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Applied and Environmental Microbiology, September 2008, p. 5662-5673, Vol. 74, No. 18
0099-2240/08/$08.00+0     doi:10.1128/AEM.00418-08
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

Polyphasic Approach to Bacterial Dynamics during the Ripening of Spanish Farmhouse Cheese, Using Culture-Dependent and -Independent Methods{triangledown}

Antonio M. Martín-Platero, Eva Valdivia, Mercedes Maqueda, Inés Martín-Sánchez, and Manuel Martínez-Bueno*

Departamento de Microbiología, Facultad de Ciencias, Fuentenueva s/n, 18071 Granada, Spain

Received 19 February 2008/ Accepted 15 July 2008


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ABSTRACT
 
We studied the dynamics of the microbial population during ripening of Cueva de la Magahá cheese using a combination of classical and molecular techniques. Samples taken during ripening of this Spanish goat's milk cheese in which Lactococcus lactis and Streptococcus thermophilus were used as starter cultures were analyzed. All bacterial isolates were clustered by using randomly amplified polymorphic DNA (RAPD) and identified by 16S rRNA gene sequencing, species-specific PCR, and multiplex PCR. Our results indicate that the majority of the 225 strains isolated and enumerated on solid media during the ripening period were nonstarter lactic acid bacteria, and Lactobacillus paracasei was the most abundant species. Other Lactobacillus species, such as Lactobacillus plantarum and Lactobacillus parabuchneri, were also detected at the beginning and end of ripening, respectively. Non-lactic-acid bacteria, mainly Kocuria and Staphylococcus strains, were also detected at the end of the ripening period. Microbial community dynamics determined by temporal temperature gradient gel electrophoresis provided a more precise estimate of the distribution of bacteria and enabled us to detect Lactobacillus curvatus and the starter bacteria S. thermophilus and L. lactis, which were not isolated. Surprisingly, the bacterium most frequently found using culture-dependent analysis, L. paracasei, was scarcely detected by this molecular approach. Finally, we studied the composition of the lactobacilli and their evolution by using length heterogeneity PCR.


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INTRODUCTION
 
Lactic acid bacteria (LAB) are functionally related by their ability to produce lactic acid via either homo- or heterofermentative metabolism. The acidification and enzymatic processes accompanying the growth of LAB impart distinctive flavors and textures to a wide variety of fermented dairy products, meats, and vegetables. In addition, their preservative qualities make these bacteria useful in the control of undesirable microorganisms (16). For this reason LAB have important applications in the food, agricultural, and medical sectors and have been the subject of considerable research and commercial development over the past decade. Lactobacilli are well represented in fermented milk, yogurt, and cheese, as either natural or intentionally added microbiota (starter cultures). Lactobacillus casei, Lactobacillus paracasei, Lactobacillus rhamnosus, Lactobacillus plantarum, Lactobacillus fermentum, Lactobacillus brevis, Lactobacillus buchneri, Lactobacillus curvatus, Lactobacillus acidophilus, and Lactobacillus pentosus are common members of the nonstarter LAB (NSLAB) communities in dairy products (11, 32, 35). In cheese NSLAB are represented mainly by L. casei and L. paracasei (5, 11, 20), but L. brevis, L. plantarum and L. curvatus are also important (4, 5, 43). Although these organisms are usually present at low levels in curd (102 to 103 CFU/g), their concentrations increase during ripening to 107 to 108 CFU/g (15, 21). NSLAB have been reported to be responsible for many of the flavor qualities of cheese, and their use as adjuncts to starter cultures might either improve taste or introduce off-flavors, depending upon the strains used (4, 38, 43).

Because complex interactions in the microbial community occur during milk curdling and cheese ripening, accurate identification of the microorganisms involved provides information essential for understanding their role in this process (7), which should lead to more objective criteria for the selection of strains for starter or adjunct cultures. However, LAB identification on the basis of phenotypic features is very difficult because of the great variation in the fermentation profiles of the organisms, which differ considerably for strains belonging to the same species. Identification is now approached by using DNA-based techniques, which allow workers to distinguish between different species with similar phenotypic characteristics and also between strains belonging to the same species. Among the various molecular techniques used for identification of LAB species are species-specific PCR (33), restriction fragment length polymorphism (8), and 16S rRNA gene sequencing (41, 42), and the latter technique is the technique most extensively used to identify species. For intraspecies characterization, pulsed-field gel electrophoresis (28), repetitive enterobacterial palindromic sequence PCR (9), and randomly amplified polymorphic DNA (RAPD) analysis (25) are the methods currently used for LAB isolates from foodstuffs and dairy products. Nevertheless, all of these molecular techniques are culture dependent. It is, however, well known that only a small proportion of microorganisms are culturable, and therefore culture-dependent techniques do not reflect real microbial communities (24). Consequently, different culture-independent techniques have been used for fermented foods and dairy ecosystems, mainly terminal restriction fragment length polymorphism analysis (44), length heterogeneity PCR (LH-PCR) (30), single-strand conformation polymorphism analysis (18), denaturing gradient gel electrophoresis (42), temperature gradient gel electrophoresis (10, 11), and temporal temperature gradient gel electrophoresis (TTGE) (3).

