Scholarly article on topic 'Diffusion of solutes inside bacterial colonies immobilized in model cheese depends on their physicochemical properties: a time-lapse microscopy study'

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Academic research paper on topic "Diffusion of solutes inside bacterial colonies immobilized in model cheese depends on their physicochemical properties: a time-lapse microscopy study"

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Food Microbiology

Diffusion of solutes inside bacterial colonies immobilized in model cheese depends on their physicochemical properties: a time-lapse microscopy study.

Juliane Floury, Ilham El_Mourdi, Juliana Valle Costa Silva, Sylvie Lortal, Anne Thierry and Sophie Jeanson

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Frontiers in Microbiology 1664-302X

Original Research Article 05 Feb 2015 10 Apr 2015 10 Apr 2015

Floury J, El_mourdi I, Silva JV, Lortal S, Thierry A and Jeanson S(2015) Diffusion of solutes inside bacterial colonies immobilized in model cheese depends on their physicochemical properties: a time-lapse microscopy study.. Front. Microbiol. 6:366. doi:10.3389/fmicb.2015.00366

© 2015 Floury, El_mourdi, Silva, Lortal, Thierry and Jeanson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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1 Diffusion of solutes inside bacterial colonies immobilized in model

2 cheese depends on their physicochemical properties: a time-lapse

3 microscopy study.

5 Juliane Floury1,2*, Ilham El Mourdi1,2, Juliana V. C. Silva1,2, Sylvie Lortal1,2Anne Thierry1,2,

6 Sophie Jeanson '

7 1INRA, UMR1253 Science and Technology of Milk and Eggs, F-35042 Rennes, France

8 Agrocampus Ouest, F-35042 Rennes, France

9 * Correspondence: A/Pr. Juliane Floury, UMR STLO INRA/Agrocampus Ouest, 65 rue de Saint

10 Brieuc, 35042 Rennes Cx, France,

11 Keywords: bacterial colony1, Lactoccocus lactis2, cheese3, confocal microscopy4, diffusion5, milk

12 protein6.

14 Abstract

16 During cheese processing and ripening, bacteria develop as colonies. Substrates and metabolites must

17 then diffuse either from or into the colonies. Exploring how the inner cells of the colony access the

18 substrates or get rid of the products leads to study the diffusion of solutes inside bacterial colonies

19 immobilized in cheese. Diffusion limitations of substrates within the bacterial colony could lead to

20 starvation for the cells in the center of the colony.

21 This study aimed at better understands ripening at the colony level, by investigating how diffusion

22 phenomena inside colonies vary depending on both the physicochemical properties of the solutes and

23 Lactococcus lactis strain. Dextrans (4, 70 and 155 kDa) and milk proteins (BSA, lactoferrin and aS1-

24 casein) of different sizes and physicochemical properties were chosen as model of diffusing solutes,

25 and two L. lactis strains presenting different surface properties were immobilized as colonies in a

26 model cheese. Diffusion of solutes inside and around colonies was experimentally followed by time-

27 lapse confocal microscopy.

28 Dextran solutes diffused inside both lactococci colonies with a non-significantly different effective

29 diffusion coefficient, which depended mainly on size of the solute. However, whereas flexible and

30 neutral hydrophilic polymers such as dextran can diffuse inside colonies whatever its size, none of

31 the three proteins investigated in this study could penetrate inside lactococci colonies. Therefore, the

32 diffusion behavior of macromolecules through bacterial colonies immobilized in a model cheese did

33 not only depends on the size of the diffusing solutes, but also and mainly on their physicochemical

34 properties. Milk caseins are probably first hydrolyzed by the cell wall proteases of L. lactis and/or

35 other proteases present in the cheese, and then the generated peptides diffuse inside colonies to be

36 further metabolized into smaller peptides and amino acids by all the cells located inside the colonies.

40 1. Introduction

41 During cheese making, regardless of the cheese type, bacteria are immobilized in the curd during the

42 coagulation step, and then grow as colonies spread within the cheese curd. Jeanson et al. (2011)

43 showed that the distribution of Lactococcus lactis colonies was random in a non-fat model cheese.

44 Lactococci are the most used starters in the cheese industry. They are a major actor of ripening which

45 gives the cheese its final sensorial properties. During ripening, they are responsible for the

46 proteolysis, the milk protein breakdown, leading to peptides and amino acids. It is then obvious that

47 the access to nitrogen sources, i.e. proteins and derivates, is of major importance for the proteolysis

48 activity and the bacterial metabolism of the cells within the colony. However, the way the bacteria

49 interact with dairy components is still poorly understood (Burgain et al., 2014). It is highly probable

50 that, on one hand, milk proteins have to diffuse from the cheese matrix (a fat-protein network) into

51 the colony to reach the bacterial cells in the center of the colony. Indeed, nutrients have to reach the

52 center cells of the colony; otherwise these center cells may be starved. On the other hand, proteolysis

53 end-products (small peptides and amino acids) have to diffuse from the bacterial colonies into the

54 cheese matrix. If diffusion limitations occur inside the bacterial colony, gradients of concentration of

55 both nitrogen sources (low concentrations in the center of the colony) and nitrogen end-products

56 (high concentrations in the center of the colony) may be generated and may affect the metabolic

57 activity of microbial cells, and thus the kinetics of the ripening process. The mean diameters of

58 colonies and the mean distance between them in a model cheese were shown to be strongly

59 influenced by the initial inoculation level. The lower the inoculation level was, the larger the colonies

60 were, and then the further away they were from each other (Jeanson et al., 2011). It has previously

61 been observed that low concentration of substrates could generate different physiological states or

62 different growth rates in pathogenic bacterial colonies when colonies were bigger than 400 (xm

63 diameter (Kreft et al., 1998; McKay et al., 1997). The main hypothesis for these observations was

64 that the diffusion limitations of substrates within the bacterial colony lead to starvation for the cells in

65 the center of the colony. As a consequence, lysis could be higher for the center cells in Vibrio cholera

66 colonies (Wimpenny, 1992). If lysis occurs at the center of the colony, it is also very important to

67 know if bacterial enzymes could diffuse out of the colony to determine how far from the colony

68 proteolytic enzymes could diffuse outside the colony, in the cheese matrix.

