Article pp.207-220 du Vol.24 n°3 (2004)

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ARTICLE ORIGINAL ORIGINAL PAPER

Monitoring bacteria growth using their intrinsic fluorescence

L. Leblanc, É. Dufour*

UPRES Typicité des Produits Alimentaires, ENITA Clermont-Ferrand, site de Marmilhat, 63370 Lempdes, France

RÉSUMÉ

Suivi de la croissance des bactéries aux moyens de leur fluorescence intrinsèque

Les spectres d’émission de fluorescence de Lc. lactis, S. carnosus et E. coli ont été enregistrés sur des suspensions diluées (D.O._620nm = 0.05) entre 280 - 480 nm (excitation : 250 nm) et entre 305 - 400 nm (excitation : 270 nm) pen- dant la durée de leurs croissances. Les spectres enregistrés après excitation à 270 nm étaient attribués à la fluorescence des tryptophanes, alors que la fluorescence enregistrée entre 280 - 480 nm provenait principalement des acides aminés aromatiques des protéines et des nucléotides des acides nucléiques.

Les analyses en composantes principales (ACP) réalisées sur les jeux de don- nées renfermant les spectres d’émission de fluorescence, enregistrés après excitation à 250 et 270 nm, permettaient de discriminer les 3 phases principales de la courbe de croissance - phase de latence, phase exponentielle et phase stationnaire, pour les 3 souches bactériennes étudiées.

Les spectres de fluorescence des tryptophanes de Lc. lactis, S. carnosus et E. coli ont été rassemblés dans une seule matrice. Une seconde matrice a été construite à partir des spectres enregistrés après excitation à 250 nm. Il a été mis en évidence par ACP que les deux cartes factorielles définies par les composantes 1 et 2 discriminaient les bactéries respectivement selon leur identité et leur stade physiologique. Nous avons conclu que les spectres de fluorescence intrinsèque des bactéries renfermaient de nombreuses informations, portant sur l’identité et le métabolisme, qui peuvent être extrai- tes aux moyens des méthodes statistiques multivariées.

Mots clés

bactérie / métabolisme / croissance / fluorescence / fluorophore intrinsèque.

* Correspondence: dufour@enitac.fr.

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SUMMARY

The emission spectra of Lc. lactis, S. carnosus and E. coli were recorded on dilute suspensions (O.D._620nm = 0.05) between 280 - 480 nm (excitation: 250 nm) and between 305 - 400 nm (excitation: 270 nm) during the time course of their growth. The spectra recorded following excitation at 270 nm were assigned to protein tryptophan fluorescence, whereas the fluorescence recorded between 280 - 480 nm mainly originated from the aromatic amino acids of proteins and the nucleotides of nucleic acids. The principal component analysis (PCA) performed on the data sets containing emission fluorescence spectra showed that the spectra can be classified in 3 groups corresponding to the 3 main phases of the growth profile, i.e., lag phase, exponential phase and stationary phase, for the 3 investigated bacteria strains.

The tryptophan fluorescence spectra recorded during the growth of Lc. lac- tis, S. carnosus and E. coli were gathered together in one matrix. It was shown by PCA that the two maps defined by the principal components 1 and 2 discriminated bacteria as a function of identity and metabolic profile, respectively. It was concluded that the intrinsic fluorescence spectra of bacteria retain a large amount of information regarding bacteria identity and metabolic profile, that could be assessed by multivariate statistical methods.

Key words

bacteria, metabolism, growth, fluorescence, intrinsic fluorophore.

1 – INTRODUCTION

There is an increasing interest in the development of rapid methods for the determination of bacterial metabolic activity. In order to evaluate the microorganisms, fluorescent dyes such as acridine orange are often used for the detec- tion of viable cells. As this dye intercalates more strongly with single stranded nucleic acids such as mRNA, acridine orange is also an indicator for cell activity, i.e., the amounts of mRNA increase with greater cell metabolic activity. Fluo- rescein derivatives also are valuable dyes that have been extensively used to assess the viability, the enzyme activities, the membrane potential and the intracellular pH of bacteria (BREEUWER and ABEE, 2000). However, the addition of fluorescent dyes to the cells may impair their metabolism and the use of extrinsic fluorophores may not allow on-line measurements.

