor n-hexadecane (g l�1) NaCl (mg l�1)

Origin 20.0 126Step1 27.5 122Step2 35.0 118Step3 42.5 114Step4 50.0 110Step5 57.5 106Step6 62.5 102Step7 72.5 98

these factors a wide range of concentrations was selected with a 1:10ratio between the lower value and the higher one (Table 1).Furthermore, the type of carbon source was added to the design asa qualitative variable. n-Hexadecane and glycerol were chosen asunsoluble and soluble substrates according to previous tests. Wesupposed that the three- and higher–order interactions could beneglected. This allowed us to reduce the number of the experimentscompared to a 2(8) full factorial design. The assumption led to builda 2(8-2) FFD with resolution of V, with seven quantitative variablesand a qualitative independent one. The whole experimental designwas composed by 64 runs plus 4 centre point experiments, two foreach value of the qualitative variables. For each run the CMD of thecrude broth was measured as a parameter proportional to the bio-surfactant concentration. The results were, then, analysed by theANOVA test to determine which one of the factors significantlyaffects the biosynthesis. The output of the ANOVA test (a ¼ 0.05) isshown in Table 5. In the ANOVA test, the three- and higher-orderinteractions were not considered. In the Table 5 only the mostsignificant factors and interactions are presented.

The FFD allowed us to select, among the eight tested culturalconditions, the three medium components which significantlyaffected the amount of biosurfactants produced by Gordonia sp.BS29. Being F0.05, 1, 31 ¼ 4.16, the significant factors and interactionswere: the type of the carbon source (x7/1), the concentrations ofphosphates (x3) and sodium chloride (x6), and the interactionsamong these factors (x7/1byx3;x7/1byx6;x3byx6). The values of theestimated effects (Table 6) permitted to evaluate the positive ornegative correlations between the significant factors and theresponse; particularly, the positive correlation of the qualitativevariable carbon source (the most important factor) meant that thevalue of the variable coded byþ1 (n-hexadecane) is better than theother (glycerol). Ignoring the unsignificant factors and interactions,the first-order model best fitting the experimental data was thefollowing:

CMDpred ¼ 16:76þ 10:07x3 � 7:87x6 þ 15:21x7=1 � 6:55x3x6

þ9:54x3x7 � 7:48x6x7 (2)

where CMDpred is the model predicted value of CMD.Substituting the values of the variables which gave the

maximum predicted result (x3 ¼ 1; x6 ¼ �1; x7/1 ¼ 1), a value ofCMDpred equal to 73.49 (90% confidence interval: 63.15–83.49) was

Table 5ANOVA test results for 2(8-2) FFD.

Factor/interaction SS df MS F p

x7/1 15 735.05 1 15 735.05 44.49 <0.00001x3 6488.30 1 6488.30 18.34 0.00016x3 by x7/1 5825.51 1 5825.51 16.46 0.00031x6 3965.85 1 3965.85 11.21 0.00214x6 by x7 3588.01 1 3588.01 10.14 0.00328x3 by x6 2748.38 1 2748.38 7.77 0.00898

ERROR 10 963.16 31 353.65TOTAL SS 60 084.58 67

Table 6Estimated effects of significant factors and interactions in 2(8-2) FFD.

Factor/interaction Estimated effect �95% Confidenceinterval

þ95% Confidenceinterval

Mean factor 16.75 12.10 21.41x7/1 30.42 21.12 39.72x3 20.13 10.54 29.72x3 by x7/1 19.08 9.49 28.66x6 �15.74 �25.53 �6.15x6 by x7 �14.97 �24.56 �5.39x3 by x6 �13.10 �22.69 �3.51

A. Franzetti et al. / International Biodeterioration & Biodegradation 63 (2009) 943–947946

obtained. Even if this was only the factor-screening step, weobtained a maximum CMDpred value among the best ones in thecurrent literature. It was almost 3-fold higher than the oneobtained culturing Gordonia sp. BS29 strain in M1 mineral medium(Franzetti et al., 2008a).

3.2. Response surface analysis

The SAM is an efficient tool to rapidly move towards theoptimum of the experimental field. To detect the direction in whichthe response increases most rapidly, a Full Factorial Design withthree quantitative variables (x3;x6;x7/2) has been applied aroundthe best condition found in the previous design, i.e.x1¼ x2¼ x4¼ x5¼ x8¼ 0;x3¼ 1;x6¼�1. n-Hexadecane was chosenas quantitative variable (x7/2) as showed in Table 2. The ANOVA testfor this design showed that n-hexadecane is the only significantfactor in those conditions. Even if the NaCl concentration did notresult significant (p � 0.05), a first order model, considering onlymain effects and ignoring the variable x3, was applied to find theequation (Eq. (3)) of the plane best fitting the experimental data.