70 However, Floury et al. (2010) reported a strong lack of data about the diffusion properties of key

71 molecules like sugars, organic acids, proteins and peptides in cheese. The first effective diffusion

72 coefficient was determined for nisin in model cheeses (Aly et al., 2011). Using fluorescently labelled

73 solutes, Silva et al. (2013) showed that dextran macromolecules up to 2 MDa, and different dairy

74 proteins, were able to diffuse through the model cheese. Quite interestingly, the proteins tested (rigid

75 and negatively charged molecules) were hindered to a greater degree than the dextrans (flexible and

76 neutral molecules) in the model cheese, due to specific interactions between the protein matrix and

77 the diffusing proteins. So far, only our previous study (Floury et al., 2013) has investigated the

78 diffusion of molecules within bacterial colonies. Even if it has been demonstrated that viral particles

79 such as bacteriophages (»100 nm head) could diffuse inside biofilms (Lacroix-Gueu et al., 2005;

80 Briandet et al., 2008), we consider that the structure of biofilms (with exopolysaccharide matrix) and

81 colonies is not really comparable. It was then very important to understand ripening at the colony

82 level by investigating the diffusion of model nutrient macromolecules, such as polysaccharides and

83 milk proteins, inside lactococci colonies.

85 In our previous study (Floury et al., 2013), we developed a specific experimental design and we

86 demonstrated for the first time that model solutes of different sizes (dextran macromolecules from 4.4

87 to 155 kDa) were able to diffuse inside bacterial colonies of L. lactis, immobilized in two different

88 models of solid food matrices (model cheese and agar). The principle of this static design was to

89 deposit a solution of the fluorescently-labelled diffusing solute on the upper side of a gel cassette®

90 (Brocklehurst et al., 1995) filled with the solid medium, previously inoculated with L. lactis. The gel

91 cassettes® were then directly observed by confocal laser microscopy and the corresponding relative

92 fluorescence intensity profiles within the colony versus in the surrounding media were quantified

93 after 3 h of diffusion of the fluorescent solutes at 19°C. It was concluded that colonies of L. lactis

94 LD61 immobilized in the model cheese were porous to all dextrans from 4 to 155 kDa after this delay

95 of migration, but no kinetic aspect of diffusion could be assessed.

97 The objective of the present work was to determine how diffusion phenomena inside colonies vary

98 depending on both the properties of solutes and L.lactis strain. We quantified the diffusion rates of

99 solutes of different sizes and physico-chemical properties both around and inside colonies

100 immobilized in a model cheese, for two Lactococcus lactis strains presenting different surface

101 properties. Our experimental device was improved by adapting the time-lapse microscopy method

102 described in Rani et al. (2005), originally developed to determine the effective diffusion coefficients

103 of fluorescent tracers into biofilm cell clusters of Staphylococcus epidermis and their surrounding

104 solution.

106 2. Materials and Methods

108 2.1. Bacterial strains and growth conditions

109 Lactococcus lactis subsp. lactis biovar diacetylactis LD61 was used (collection of the Centre

110 International de Ressources Microbiennes-Bactéries d'Intérêt Alimentaire (CIRM-BIA), INRA,

111 Rennes, France) and was routinely grown under static conditions in M17 lactose broth (Difco, Becton

112 Dickinson, Le Pont de Claix, France) at 30°C.

113 Lactococcus lactis subsp. lactis TIL1230 was kindly given M-P Chapot-Chartier and obtained from

114 the parental strain NCD02110 (Giaouris et al., 2009). This strain was lactose and protease negative

115 and was then grown under static conditions in M17 lactose broth supplemented with 0.5 % glucose

116 (Sigma) at 30°C. Therefore, to ensure its optimal growth in milk, the milk cultures of TIL1230 were

117 supplemented with 1% glucose (Sigma) and 0.3% peptone casein (BD).

119 2.2 Bacterial surface characterization

121 2.2.1. Cell surface hydrophobicity

122 Net surface charge of the bacteria and the presence of lipophilic compounds affect partitioning

123 between two immiscible liquids (Burgain et al., 2014). The microbial adhesion to solvents (MATS)

124 method was employed for the evaluation of the hydrophobic/hydrophilic character of the cell surface

125 of L. lactis strains and for their Lewis acid-base characteristics. On this basis, we selected

126 chloroform, a monopolar and acidic solvent (electron acceptor) and hexadecane, an apolar alkane

127 using the protocol fully described in Giaouris et al. (2009). The values of MATS obtained with the

128 chloroform were regarded as a measure of electron donor/basic characteristics of bacteria. Adhesion

129 ability of the bacteria to the solvent is expressed as a percentage (%) according to the following

130 relation:

^~initial aqueous phase ^~aqueous phase after mixing -lo-i OA nrlhoain-rt — UU*00_~uu400__/i\

131 /0 """"LU,L ~ nninitial aqueous phase V1^

132 With OD the optical density of the bacterial suspension measured at 400 nm. Each measurement was

133 performed in triplicate and the experiment was repeated twice with independent bacterial cultures.