For all these reasons, it may be valuable to use the intrinsic fluorescence of cellular components to characterize the growth of bacteria. Indeed, proteins in bacteria, as well as in food products, show fluorescence of their tryptophan residues in the 300-400 nm range following excitation at 270-290 nm. It has been shown that fluorescent properties of tryptophan residues in proteins are useful for investigation of the structure of cheeses. Tryptophan fluorescence spectra of a cheese are fingerprints that allow identification of the cheese type.

Using front face fluorescence (HIRSCH and NAGEL, 1989) in combination with chemometric methods, we have developed methods allowing the identification

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of cheeses and the characterisation at the molecular level of dairy products (DUFOUR et al., 2000; HERBERT et al., 2000; HERBERT et al., 1999).

The nucleotides constituting nucleic acids are also fluorophores despite the fact that their quantum yields are about 100-times lower than the quantum yields of tryptophans (CANTOR and SCHIMMEL, 1980; DAWSON et al., 1986). Following excitation at 260 nm, a maximum emission wavelength is observed at about 334 nm. But phenylalanine, tyrosine and tryptophan residues of proteins also exhibit fluorescence at about 320-330 nm after excitation at 250-260 nm (CANTOR and SCHIMMEL, 1980). Recently, fluorescence spectroscopy has been shown to be a valuable technique for the identification of bacteria at the genus, species and strain levels (LEBLANC and DUFOUR, 2002). Indeed, it has been demonstrated that the fluorescence spectrum of a bacteria is the fingerprint of this bacterial strain.

The aim of this study was to investigate the potential of fluorescence spectroscopy in order to monitor the growth of three different bacteria using their intrinsic fluorescence.

2 – MATERIALS AND METHODS

2.1 Strains and growth conditions

Lactococcus lactis spp cremoris 102301T (CIP), Staphylococcus carnosus N˚756 (INRA) and Escherichia coli 54.8T (CIP), from Institut Pasteur and INRA collections, were investigated.

From the pure cultures kept at –20˚C (with glycerol), the bacteria were grown on agar plate at 30˚C (Lc. lactis) and 37˚C (S. carnosus and E. coli) for 24 h. One colony of each strain was harvested and then suspended into 5 ml BHI liquid medium. The 3 pre-cultures were grown for 12 h at optimal temperatures: 30˚C for Lc. lactis, (anaerobic conditions) and 37˚C for S. carnosus and E. coli (aero- bic conditions). BHI liquid medium was used for the cultures of the investigated bacteria since it allowed their optimal growth.

For Lc. lactis and S. carnosus, 2 ml of the pre-cultures were inoculated to 98ml of fresh BHI liquid medium, whereas the inoculation of fresh BHI liquid medium was 1.4% for E. coli. As determined by the plate count method, the inoculation yield corresponded to 1 to 3.10⁶ cells/ml. The strains were grown at 30˚C (Lc. lactis) and 37˚C (S. carnosus and E. coli) for 6 h. Thirteen aliquots were taken at 25, 50, 65, 80, 100, 140, 160, 210, 235, 275, 295, 340 and 390 min during the growth (T1-T13, respectively). At the end of the growth, cell numbers per ml ranged between 1.5.10⁹ and 5.10⁹. The cultures were realized in triplicate.

Absorbance of bacterial cultures was measured at 620 nm using a Cary 100 Bio UV-Visible spectrophotometer (Varian, Australia). Culture medium was removed by centrifugation at 5000 rpm for 10 min. Then, cells were washed twice with 5 mL of saline solution (NaCl, 9 g.L^-1) and centrifuged as previously described. Finally, the pellet was suspended in a define volume of saline solution in order to obtain an O.D._620nm = 0.05. This suspension was used for fluorescence experiments.