CMDpred ¼ 51:59� 12:25x6 þ 37:30x7=2 (3)

Eight experiments were then carried out on this plane startingfrom the centre of the full factorial design along the direction of thehighest slope (Table 3). The other variables were kept constant atthe following values: x1 ¼ x2 ¼ x4 ¼ x5 ¼ x8 ¼ 0;x3 ¼ 1 according toboth the Eq. (1) and ranges of Table 1. Results allowed us to detecta maximum along this path which coincided with the step 3. In thiscondition, the concentrations of n-hexadecane and NaCl were42.5 g l�1 and 114 mg l�1, respectively. We observed a significantincrease of the CMD value from the origin (72.5) to the step 3(128.3). This result confirmed the importance of the concentrationof n-hexadecane on the biosurfactant production.

Centering the design in the conditions of step 3, a CCD has beenbuilt to calculate a second-order function which led to estimate theoptimum conditions for the biosurfactant production. The chosenvariables were x3, x6 and x7/2, coded according to both the Eq. (1)and ranges shown in Table 4. The ANOVA test (a ¼ 0.05) is shownin Table 7. It is evident that there are no significant factors (F0.05, 1,

Table 7ANOVA test results for CCD.

Factor/interaction SS df MS F p

X3 (L) 48.02 1 48.02 1.44 0.27542x3 (Q) 65.44 1 65.44 1.96 0.21084x6 (L) 10.54 1 10.54 0.31 0.59432x6 (Q) 52.25 1 52.25 1.56 0.25729x7 (L) 55.74 1 55.74 1.67 0.24366x7 (Q) 46.21 1 46.21 1.38 0.28373x3 (L) by x6 (L) 15.68 1 15.68 0.47 0.51855x3 (L) by x7 (L) 14.04 1 14.04 0.42 0.54044x6 (L) by x7 (L) 160.20 1 160.20 4.8 0.07092

ERROR 200.14 6 33.35TOTAL SS 594.39 15

6 ¼ 5.99) in this region of the experimental field. This result did notpermit to calculate a second order model for the identification ofthe best conditions, being the mean coefficient the only importantfactor. The mean coefficient value was 129.43 (95% confidenceinterval: 119.47–139.40). This is one of the best values of CMD in thecurrent literature and it is much higher than both the one found inthe un-optimised M1 medium (26.00) and the highest one calcu-lated by FFD (73.49). This result, also, demonstrates that there isa quite wide region of the experimental field in which the responsecould be considered the highest and, virtually, constant. Thisrobustness can have a very positive impact on the scaling up of theprocess to an industrial scale in which the cultural conditions canbe controlled less efficiently than at laboratory scale.

3.3. Chemical characterisation of biosurfactants

Solvent extraction and TLC analyses were carried out in order tocompare the number and type of biosurfactants produced in theun-optimised (M1 medium with 20 g l�1 n-hexadecane) and opti-mised cultural conditions [Carbon source: n-hexadecane 42.5 g l�1

– Mineral components: NaNO3 2337 mg l�1, (NH4)2SO4 3135 mg l�1,K2HPO4 : KH2PO4 (2:1 weight ratio) 2002 mg l�1, MgSO4 137 mg l�1,FeSO4$7H2O 148 mg l�1, 114 NaCl mg l�1 – Microelements: CaCO3

2.5 mg l�1, ZnSO4$7H2O 1.8 mg l�1, MnSO4$H2O 1.4 mg l�1, CuSO4

5H2O 0.31 mg l�1, CoSO4$7H2O 0.35 mg l�1, H3BO3 0.075 mg l�1].Two main spots (Rf1 ¼ 0.27; Rf2 ¼ 0.51) were detected by

glycolipid specific a-naphthol staining in the un-optimised condi-tion, as previously reported (Franzetti et al., 2008a). The sameresult was also obtained in the TLC analyses of the extract frombacterial biomass grown in the optimised medium. Thus, theoptimisation of the cultural conditions did not change the numberand type of the glycolipid biosurfactants produced by the Gordoniasp. BS29. The semi-quantitative comparison by TLC analysis of thebiosurfactants produced in the un-optimised and optimisedconditions confirmed an increase in the production after the opti-misation of the medium composition.