135 2.2.2. Cell surface charge

136 The electrophoretic mobility (EM) was measured to determine the cell surface net charge of the two

137 bacteria according to the protocol described in Boonaert & Rouxhet (2000). EM of the bacteria with

138 the appropriate pH values were measured at room temperature on a Zetameter model (Zeta Sizer

139 Nano Series, Malvern Instruments Ltd, Malvern, UK). Experiments were made twice with

140 independent culture with triplicate measurements. EM was expressed in 10-8 m2/V.s.

142 2.3. Preparation of the model cheese in imaging chambers

143 A fat-free cheese made from renneted concentrated skim milk was used as model cheese, as

144 previously described in Floury et al. (2013). This non-fat model cheese has the great advantage over

145 traditional cheese technology to be a repeatable and homogeneous cheese matrix. Moulded after

146 renneting, it is coagulated without further syneresis of the gel, thus exhibiting highly reproducible

147 micro- and macro- structural properties. The concentrated milk was inoculated for a final

148 concentration of 105 CFU/ml, and coagulant agent (Maxiren 180; DSM Food Specialities, Seclin,

149 France) was added at a final concentration of 300 p,l/l. After homogenization, 400 (il of the mixture

150 was slowly poured into several CoverWell imaging chambers (Sigma-Aldrich, Saint-Quentin

151 Fallavier, France) that allow direct observation under the confocal microscope (Floury et al., 2012).

152 The imaging chambers with the model cheese were then vertically incubated at 30°C for 15h for

153 coagulation and growth of the L. lactis LD61. For the L. lactis TIL1230, imaging chambers were also

154 vertically incubated, for 8h at 30°C and then for 15 h at 19°C. In parallel, the same media were also

155 inoculated in 30 ml-bottles to measure the pH during acidification by L. lactis. The pH of the model

156 cheeses were 5.05±0.06 and 5.32±0.10 for LD61 and TIL1230, respectively, after 15 h of incubation.

158 2.4. Fluorescent dyes and labelled solutes

159 SYTO9™ was added before coagulation of the model cheese to a final concentration of 1.2 (xmol/l, in

160 order to dye the bacterial cells and to visualize colonies within the opaque matrix of cheese.

161 SYTO9™ penetrates all bacterial membranes and dies all the bacterial cells, alive and damaged

162 (Boulos et al., 1999).

163 Three Rhodamine B isothiocyanate (RITC) conjugated dextrans of 10, 70 and 155 kDa were chosen

164 as model of flexible and neutral polymers of anhydroglucose of different sizes (Table 1), labelled

165 with an extent of labelling from 0.002 to 0.015 mol RITC per mol glucose (Sigma-Aldrich, Saint-

166 Quentin Falavier, France). RITC-dextrans were dissolved to 50 mg/ml in distilled water.

167 The studied set of solutes was completed with three milk proteins, one random coil milk protein, the

168 aS1-casein (INRA, Rennes, France), and two globular dairy proteins, bovine serum albumin (BSA,

169 Sigma-Aldrich, Saint-Quentin Falavier, France) and lactoferrin (LF, Fonterra Boulogne-Billancourt,

170 France). The proteins were labelled with free RITC (Sigma) using the protocol described in Silva et

171 al. (2013). The three solutions were lyophilized and labelling efficiencies were determined by mass

172 spectroscopy. BSA, LF and aS1-casein were mainly mono-labelled with RITC. Finally, the RITC-

173 labelled solutes were either dissolved to 50 mg/ml in water for the dextrans and the lactoferrin, in a

174 permeate solution obtained from the ultrafiltration of skimmed milk for aS1-casein, and in a 0.1 M

175 BisTris buffer at pH 6.8 for the BSA.

176 The solutions of labelled solutes were stored at -20°C, protected from light before and during

177 fluorescence measurements.

178 Physicochemical properties of the solutes are summarized in Table 1.

180 Table 1: Physicochemical properties of the fluorescently-labelled solutes

Dextran BSA Lactoferrin aS1-casein

10 70 155

Molecular Weight (kDa) 10 70 155 66.41 772 23.63

Isolectrical point - - - - 51 8-92 4.944

Hydrodynamic radius (nm) 2.35 65 8.55 3.65 2.26 2.93

Flexibility flexible rigid flexible

Hydrophobicity hydrophilic hydrophobic amphiphile

1Bohme and Scheler (2007); 2Bokkhim et al. (20 13); 3Marchin (2007);

182 4values reported by ; 5values reported by Sigma-Aldrich; supplier data online;

183 6Chaufer et al. (2000)

186 2.5. Experimental device for solute diffusion

188 2.5.1. Experimental set-up

189 After the incubation time necessary for bacterial growth, a concentration gradient of the

190 fluorescently-labelled solutes between the surface of the imaging chamber and the model cheese was

191 triggered in order to induce the diffusion phenomenon. Five (il of the fluorescently-labelled dextran

192 or protein solution was dropped off at the surface of the coagulated model cheese and left to diffuse

193 for 5 min throughout the surrounding medium, in the dark and in an air-conditioned room at 19°C.

194 Solute diffusion into the model cheeses began as soon as the fluorescent solution was left in contact

195 with the surface of the cheese (t = 0). The fluorescent solutes diffuse into the gel by a plane one-

196 dimensional diffusion mechanism (Figure 1).