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2.2 Fluorescence spectroscopy

Fluorescence spectra of the bacteria samples were obtained using a Fluoro- Max-2 spectrofluorimeter (Spex-Jobin Yvon, NJ, USA) provided with a right angle cell holder. Bacteria samples were placed in a quartz cuvette. Emission fluorescence spectra (305-400 nm, resolution: 1 nm, slits: 3 nm) of tryptophan residues were recorded with excitation wavelength set at 270 nm. Emission fluorescence spectra (280 – 480 nm; resolution: 1 nm; slits: 4 nm) were also recorded with excitation set at 250 nm. In this condition, a large number of fluorophores may be excited. These setting mainly corresponded to the fluorescence properties of aromatic amino acids in proteins and nucleotides constituting nucleic acids (CANTOR

and SCHIMMEL, 1980). The spectra of each sample were recorded in triplicate using different aliquots. Samples from 3 different cultures were analyzed.

2.3 Mathematical treatment of data

The fluorescence spectra have been normalized by reducing the area under each spectrum to a value of 1 according to Bertrand and Scotter (1992). Princi- pal Component Analysis (PCA) was applied to the normalized spectra in order to investigate changes in the data (HERBERT, 1999; HERBERT et al., 1999). This statistical multivariate treatment makes it possible to draw score plots of the samples and to get spectral patterns (BERTRAND and SCOTTER, 1992; JOLIFFE, 1986). While the score plots allow the comparison of the spectra in such a way that two neighboring points represent two similar spectra, the spectral patterns exhibit the absorption bands that explain the similarities observed on the maps.

The discriminant ability of the data was investigated by applying Mahalano- bis distances to the spectral data. A group was created for each stage of the bacteria growth, i.e., the lag phase, the exponential phase and the stationary phase. The variable selection was realized following the classification percentage of the samples. When adding a supplementary variable did not significantly improve the classification percentage, the variable selection was finished.

Factorial Discriminant Analysis (FDA) was performed on the first 20 principal components resulting from the PCA applied on the fluorescence spectral data.

The aim of this technique is to predict membership of an individual bacterial sample following the definition of three qualitative groups: Lactococcus lactis, Staphylococcus carnosus and Escherichia coli. FDA were carried out using StatBoxPro (Grimmer logiciels, Paris, France).

3 – RESULTS AND DISCUSSION

3.1 Growth profiles of bacteria

The growth of the 3 different strains was followed by recording the absorbance at 620 nm during the time course of the culture. Figure 1 shows a typical profile for Lc. lactis growth. The curve exhibited 3 characteristic regions: the lag phase was followed by the exponential phase and finally a stationary phase was

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observed. Using standardised experimental conditions described in Materials and Methods, reproducible data were obtained for the 3 strains (data not shown). As previous studies have shown that the shape of the infrared spectrum is especially sensitive to the experimental procedures relative to growth conditions (CURK et al., 1994; ZEROUAL et al., 1994), such changes were expected in the fluorescence spectra.

Figure 1

Time course of the growth of Lactococcus lactis

Thirteen aliquots were taken at 25, 50, 65, 80, 100, 140, 160, 210, 235, 275, 295, 340 and 390 min during the growth (T1-T13, respectively).

3.2 Fluorescence spectra of bacteria in dilute suspension

The experimental conditions for recording the fluorescence spectra of bacteria in dilute suspensions were fixed in a first step. For tryptophan fluorescence spectrum, emitted photons were recorded between 305 and 400 nm following classical excitation at 290 nm (DUFOUR and RIAUBLANC, 1997). In these conditions

0 0.2 0.4 0.6 0.8 1

0 100 200 300 400

Time (min)

O.D. at 620 nm

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a Raman band was observed in the spectrum at 320 nm (data not shown). To eliminate this Raman band, the excitation wavelength was fixed at 270 nm with emission wavelengths ranging between 305 and 400 nm as mentioned above.

Three fluorescence spectra of tryptophans in Lc. lactis proteins are shown in Figure 2. The spectrum of the lag phase (T2) was characterized by a maximum emission wavelength at 343 nm, while the spectrum of the exponential phase (T8) was shifted by about 1 nm towards higher wavelengths. More dramatic changes were observed for the spectrum of the stationary phase (T12) exhibiting a maximum emission wavelength at 335 nm. Our results suggest that shape of a fluorescence spectrum of protein tryptophan residues is correlated to the physiological status of the bacteria.