Cueva de la Magahá is a cheese made in the south of Spain (Jayena, Granada) from raw goat's milk inoculated with the starter cultures Lactococcus lactis and Streptococcus thermophilus. The aim of this study was to characterize the microbial communities isolated during the ripening process. The dynamics of microbial diversity was also studied by using the culture-independent techniques TTGE and LH-PCR; the latter was used to evaluate the Lactobacillus community, which provided a quick and easy way to fingerprint this bacterial group.


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MATERIALS AND METHODS
 
Sample preparation and microbiological analysis.
The samples analyzed in this study were obtained from three different cheeses from the same batch of Cueva de la Magahá cheese, a hard farmhouse cheese made in Jayena in the province of Granada (Spain) from raw goat's milk inoculated with starter cultures (EZAL MA-400; Rhodia Food, Sassenage, France). The curd of this cheese is processed by heating it to 37°C, cutting and molding, and then salting by immersion for 24 h in natural brine (20.4 to 22.2° Baumé; 25.6 to 28.3% NaCl) before it is ripened for 8 months by storage under controlled humidity (relativity humidity, 80 to 90%) and temperature (12 to 13°C) conditions. According to the starter manufacturer, EZAL MA-400 is composed of a mixture of L. lactis subsp. lactis, L. lactis subsp. cremoris, L. lactis subsp. lactis bv. diacetylactis, and S. thermophilus.

Before sampling, the cheeses were washed with water, and their rinds were removed. Ten-gram samples were collected aseptically from three cheeses from the same batch after 1, 17, and 34 weeks of ripening, and each sample was homogenized for 2 min in 90 ml of a prewarmed (37°C), sterile, 2% sodium citrate solution in a sterile plastic bag with a lateral filter, using a Stomacher lab blender (IUL Instruments, Barcelona, Spain). One milliliter of the resulting mixture was taken from the filtrate side, and 10-fold serial dilutions up to 10–7 were prepared using a sterile saline solution (0.8% NaCl). A 100-µl aliquot was spread in triplicate on agar plates for bacterial enumeration. The plates were incubated at 28°C for 4 to 7 days, and the bacteria were enumerated by counting colonies on different media, including Tween APT agar, M-17 agar, and brain heart infusion agar (BHA) (all obtained from Scharlab Barcelona, Spain) to estimate the total number of aerobic, mesophilic bacteria, Man-Rogosa-Sharpe (MRS) agar to estimate the number of LAB, Kenner fecal agar (KFA) to estimate the number of enterococci, Vogel-Johnson agar to estimate the number of staphylococci, and MacConkey agar to estimate the number of enterobacteria. The average counts for the replicate cheese samples and the standard deviations were calculated after log transformation. Additionally, between 10 and 20 LAB isolates (corresponding to the square roots of the total numbers of colonies) were randomly picked from general and selective medium plates and cultured on the corresponding media. The isolates were purified, examined to study their morphology, and Gram stained and tested for catalase activity before they were stored for further analyses at –70°C in the corresponding broth media supplemented with 35% glycerol.

Another strategy used in this study was based on the quantitative PCR (QPCR) most-probable-number assay for detection of LAB growth in enrichment cultures. For this, 10-g replicates of 34-week-old cheese were homogenized as described above, and the suspensions were serially diluted 10-fold in triplicate in tubes containing MRS broth and Rothe azide broth (Scharlau, Barcelona, Spain) and incubated without agitation at 28°C for 48 h. Rothe azide broth was used for primary enrichment of fecal streptococci due to the presence of sodium azide, which is both selective for enterococci and an inhibitor of the accompanying flora through interference with the electron transport chain. The most probable number was determined from the more diluted tubes showing turbidity. Tubes showing turbidity were selected for TTGE analysis or multiple specific PCR.

Genomic DNA isolation.
A suspension corresponding to 1 g of cheese was centrifuged for 5 min at 13,000 x g in a microcentrifuge, and the sediment was either stored at –70°C or used for extraction and isolation of genomic DNA as described by Martín-Platero et al. (34). The same method was used to extract DNA from pure cultures (34).