198 2.5.2. Time-lapse confocal laser scanning microscopy

199 Model cheese samples were imaged on an inverted NIKON Eclipse-TE2000-C1si microscope

200 allowing confocal laser scanning microscopy (NIKON-France, Champigny sur Marne, France), with

201 an oil-immersion 40x objective at 512x512 pixel resolution. Ten minutes after the deposit of the

202 fluorescent solution containing the diffusing solutes, the first step was to localize a fluorescently

203 (SYTO9™) labelled colony, that had grown both in a focal plane at 10-15 [im depth from the

204 coverslip and at a quite close distance from the surface of the gel, in order to visualize the diffusion

205 front of fluorescence of the RITC-labelled solutes in a reasonable time-scale. SYTO9™ fluorescence

206 was excited with the 488 nm laser and detected between 500 and 530 nm. The second step was to

207 obtain the kinetic of the diffusion process of the RITC labelled solutes thanks to the acquisition of

208 images of the fluorescent front of diffusion around and into the target bacterial colony every 5 to 15

209 min for at least 2 h. Fluorescently RITC-labelled dextrans and proteins were excited at 543 nm

210 wavelength, and fluorescence emission was detected between 565 and 615 nm. All experiments were

211 performed at 19°C using a temperature-regulated platform and air-conditioned room and were

212 performed at least in triplicate.

214 2.5.3. Estimation of diffusion coefficients

215 Images obtained after a time series of acquisition were analyzed using ImageJ software. A line

216 measuring 512 pixels long and 10 pixels wide was drawn through the axial diameter of the colony in

217 order to quantify the profile of RITC fluorescence intensity (also named grey-level value) along the

218 direction of the diffusion front and at each acquisition time. The resulting fluorescence intensity

219 profiles versus time were then exported into a single spreadsheet.

220 According to Crank (1975), in the case of a plane one-dimensional diffusion, induced by an

221 instantaneous source and after a short time t of diffusion, the concentration gradient of the

222 investigated solute is given by the following relationship:

223 = )7=mexp{--$5i) (2)

224 where C is the concentration expressed as the amount of diffusing solute per unit area of surface, x is

225 the perpendicular axis to the surface of the model cheese in (xm (x=0 corresponded to the surface), t

226 is the time, D is the diffusion coefficient and M is the surface concentration of the diffusing solute,

227 which corresponds to the total amount of the investigated fluorescently labelled solute in the gel

228 related to the gel surface unit. This concentration M was considered as constant since it was in great

229 excess compared to its concentration inside the cheese and as there was no reaction between the

230 investigated component and the model cheese.

231 Equation (2) can be linearized:

232 Ln(c(x»=Ln/)M-ik (3)

233 The diffusion coefficient D was estimated from the slope of the straight line Ln (C(x)) versus x2,

234 equal to -1/(4Dt). The slopes of the lines inside and outside the colonies were obtained by performing

235 a linear regression with the best-fit linear trend function in Microsoft Excel using the least-squares

236 method. Two effective diffusion coefficients Dout and Din were quantified from the concentration

237 profiles around the bacterial colony (Dout) and inside the bacterial colony (Din). Both Dout and Dj„

238 were determined from the concentration profiles (grey values or fluorescence intensity profiles)

239 obtained at a short time of diffusion, i.e. 30 min after the deposit, of the fluorescent solution at the

240 surface of the model cheese.

242 2.6. Statistical analysis

243 One-way analysis of variance (ANOVA) and Tukey's paired comparison test were applied to the

244 diffusion coefficient data in order to determine which mean values were significantly different from

245 one another at the 95% confidence level using the R software package (version R i386 3.0.2).

247 3. Results and Discussion

248 3.1. Surface of both lactoccoci strains are hydrophilic, but TIL1230 is more electronegative

249 than LD61 at the pH of the model cheese.

251 The first step of the strategy of this study was to determine the hydrophobic/hydrophilic character,

252 Lewis acid-base interactions, and electrostatic cell surface properties. The microbial adhesion to

253 solvents method and electrophoretic mobility measurements gave us information on the potential

254 ability of the two L. lactis strains to generate physicochemical interactions between both the cheese

255 matrix and the diffusing solutes.

256 Results of the MATS method are reported in Table 2.

257 Table 2: Results of the microbial adhesion to solvents (MATS) method

260 261 262

280 281 282

L.lactis strain % of adhesion to :

hexadecane chloroform

LD61 8.6 ± 5.2 (n=4) 11.3 ± 9.8 (n=3)

TIL1230 12.8 ± 5.3 (n=6) 13.7 ± 2.5 (n=5)

The results are expressed as the mean ± one standard deviation of n indepenc

ent measurements

The partitioning of cells between aqueous and hexadecane is a direct measurement of the cell surface hydrophobicity or hydrophilicity. The surface property of a cell can be considered as hydrophilic if its affinity for apolar hexadecane is below 40% (Giaouris et al., 2009). As shown in Table 2, the percentage of adherent cells to hexadecane was slightly higher (not significantly) for TIL1230 than for LD61, with values largely inferior to 20% for both L. lactis strains, demonstrating a clear hydrophilic character of their surface. The hydrophilic character of bacteria is largely due to the nature of the compounds present on the surface, useful for adhesion (Burgain et al., 2014). The percentages of bacterial adhesion to the chloroform, an acidic solvent and electron acceptor, were not significantly different between the two L. lactis strains, with values also inferior to 20% (Table 2). These results are in agreement with values of adhesion to chloroform obtained on various L. lactis strains by Ly et al. (2006) and Giaouris et al. (2009).