Figure 2

Emission fluorescence spectra recorded following excitation at 270 nm for Lactococcus lactis during the time course of the growth: T2 ( - - -), T8 ( ^___ )

and T12 (x x x).

Figure 3 presents spectra recorded following excitation at 250 nm. This wavelength made it possible to excite a large number of fluorophores, but the resulting emission spectra were assigned mainly to the aromatic amino acids of proteins and the nucleotides of nucleic acids (CANTOR and SCHIMMEL, 1980).

They showed different shapes as a function of the physiology of the Lc. lactis cells and were characterized by a maximum and a shoulder at about 350 nm and 440 nm, respectively. Considering the spectrum of the lag phase (T2), the maximum was at 350 nm and the shoulder was observed at 445 nm. The maximum of the spectrum recorded during the exponential phase (T8) was slightly shifted towards higher wavelengths and the fluorescence intensity of the shoulder was higher than the one of the previous spectrum. Again the most important changes were observed for the spectrum recorded during the stationary phase (T12) with a maximum shifted by 10 nm towards lower wavelengths.

Once again, it appears that the intrinsic fluorescence spectra recorded during the growth could be considered as fingerprints.

0.00E+00 2.00E-02 4.00E-02 6.00E-02 8.00E-02 1.00E-01 1.20E-01 1.40E-01

305 325 345 365 385

Emission wavelength (nm)

Fluorescence intensity (a.u)

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Figure 3

Emission fluorescence spectra recorded following excitation at 250 nm for Lactococcus lactis during the time course of the growth: T2 ( - - -), T8 ( ^___ )

and T12 (x x x).

3.3 Relation between Lc. lactis growth profiles and the fluorescence spectra

Fluorescence properties of fluorophores are very sensitive to changes of their environment (MARANGONI, 1992). Considering the experiments performed on cheeses (DUFOUR et al., 2000; HERBERT, 1999; HERBERTet al., 2000), it has been shown that a spectrum permits characterisation and identification of cheeses varying in manufacturing process and stage of ripening. Despite the slight differences in the shapes of the recorded spectra, the potential of fluorescence spectroscopy in combination with chemometric methods to discriminate between cheese samples has been demonstrated (DUFOUR et al., 2000; HER- BERT et al., 2000).

As the spectra of the bacteria were recorded at different stages of the growth curve, it was assumed that the composition and the metabolic profile of bacteria, and as a consequence the environments of fluorophores, were different (HERBERT, 1999). Recently, we have shown strong correlations between the fluorescence spectra and the metabolic profiles determined using the Biolog system recorded on 30 isolates of Pseudomonas spp. (LERICHE et al., 2003). In this study, the fluorescence spectra permitted discrimination between the isolates and it was shown that the differences in fluorophore environments were related to the different metabolic profiles of the isolates.

In order to compare the set of fluorescence spectra and to emphasize the similarities and the differences underlined above, principal component analysis (PCA) was performed on the spectra to describe the main variations between the different physiological states of bacteria. Considering the 39 tryptophan spectra

2.00E-02 3.00E-02 4.00E-02 5.00E-02 6.00E-02 7.00E-02 8.00E-02 9.00E-02 1.00E-01 1.10E-01

285 325 365 405 445

Emission wavelength (nm)

Fluorescence intensity (a.u.)

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of Lc. lactis recorded during the growth, the first two principal components accounted for 75.2% and 23.6% of the total variance in the spectral data set. The score plot defined by the principal components 1 and 2 showed 3 groups corresponding to the 3 main physiological states, i.e., lag phase, exponential phase and stationary phase (figure 4). The principal component 1 separated the spectra recorded during the lag phase (T1 to T4) from that one recorded during the stationary and exponential phases. Whereas the stationary phase (T11 to T13) and the exponential phase (T5 to T10) were mainly discriminated according to the principal component 2. In a second step discriminant ability of the data was investigated by applying Mahalanobis distances method on the spectral data.