RAPD analysis.
The genotypes of all strains were determined using a RAPD-PCR procedure (40). The PCR was carried out using a 50-µl (total volume) mixture containing 5 µl of 10x Taq reaction buffer, 3 mM MgCl2, each deoxynucleoside triphosphate (dNTP) at a concentration of 400 µM, 1 µM primer M13 (5'-GAGGGTGGCGGTTCT-3'), 1 U of Taq DNA polymerase (MBL, Córdoba, Spain), and 5 µl of template DNA. Amplification was performed with an iCycler 170-8720 (Bio-Rad, Hercules, CA) using a program consisting of an initial denaturing step of 94°C for 60 s, followed by 35 cycles of 60 s at 94°C, 20 s at 40°C (with a 0.6°C/s ramp), and 80 s at 72°C (with a 0.6°C/s ramp) and then a final extension at 72°C for 5 min. The PCR products were analyzed by electrophoresis in 1.5% agarose gels at 30 V for 16 h in 1x TAE buffer (40 mM Tris-acetate, 2.5 mM EDTA; pH 8) and were revealed by staining with ethidium bromide (0.5 µg/ml). Gels were photographed under UV light and analyzed by using Fingerprinting II Informatrix software (Bio-Rad, Hercules, CA). A similarity matrix was constructed on the basis of the Pearson product moment correlation coefficient, and the corresponding dendrogram was deduced using the unweighted-pair group method with arithmetic averages.

16S rRNA gene sequencing.
A 700-bp fragment of the 16S rRNA gene, which included variable regions V1 to V4, was amplified for representative strains of each RAPD genotype for subsequent sequencing. The PCR was carried out using a 50-µl (total volume) mixture containing 5 µl of 10x Taq reaction buffer, 10 µl of 5x Taq Enhancer, 1.5 mM magnesium diacetate, each dNTP at a concentration of 400 µM, 0.4 µM primer WO1 (5'-AGAGTTTGATC[AC]TGGCTC-3'), 0.4 µM primer WO12 (5'-TACGCATTTCACC[GT]CTACA-3') (Table 1), 1 U of Eppendorf Master Taq polymerase, and 1 µl of template DNA. The amplification program consisted of an initial denaturing step of 94°C for 4 min, followed by amplification using 30 cycles of 30 s at 94°C, 30 s at 50°C, and 60 s at 72°C and then a final extension at 72°C for 2 min. PCR products were purified with a Perfectprep gel cleanup kit (Eppendorf, Hamburg, Germany) and were sequenced using an ABI Prism dye terminator cycle sequencing ready-reaction automated sequencer (ABI 3100; Applied Biosystems). Homologies were searched for in the BLASTN database (National Center for Biotechnology Information) using BLAST (2).


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  		TABLE 1. Primer pairs used in this study

Species-specific PCR and multiple PCR.
Species-specific PCR and multiple PCR were used to confirm the identities of the strains belonging to the same RAPD genotype which were not identified by 16S rRNA gene sequencing. Each PCR was carried out using a 50-µl (total volume) mixture containing 5 µl of 10x Taq reaction buffer, 10 µl of 5x Taq Enhancer, 1.5 mM magnesium diacetate, each dNTP at a concentration of 400 µM, each of the two primers at a concentration of 0.4 µM, 1 U of Eppendorf Master Taq polymerase, and 1 µl of template DNA. The species-specific primers used are shown in Table 1. Amplification was performed by following the recommendations described previously (Table 1). The products were analyzed by electrophoresis in 1% agarose gels in 1x TAE buffer.

TTGE.
TTGE samples were prepared by nested PCR (37). First, a 700-bp fragment of the 16S rRNA gene was amplified as described above with primers WO1 and WO12 (Table 1) but with 1.5 U of Eppendorf Master Taq polymerase and 2 µl of DNA template (100 ng). The PCR product was used to amplify the V3 region of the 16S rRNA gene, for which we used two different pairs of primers (6, 37): primers gc338f (5'-CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGGACTCCTACGGGAGGCAGCAG-3') and 518r (5'-ATTACCGCGGCTGCTGG-3') and primers HDA1-gc (5'-CGCCCGGGGCGCGCCCCGGGCGGGGCGGGGGCACGGGGGGACTCCTACGGGAGGCAGCAGT-3') and HDA2 (5'-GTATTACCGCGGCTGCTGGCA-3'). The PCR was carried out using a 50-µl (total volume) mixture containing 5 µl of 10x Master Taq reaction buffer, 10 µl of 5x Taq Enhancer, 1.5 mM magnesium diacetate, each dNTP at a concentration of 400 µM, each primer at a concentration of 0.4 µM, 1.5 U of Eppendorf Master Taq polymerase, and 1 µl of the amplified 700-bp fragment of the 16S rRNA gene. The amplification program included an initial denaturing step of 94°C for 1 min and then 30 cycles of DNA amplification (30 s at 94°C, 30 s at 52°C, and 30 s at 72°C) and a final extension at 72°C for 5 min.

The PCR product of the V3 region was analyzed by TTGE using the Dcode universal mutation detection system (Bio-Rad, Hercules, CA) as described by Ogier et al. (37). The gels were photographed under UV light, and the different bands were cut out with a sterile scalpel and reamplified with the same pair of primers. These PCR products were subject once more to TTGE analysis, and the products found to be pure were sequenced as described above.