The electrophoretic mobilities (EM) of the two L. lactis strains at different pH values indicated that the isoelectric points were around pH 2.5 and 4.5 for TIL1230 and LD61 strains, respectively (Figure 2). Between pH 2 and 6, the EM of L. lactis TIL1230 drastically decreased by about 4x10-8, whereas it decreased only 0.4x10-8 m2/V.s for LD61. L. lactis TIL1230 has a greater EM above pH 3 than LD61. Interestingly, LD61 strain presented EM very close to zero at all pH values tested, revealing very low electronegative cell surface in those conditions. In contrast, L. lactis TIL1230 was found to be highly negatively charged at pH between 4 and 6, as previously observed for most of L. lactis strains, with same order of magnitude for EM values, ranging from -2 to

-5x10 8 m2/V .s (Habimana

et al., 2007; Ly et al., 2006; Giaouris et al., 2009). Giaouris et al. (2009) reported for the first time that some lactic acid bacteria possess a very low surface electronegativity around neutral pHs, as observed here for L. lactis LD61. This diversity in the global charge of lactococcal cell surface may be linked to the variability of the molecules containing ionized groups in the cell envelope. Three types of ionized groups are considered to determine the surface electrical properties of L. lactis: phosphate groups present in teichoic and lipoteichoic acids, and carboxylate and protonated amino groups of proteins (Boonaert and Rouxhet, 2000). It has been previously shown that the expression of the major cell wall-anchored protease was responsible for altering L.lactis surface physicochemical properties, shifting the cell envelope from a hydrophilic surface to an extremely hydrophobic one, going along with an increase of negative charges at the cell surface (Habimana et al., 2007). In the present study, the two strains of L.lactis LD61 and TIL1230 were thus supposed to present greater differences in their cell surface properties as TIL1230 does not possess the cell wall protease and LD61 does. Obviously, the global property of the cell surface is multi-causal and then difficult to predict.

292 Bacterial cell wall properties were shown to affect diffusion particles of nanoparticles inside biofilm

293 matrices of L.lactis (Habimana et al., 2011). They measured that the diffusion of 50-nm radius

294 particles of anionic carboxylate-modified fluorescent polystyrene beads was more hindered in biofilm

295 matrix of L.lactis which possessed the anchored protease. Based on these results, the present study

296 aimed at comparing the diffusion of solutes of different charge, flexibility and hydrophobicity, inside

297 immobilized colonies (in cheese) of two different L.lactis strains presenting (LD61) or not (TIL1230)

298 the anchored protease in their cell walls.

300 3.2. Diffusion coefficients of dextrans inside the colonies depend on the solute size but not on

301 the lactococci strains.

303 Figure 3A shows typical confocal microscopic observations of L. lactis colonies, immobilized in the

304 model cheese, and visualized at different times after the deposit of the 70 kDa fluorescently-labelled

305 dextran solution. The images obtained with L. lactis TIL1230 and the two other fluorescently-

306 labelled dextrans (10 and 155 kDa) were similar and are thus not shown here. Both lactococci strains

307 grew in this model cheese as perfect spheres with diameters around 30-40 (xm, as previously reported

308 in Jeanson et al. (2011) and Floury et al. (2013). Figure 3A also clearly shows the progressive

309 increase of the red fluorescence both along the x-axis and through time, proving that the fluorescent

310 solute progressively moved inward toward a Lactococcus colony because of the concentration

311 gradient between the surface and the interior of the model cheese. After 2h of diffusion (Figure 3B),

312 the red color was uniform in all the directions around the colony, meaning that the concentration of

313 the fluorescently-labelled solute had reached a plateau. The diffusing process ended because there

314 was no more concentration gradient in this area. The simple observation of these time series of

315 images also suggests that the hypothesis of unidirectional diffusion of solute is valid. Therefore,

316 image analysis of the intensity profiles of red fluorescence along this x-axis allowed to directly

317 quantifying the diffusive penetration of the solutes as a function of time (Figure 3B). Typical

318 fluorescence intensity profiles were obtained (Figures 4A to 4C) at different times (between 20 and

319 150 min). Only an example of the fluorescence intensity profiles obtained with TIL1230 strain was

320 shown on Figure 4D because the profiles were very similar to those obtained with LD61.

321 From all these fluorescence intensity data as a function of the position and the time of diffusion, we

322 calculated the corresponding relative fluorescence intensity by dividing the fluorescence intensity at

323 each position x by the average fluorescence intensity obtained on the region upstream the colony. An

324 example is given on Figure 4E for the diffusion of the 70 kDa dextran in a colony of L. lactis LD61.

325 The relative fluorescence intensity profiles obtained with the other dextrans and with the other strain

326 were very similar (data not shown). The purpose of this graphical representation of the results was to

327 observe the evolution of the ratio of the fluorescence intensity in the colony versus outside the colony

328 as a function of time.

329 As shown on Figure 4E, whatever the time of diffusion considered, the fluorescence intensity inside

330 the colony of both L. lactis strains drastically dropped compared to the fluorescence intensity in the

331 surrounding cheese matrix, with a quite constant ratio around 0.4-0.6 depending on the x-axis

332 position inside the colony. We previously showed that even the fluorescently-labelled solutes diffuse

333 inside a bacterial colony (Floury et al., 2013), but do not penetrate into the bacterial cells.