A good classification was observed for 100% of the samples using only one variable, i.e., 322 nm. This result is in agreement with the spectral pattern associated with the principal component 1 showing that the most discriminant wavelength for the data collection is located at 322 nm (figure 5). The spectral pattern 1 pre- senting a minimum at 322 nm and a maximum at 370 nm indicated that the environment of tryptophan residues was relatively more hydrophilic for the spectra recorded during the lag phase than those recorded during exponential and stationary phases. From the spectral pattern 2 associated with PC2, it was concluded that the width of fluorescence spectra was larger for spectra located on the positive side of the PCA score plot than those on the negative side.

Figure 4

Principal component analysis score plots determined by principal components 1 and 2 for the tryptophan spectra of Lactococcus lactis.

-0.01 -0.008 -0.006 -0.004 -0.002 0 0.002 0.004 0.006 0.008 0.01

-0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02

PC 2 (23.6%)

PC 1 (75.2%)

lag phase exponential phase

stationary phase T10

T9

T8 T6

T5 T7

T4

T1 T2

T3

T12 T13

T11

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Figure 5

Spectral patterns associated with the principal components 1 (⎯) and 2 (⋅⋅⋅⋅⋅) of the PCA performed on the tryptophan fluorescence spectra.

The 39 spectra of Lc lactis recorded following excitation at 250 nm were also evaluated by principal component analysis. The first and the second principal components took into account 85.44% and 9.35%, respectively, and discriminated the 3 main phases of the growth profile (data not shown). Indeed, the 3 groups observed previously were formed: T1 to T4, T5 to T10 and T11 to T13. But in this case, principal component 1 discriminated the exponential phase from lag and stationary phases, these two phases being discriminated according to the principal component 2. In a second step discriminant ability of the data was investigated by applying Mahalanobis distances method on the spectral data. A good classification was observed for 100% of the samples using 4 variables, i.e., 395 nm, 324 nm, 399 nm, and 396 nm.

The analysis of intrinsic fluorescence spectra recorded during the growths of S. carnosus and E. coli also showed a good discrimination of the different stages of the growth (data not shown). It is concluded that tryptophan and aromatic-amino-acids+nucleic-acids fluorescence spectra recorded during the growth are to be considered as fingerprints that can be classified in 3 groups corresponding to the 3 different phases of bacteria growth.

The characterization of the viability or of the metabolic profile of microorganisms during the manufacturing of fermented product is of a major importance. Considering viability, it is commonly determined by the plate count method. However, the time to form visible colonies is relatively long. Moreover, the viable plate count method can be impaired by clumping, inhibition by neighboring cells and composition of the growth media used (MASON et al., 1986). Therefore, there is an increasing interest in the development of rapid methods for the determination of cell viability or physiological status of bacteria. Fluorescence probes may be valuable tools in order to achieve these goals. Indeed, fluorescent probes are used for the determination of intracellular pH, membrane integrity, respiration and enzyme activities of bacteria (BREEUWER and

-0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2

300 320 340 360 380 400

Wavelength (nm)

A.U.

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ABEE, 2000; LEBRUN et al., 2001). But the addition of an extrinsic dye may be toxic and may alter the metabolism of the cells. Our results suggest that intrinsic fluorescence of bacteria could be well suited to the characterization of their physiological status. It is a rapid, low cost, non-invasive and non-destructive method. Another point to add here is that fluorescence measurements require only very small quantities of sample (nanomoles or less).

3.4 Discrimination of 3 different bacteria during their growth from their fluorescence spectra

The tryptophan fluorescence spectra recorded during the growth of Lc. lac- tis, S. carnosus and E. coli were gathered together in one matrix. A second matrix was build up from the spectra recorded following excitation at 250 nm.

Then, these two tables were analyzed by PCA. The aim of this approach was to evaluate the potential of intrinsic fluorescence in the discrimination of bacterial strains at different physiological states. The PCA score plots defined by principal components 1 and 2 for aromatic-amino-acids+nucleic-acids is presented Figure 6. For data on aromatic-amino-acids+nucleic acids fluorescence, as well as for tryptophan fluorescence (data not shown), the principal component 1 discriminated the 3 strains for the 2 score plots, whereas the physiologic states of the 3 bacteria were discriminated according to the principal component 2. This last point suggests that the fluorescence spectra recorded at any precise time of the cell cycle exhibit common features for the 3 bacteria. In addition, a good discrimination of the 3 different bacteria whatever their growth status was obtained from the intrinsic fluorescence spectra (Figure 7). It has been shown that the intrinsic fluorescence spectrum of a bacteria is a fingerprint characteris- ing a bacterial strain (LEBLANC and DUFOUR, 2002). The results presented also show that the spectra retain specific features allowing strain identification whatever its growth state.