4. Discussion

The factors affecting the surfactant biosynthesis have beenextensively studied in the last years, but few of these studies usedproper statistical tools for experimental design. The classicalmethod of medium optimisation consists in changing one variableat time and keeping the others at fixed level. This time-consumingmethod leads to neglect the interaction among factors and, often,does not guarantee the actual determination of the optimalconditions. Biosurfactant production has often been found undergrowth-limiting conditions. Nitrogen limitation caused an increasein biosurfactant production in Pseudomonas aeruginosa (Ramanaand Karanth, 1989), Candida tropicalis IIP-4 (Singh et al., 1990), andNocardia sp. SFC-D (Suzuki et al., 1974; Kosaric et al., 1990). Syldatket al. (1985) have showed that nitrogen limitation does not onlycause overproduction of biosurfactant but changes, also, thecomposition of the product. Guerra-Santos et al. (1984, 1986) havefound the maximum rhamnolipid production when the nitrogenlimitation occurred, at a C:N ratio ranging from 16:1 to 18:1,whereas no surfactant production has been found below a C:N ratioof 11:1, when the culture was not nitrogen limited. On the contrary,Espuny et al. (1996) have found a growth-dependent production ofbiosurfactant by Rhodococcus sp. Furthermore, n-tridecane hasbeen identified as the best carbon source for the biosurfactantproduction while the best medium composition contained sodiumnitrate and phosphates at concentrations of 2.5 g l�1 and 2.0 g l�1,respectively. In this work, no significant influence of the nitrateconcentration was observed on surfactant biosynthesis whereas

A. Franzetti et al. / International Biodeterioration & Biodegradation 63 (2009) 943–947 947

the inorganic component of the cultural medium, significantlyaffecting the biosynthesis, was phosphorous. Jacques et al. (1999)have found the same influence of the phosphorous concentrationon the lipopeptide production by Bacillus subtilis S499 while theconcentrations of FeSO4 and MnSO4 affect the surfactin productionby B. subtilis DSM 3256 more than the nitrogen one (Sen, 1997).

Recently, experimental design techniques have been applied forthe optimisation of biosurfactant production. Jacques et al. (1999)have optimised cultural and fermentative conditions for lipopetide(surfactin) production by B. subtilis. Cunha et al. (2004) have iso-lated different Serratia spp. strains and evaluated the effects of thefermentative conditions and carbon source concentration on thesurfactant biosynthesis. Albuquerque et al. (2006) were the firstwho optimised the medium components for the bioemulsifierproduction by Candida lipolytica. Overall, our study can be consid-ered the first attempt to identify the cultural parameters influ-encing the biosurfactant production in Gordonia genus. The use ofdifferent experimental design techniques resulted in a straightfor-ward and time-saving process which allowed us to individuate themost important parameters and interactions, and, finally, identifythe concentrations of these parameters maximising the bio-surfactant production at flask level. Carrying out 98 batch experi-ments, we could evaluate, at the same time, eight different culturalparameters. In the optimised broth composition we obtained a 5-fold increase in the biosurfactant concentration compared to theM1 broth, reaching a CMD value [129.43 (95% confidence interval:119.47–139.40)] among the highest in literature. Furthermore, theoptimisation procedure did not change the number and type ofthe glycolipid biosurfactants produced by the Gordonia sp. BS29.The concentration of n-hexadecane, phosphates and sodiumchloride were the cultural factors significantly influencing thesurfactant biosynthesis. In order to better evaluate the effect ofphosphate buffer, a kinetic experiment was carried out by growingGordonia sp. BS29 under unoptimised and optimised conditionsand measuring pH over time (data not shown). Results indicatedthat the pH values remained almost constant in both cultural mediaranging between 5.70 and 5.90 in the unoptimised medium and6.60–6.80 in the optimised one. Both the media demonstrateda suitable buffering capacity whereas the higher pH valuesobserved under the optimised conditions could be responsible forthe improvement in biosurfactant production. An effect of phos-phate on the biosurfactant anabolic pathway cannot be excluded.Currently, this metabolic pathway has not been studied in Gordonia.However, as already hypothesised by Pagilla et al. (2002), the cell-bound glycolipids produced by Gordonia are likely to be structurallysimilar to the trehalose dimycolates produced by several strains ofRhodococcus. This biosynthetic pathway has been elucidated inRhodococcus where one of the key reactions for the synthesis of thefinal resulting sugar residue, trehalose-6-phosphate, is catalysed bythe trehalose-6-phosphate synthetase. UDP-glucose and glucose-6-phosphate are the immediate precursors (Lang and Philp, 1998).Actually, the effect of phosphate on this metabolic pathway has notbeen investigated yet. Among Actynomycetes, high phosphateconcentrations in liquid medium has been described to lead to anaccumulation of glucose-6-phosphate in Streptomyces cells whengrown on glucose (Madry et al., 1979). Based on these results, wecould hypothesise that the high concentration of phosphorous inthe optimised conditions could increase the amount of glucose-6-phosphate in Gordonia cells and subsequently the activity oftrehalose-6-phosphate synthetase.

Acknowledgments

The authors gratefully acknowledge Dr. Silvia Beretta for labo-ratory assistance and Prof. Roberto Todeschini for manuscript

revision. This work was partially funded by ISPESL (Project:‘‘Biosynthesis and characterisation of surfactants for hydrocarbon-contaminated site remediation).

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