334 Furthermore, dextrans are not metabolized by lactococci cells. Thus the only way to explain this drop

335 of relative fluorescence intensity inside the colony is because on the line of 10-pixel wide (Figure

336 3B), the volume filled with the fluorescent solution is lower inside the colony than outside the colony

337 due to the presence of the bacterial cells (corresponding to black zones with no fluorescence

338 intensity). So even if the experimental fluorescence intensity is different, the real concentration of the

339 fluorescent solute is effectively the same both inside and around the colony. The calculated average

340 value represented by the relative fluorescence intensity profiles was quite stable along the x-axis

341 inside the colonies for the fluorescently-labelled dextran solutes (Figure 3B), and this was also true

342 whatever the time of diffusion considered (Figure 4E).

343 The concentration of the diffusing solute cannot be calculated from experimental data. The

344 fluorescent intensity is, however, proportional to the diffusing solute concentration. Then, assuming a

345 one-dimensional Fickian diffusion induced by an instantaneous source, the effective diffusion

346 coefficients both inside the colony and in the surrounding matrix could be estimated from the slope

347 of the linearization of the experimental fluorescence intensity profiles obtained a short time after the

348 beginning of the diffusive process, with D = — 8: from Eq. 3. A typical linearized curve and

349 the corresponding fitted equations obtained both outside and inside the colony are shown on Figure 5.

350 Regression coefficients of the linear models were generally higher than 0.9 in the surrounding matrix,

351 and slightly lower inside the colony with values around 0.7 because of a lower signal to noise ratio

352 inside colonies. The slope of the line was clearly higher inside than outside the colony (Figure 5),

353 suggesting that the diffusion of solutes was slower inside the colony. The diffusion of the fluorescent

354 solute was probably more hindered inside the colony, most likely because of the high volume filled

355 with the bacterial cells, than in the protein-network of the surrounding matrix.

356 The mean effective diffusion coefficients (Deff) of the different RITC-dextrans were obtained using

357 this modeling approach, both inside and outside the colonies of the two bacterial strains (Figure 6).

358 Deff were significantly (p < 0.05) lower inside the colonies than in the surrounding matrix. When Deff

359 were plotted against the hydrodynamic radius, linear relationships (R2 > 0.8) were obtained over the

360 molecular weight range of 10 to 155 kDa, both inside and outside colonies. The statistical analysis

361 (ANOVA) performed on the estimated values revealed that the values of Deff were not significantly

362 different (p < 0.001) between the two bacterial strains, meaning that dextran solutes diffused inside

363 both Lactocci colonies with a similar diffusion coefficient, which depended mainly on size of the

364 solute. The absence of significant difference between both L. lactis strains was expected because

365 dextrans are known to be hydrophilic macromolecules and the surface properties of the two different

366 cells were shown to be also both very hydrophilic.

367 In the present study, we went further than the previous study (Floury et al., 2013) by visualizing the

368 kinetic of the diffusion process inside the colonies. Moreover, we were able to estimate diffusion

369 coefficients of the dextran solutes inside the microbial colonies from image analysis of the data. As

370 shown in Table 3, whatever their size between 10 and 155 kDa and the Lactoccocus strain, the

371 effective diffusion coefficients of dextrans obtained inside the colonies were around twice lower than

372 their respective diffusion coefficients in the surrounding cheese matrix around the colonies, and up to

373 50 times smaller than those in water Dw (calculated from the Stokes-Einstein equation). Silva et al.

374 (2013) also found that effective diffusion coefficient values of fluorescein isothiocyanate (FITC)-

375 dextrans (from 4 to 2000 kDa) in the same model cheese, but not inoculated, were smaller than those

376 in water due to the hindrance of the protein network. However, their values of effective diffusion

377 coefficients were between 4 and 9 times larger than in the present study, depending of the size of the

378 dextran.

379 The variability observed has two major causes. The first source of variability is the experimental

380 approaches used to estimate diffusion coefficients (Floury et al., 2010). Effective diffusion

381 coefficients estimated thanks to the concentration profiles method in the present method are then

382 difficult to compared to the so called "self-diffusion" coefficients obtained using the FRAP technique

383 in Silva et al. (2013).

Table 3: Calculated ratios of effective diffusion coefficients of dextrans obtained inside and outside L. lactis colonies (Din/Dout), of diffusion coefficients of dextrans in water* versus inside colonies (Dw/Din), and corresponding tortuosity indices, calculated as square root of Dw/Din.

Dextran MW (kDa) Din/Dout Dw/Din Tortuosity index

L.lactis strain

LD61 TIL1230 LD61 TIL1230 LD61 TIL1230

10 0.54 0.52 43 50 6.6 7.1

70 0.50 0.40 20 32 4.5 5.7

155 0.40 0.34 32 43 5.7 6.5

Dw values at 20°C calculated by using t

ie Stokes-Einstein relationship

The second source of variability is the model cheese. Indeed, even if the model cheese had the same initial composition in both studies, the metabolism of the lactococci inoculated in the present study induced a strong decrease of cheese pH from 6.6 to 5.1-5.3, depending on the L. lactis strain, which probably modified to some extent the microstructure of the protein network and then the diffusion behavior of the solutes in both cheeses.