Numerous intrinsic fluorophores can be found in bacteria cells. They include the aromatic amino-acids – tryptophan, tyrosine and phenylalanine in proteins, vitamins E, A and B₂, NADH derivatives of pyridoxal, some nucleotides… and numerous other compounds that can be found at low or very low concentra- tions. For example, riboflavin, a water-soluble vitamin that occurs naturally in bacteria, has a strong and broad fluorescence emission peak in the region 525- 531 nm. The monitoring of oxido-reduction status in bacteria is such a domain where fluorescence of riboflavin or NADH could have valuable input. This para- meter is critical for the development of micro-organisms and flavour compounds in fermented food products.

Fluorescence spectroscopy offers several inherent advantages compared with others spectroscopic methods such as infrared. First, fluorescence is 100- 1000 times more sensitive than spectrophotometric techniques. Second, fluorescence allows investigatation of a given molecule exhibiting well-defined excitation and emission wavelengths and the fluorescence properties of a fluorophore are extremely sensitive to its environment. Due to this environmental sensitivity, a fluorescence spectrum retains information on the protein con- tent (quantity and nature) of a cell, on the structure of proteins and on the interactions of proteins with other cell components. It can be considered as a fingerprint. Compared with infrared, the other major interest of fluorescence is the absence of signal from water. This major compound of the bacteria and of

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the samples is responsible for large contributions in near- and mid-infrared spectra requiring the dehydration of the sample prior the recording of a spectrum. Third, most fluorescence methods are relatively rapid. Diode array detec- tors or CCD camera allow recording of a spectrum in less than a second. In addition, the acquisition of spectra of a large number of samples can easily be automated by coupling a spectrofluorimeter and an plate-reader by a fibre optic.

Figure 6

Principal component analysis score plots determined by principal components 1 and 2 for the aromatic amino acids+nucleic acid spectra of Lactococcus lactis ( ),

Staphylococcus carnosus ( ) and Escherichia coli ( ).

-0.015 -0.01 -0.005 0 0.005

0.01 0.015

-0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 0.025 0.03

PC 2 (17.97%)

PC 1 (79.79%)

Bacterial growth

Staphylococcus carnosus

Lactococcus

lactis Escherichia

coli

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Figure 7

Discriminant analysis similarity map determined by discriminant functions 1 and 2 for the aromatic amino acids+nucleic acid spectra of Lactococcus lactis ( ),

Staphylococcus carnosus ( ) and Escherichia coli ( ).

4 – CONCLUSION

The potential of intrinsic fluorescence spectroscopy of dilute suspension of bacteria to monitor the growth of bacteria has been demonstrated. It appears that the intrinsic fluorescence spectra of bacteria retain a large amount of information regarding bacterial identity and metabolic profile that can be assessed by multivariate statistical methods (LEBLANC and DUFOUR, 2002; LERICHE et al., 2003). The most important advantage of the fluorescence technique we would like to specify is that there is no need for any extrinsic fluorophore to provide samples with specific properties that allow them to be examined. Therefore the intrinsic fluorescence technique provides unique information, which is a real reflection of the natural state of bacteria. It should allow the characterisation of the viability or of the metabolic profile of bacteria isolates used for the manufacturing of fermented products.

-0.400 -0.300 -0.200 -0.100 0.000 0.100 0.200 0.300 0.400 0.500

-0.800 -0.600 -0.400 -0.200 0.000 0.200 0.400

F1 (94%)

F2 (6%)

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5 – ACKNOWLEDGEMENT

We are grateful to Dr D. Bertrand (ENITIAA-INRA, Nantes) for the PCA and Mahalanobis distance programs.

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