In agreement with our results, Guiot et al. (2002) and Thurnheer et al. (2003) observed that the diffusion coefficients of fluorescently-labelled dextrans from 3 to 70 kDa also decreased linearly with hydrodynamic radius in different mono- and poly-species biofilms, and were up to 150 times smaller than those in bulk water. However the direct comparison of their results with our study is difficult because the microbial cell distribution is rather different in a biofilm and in a food matrix such as cheese. To our knowledge, only two studies are realistically comparable to our system (Rani et al.,2005 and Takenaka et al.,2009). They focused the analysis of the solute diffusion exclusively within identified clusters of microbial cells inside different model oral biofilms. The diffusive penetration of two tracer molecules (rhodamine B and fluorescein, MW ~ 400 Da, chosen as model of antibiotic for their similar size), into staphylococcal cell clusters was directly visualized by confocal scanning laser microscopy (Rani et al., 2005). The effective diffusion coefficients of the two fluorescent tracers were around 10 times lower than the corresponding solute diffusion coefficient in water. The difference with the present study could be due to a denser population of cells in our colonies. The diffusive penetration of fluorescently-labelled dextrans of various molecular weights (from 3 to 70 kDa) was visualized into three different species of cell clusters formed by oral bacteria grown in a flow cell (Takenaka et al.,2009). Like in the present study, the effective diffusion coefficient of dextrans strongly decreased with their molecular weights. However, their order of magnitude was different from our results, with effective diffusion coefficients only twice smaller than those in water. For Thurnheer et al. (2003), analysis of diffusion phenomena within biofilms suggested tortuosity as the most probable factor responsible for retarded diffusion compared to water. They defined a tortuosity index, as the square root of Dw/Din, representing an indicator of solute diffusion through interstitial space between bacterial cells. A molecule going through a highly convoluted three-dimensional route in a matrix will be delayed in comparison with free diffusion in water. As shown in Table 3, the tortuosity indexes estimated from our experimental data were of the same order of magnitude regardless of the L. lactis strain and the size of the diffusing dextran solutes. In our conditions, the extracellular space between the lactococci cells within the colony is filled with an aqueous phase composed of water, lactose and minerals (Floury et al. 2013), thus explaining why the tortuosity index did not depend on the size of the dextrans.

421 In conclusion about the diffusion of dextrans within bacterial colony, we confirmed that

422 macromolecules as large as dextrans of 155 kDa diffused into lactococci colonies in a model cheese

423 (Floury et al., 2013). We demonstrated that their diffusion was similar for two different strains of

424 lactoccoci whatever the size of dextrans up to 155 kDa.

425 3.3.Milk proteins, such as BSA, lactoferrin and aS1-casein, do not diffuse inside neitherLD61

426 nor TIL1230 lactococci colonies

427 The typical fluorescence intensity profiles for three fluorescently-labelled proteins, and typical

428 images of the corresponding colonies at the end of the experiments are shown on Figures 7, 8 and 9.

429 Whereas the fluorescence intensity of the three proteins outside the colonies increased with time, the

430 fluorescence intensity measured inside the colonies was very low all along the duration of the

431 experiments. The increase of the fluorescence intensity throughout time outside the colonies shows

432 that the three labelled-proteins effectively diffused in the surrounding cheese matrix. Whereas the

433 fluorescence outside the colonies was finally intense, the observation of the micrographs clearly

434 confirmed the intensity profiles by the absence of fluorescence inside the colonies. This means that,

435 surprisingly, none of the three proteins could diffuse inside the bacterial colonies, although their

436 hydrodynamic radii were much smaller than the radius of the largest dextran (Table 1). Concerning

437 the diffusion of proteins in cell clusters, to our knowledge the only published study is from Takenaka

438 et al. (2009).Contrary to our results, they clearly visualized by time-lapse confocal microscopic

439 observations that fluorescently-labelled proteins, even the largest like ConA (MW 104 kDa) and IgG

440 (MW 150 kDa), diffused inside microbial cell clusters that were approximately a few hundred

441 micrometers in diameter and reached the center of these cell clusters in less than 3 min.

442 These results highlighted that the size of the diffusing solute was not the sole factor conditioning its

443 ability to enter inside colonies of L. lactis immobilized in cheese. Other physicochemical factors such

444 as flexibility, charge and/or hydrophobicity of the solute can also be of involved, by generating

445 bacteria-solute interactions of different nature, especially for diffusing solutes such as milk proteins.

446 Moreover, the impact of these factors can also depend on the surface properties of the strain

447 (Habimana et al., 2011).

448 When diffusing through a non-inoculated model cheese, the rigid and globally negatively charged

449 BSA protein was hindered more than dextrans with a similar hydrodynamic radius, because of the

450 existence of solute-matrix interactions (Silva et al., 2013). In the same way, deBeer et al. (1997) and

451 Takenaka et al. (2009) reported that diffusion coefficients of solutes in different kinds of cell clusters

452 were conditioned on the network structure in the interstitial space, but also mainly depended on the

453 size and the charge of the diffusing solute. Unlike dextrans that are flexible, neutral and hydrophilic

454 polymers, proteins possess different shapes, hydrophobicity, and charges (Table 1). Moreover, even

455 if the surface of the cells of the two L. lactis strains were shown to be both hydrophilic, L. lactis

456 TIL1230 was more electronegative than LD61 at the pH of the model cheeses. Therefore, we could

457 have expected the surface properties of bacterial cells to influence the ability of solutes to diffuse or

458 not inside the colony by generating either repulsive or attractive interactions like electrostatic forces,

459 depending on the charge of the solute (Burgain et al., 2014). The pH of the model cheeses were

460 around 5.1 and 5.3 for LD61 and TIL1230, respectively. Therefore, according to the isoelectric point

461 of the proteins (Table 1), the net charges of BSA and a-S1 casein were slightly negative, whereas LF

462 was globally positively charged in both cheese matrices. Electrostatic repulsions could have then

463 occurred between the outer bacterial cells of the colony and the negatively charged solutes,

464 preventing their diffusion inside colony. However, it is largely known that cheese is a medium

465 presenting a high ionic strength (around 100 mM). In that case, the Debye length is very small

466 (around 2 nm) and then the energy barrier due to repulsive forces is very low, meaning that the

467 electrostatic contribution is strongly suppressed (Burgain et al., 2014). Interactions of electrostatic

468 nature were not explaining the non-ability of the three milk proteins to penetrate inside L.lactis

469 colonies immobilized in cheese. Other kind of repulsive forces such as hydrophobic interactions can

470 be involved, especially between the hydrophobic BSA and LF proteins and the hydrophilic surfaces

471 of the cells of both L.lactis strains. However, for the amphiphilic a-S1 casein, there was no reason for

472 repulsions of hydrophobic origin with the bacterial surfaces.

473 We were finally not able to explain why a-S1 casein proteins could not diffuse inside the lactococci

474 colonies. However, it is well known that milk caseins, especially the a-S1 casein, are hydrolyzed by

475 the cell wall proteases of L.lactis in cheese and/or other proteases present in the cheese. We can thus

476 hypothesize that some of the generated peptides can diffuse inside colonies, and are further

477 metabolized into smaller peptides and amino acids by all the cells located inside the colonies, as

478 strongly suggested by the results obtained in the same model cheese by Le Boucher et al. (submitted).

479 4. Conclusion

481 Effective diffusion coefficients of dextran macromolecules were quantified for the first time inside

482 colonies of two different L.lactis strains immobilized in a model cheese. We clearly showed that the

483 diffusion behavior of macromolecules through bacterial colonies immobilized in a model cheese not

484 only depends on the size of the diffusing solutes, but also and mainly on their physicochemical

485 properties. Whereas a flexible and neutral hydrophilic polymer such as a dextran can diffuse inside

486 colonies whatever its size, none of the three proteins investigated in this study could penetrate inside

487 lactococci colonies. These original results remain unexplained because both the surface of the two

488 bacterial strains and the three diffusing proteins presented various physicochemical properties, from

489 rigid to flexible shapes, and from negatively to neutral and positively charged. Our results finally

490 show that the choice of the fluorescently-labelled molecule as a model of diffusing solute is crucial.

492 Acknowledgments

493 This study was part of the CheeseOmic Project co-funded by the regions Bretagne and Pays-de-la-

494 Loire and supported by Bretagne Biotechnologie Alimentaire (BBA) association.

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587 Figure legends

588 Figure 1: Diagram of the experimental device for monitoring the kinetics of diffusion of solutes

589 around and inside colonies immobilized in the model cheese

591 Figure 2: Variation of electrophoretic mobility as a function of pH for Lactococcus lactis LD61

592 (circles) and TIL1230 (squares). Cells were harvested in the stationary growth phase. Measurements

593 were made in 1 mM KNO3 solution on two independent sets of data; the bars represent the standard

594 deviations of mean values.

596 Figure 3: (A) Example of a time-lapse microscopic observations of a Lactococcus lactis LD61

597 colony immobilized in a model cheese after 24h of growth at a temperature of 30°C during diffusion

598 of a RITC-labelled dextran (here RITC-Dextran 70 kDa). L.lactis cells are colored in green, RITC-

599 dextran in red. (B) Focus on the microscopic observation of the fluorescence intensity of RITC-

600 dextran inside and around a L. lactis LD61 colony immobilized in a model cheese at t=120 min of

601 diffusion and the corresponding fluorescence intensity profile along a 10 pixels wide line versus

602 position x. Black zones in the colony corresponds to the L.lactis cells.

603 Figure 4: Profiles of fluorescence intensity during diffusion of RITC-dextran 10 kDa (A); 70 kDa

604 (B) and 155 kDa (C) in colonies of Lactococcus lactis LD61 and of RITC-dextran 70 kDa in

605 TIL1230 (D) as function of diffusion time (from 20 to 120 min). (E) Typical relative fluorescence

606 intensity profile obtained with RITC-dextran 70 kDa in LD61.

607 Figure 5: Typical linearized curve obtained 30 min after the deposit of the fluorescent solution

608 containing a 70 kDa dextran at the surface of the model cheese inoculated with Lactococcus lactis

609 LD61. Lines correspond to the linear fit of experimental data both outside (grey circles) and inside

610 the colony (red circles).

611 Figure 6: Plots of the mean effective diffusion coefficients (Deff) of dextrans 10, 70 and 155 kDa

612 versus their respective hydrodynamic radius, estimated from experimental data obtained after 30

613 min, both inside (open symbols) and outside (plain symbols) colonies of Lactoccus lactis LD61

614 (squares) and TIL1230 (triangles) in a model cheese. Lines = linear regression.

615 Figure 7: Fluorescence profiles of of fluorescently-labelled Bovine Serum Albumin (BSA), in

616 colonies of Lactococcus lactis LD61 (A) and TIL 1230 (B) at different times from 20 to 120 min

617 after the deposit at the surface of a model cheese and the corresponding microscopic observations of

618 the colony after 120 min of diffusion.

619 Figure 8: Fluorescence profiles of RITC-LF in Lactococcus lactis LD61 (A) and TIL1230 (B) from

620 20 to 150 min and corresponding microscopic observations of the colony after 150 min of diffusion.

621 Figure 9: Fluorescence profiles of RITC-aS1-casein in Lactococcus lactis LD61 (A) and TIL1230

622 (B) from 20 to 180 min and corresponding microscopic observations of the colony after 180 min of

623 diffusion.

Fluorescence Intensity Fluorescence Intensity

Fluorescence Intensity Fluoresence Intensity

time (rnin)

40 60 x{Mm)

40 60 x(nm)

40 60 x{nm)

40 , ,60