LH-PCR.
The 16S/23S rRNA intergenic spacer region specific to lactobacilli was amplified using primers R16-1F and LbLMA1-R (17); the reverse primer LbLMA1-R was labeled fluorescently with 6-carboxyfluorescein. The PCR was carried out using a 50-µl (total volume) mixture containing 5 µl of 10x Master Taq reaction buffer, 10 µl of 5x Taq Enhancer, 1.5 mM magnesium diacetate, each dNTP at a concentration of 400 µM, each of the two primers at a concentration of 0.4 µM, 1 U of Eppendorf Master Taq polymerase, and 1 µl of template DNA. The amplification program included an initial denaturing step of 94°C for 3 min, followed by amplification for 30 cycles of 30 s at 94°C, 30 s at 55°C, and 30 s at 72°C and then a final extension at 72°C for 5 min. The amplified DNA spacer regions were denatured by heating in formamide, and the lengths of the fragments were determined by means of automated fluorescent capillary electrophoresis with an ABI Prism 310 genetic analyzer (Applied Biosystems). Electropherogram peak values (i.e., fragment lengths) were calculated after interpolation with an internal size standard. The fingerprints were compared electronically with a database of fingerprints obtained for different Lactobacillus species (Table 2).


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  		TABLE 2. LH-PCR fragment lengths obtained for different lactobacilli


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RESULTS
 
Microbiological analysis of the cheese samples.
Microbial counts obtained by plating serial dilutions of samples are shown in Table 3. The total LAB counts were always in the range from 107 to 108 CFU/g; the highest levels occurred at the mid-ripening stage, and the lowest levels occurred at the end of the process. No significant differences between counts in the different culture media used were observed, although the lowest levels were obtained with BHA. Enterococci were found at levels of 104 CFU/g during the first week but were not detected during the remaining ripening period. Staphylococci were detected only at the end of the ripening period, at levels of 104 CFU/g, and Enterobacteriaceae were not detected at all throughout ripening. During cheese ripening the pH values were low (pH 5.44 after 1 week of ripening to pH 5.41 after 34 weeks).


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  		TABLE 3. Microbial counts determined during Cueva de la Magahá cheese ripening

Microbial identification and cluster analysis.
Numbers of colonies equal to the square roots of the total numbers of colonies on MRS medium, M17-glucose medium, BHA, and KFA plates containing 30 to 300 colonies were randomly picked and restreaked onto the same media to obtain pure cultures. Thus, a total of 225 isolates (119 isolates from MRS agar, 54 isolates from M17 agar, 41 isolates from BHA, and 11 isolates from KFA) were collected at different times during the ripening period, and after they were tested for catalase and Gram staining, they were used for DNA extraction and RADP-PCR amplification. The level of identity for strain discrimination was set at 86% similarity for different genotypes. The dendrograms deduced using the unweighted-pair group method with arithmetic averages are shown in Fig. 1. After RAPD profiles were compared, a total of 51 different genotypes were chosen for species identification and cluster analysis. At the end of the first week of ripening we detected 26 different genotypes, which were designated G1-1 to G1-26. After 17 weeks of ripening 16 different genotypes were found in the cheese, 10 of which were similar to genotypes identified during the first week. The new genotypes that appeared in this sample were designated G2-1 to G2-6. Finally, at week 34, 26 genotypes were detected, 19 of which (G3-1 to G3-19) were found only at this late stage. A strain of each cluster was identified by 16S rRNA gene sequencing, and the species identity of the other members of the cluster was confirmed by means of PCR amplification using the species-specific probes shown in Table 1.


Figure 1
Figure 1
Figure 1
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  		FIG. 1. Dendrogram obtained after RAPD-PCR analysis of the 225 strains isolated during cheese ripening. (A) One week of ripening. (B) Seventeen weeks of ripening. (C) Thirty-four weeks of ripening. The genotypes and their levels (in log CFU/g) (in parentheses) are indicated on the right. Log CFU/g values were obtained by theoretical calculation on the basis of proportions of the different frequencies of isolation of each genotype on or in different culture media.

Microbial evolution during cheese ripening.
The designations of different genotypes, the species assigned to each of the genotypes, and the percentages of each species based on the total numbers of isolates at the three sampling times are shown in Fig. 1A, B, and C. Log counts were obtained by theoretical calculation on the basis of the proportions of the different frequencies of isolation of each genotype. Cluster analysis of RAPD-PCR patterns revealed a high degree of diversity, dominated by Lactobacillus strains, which were the predominant bacteria throughout the entire ripening period. Other bacterial species, such as Staphylococcus and Kocuria species, appeared only at the mature stage. Six genotypes, L. brevis G1-4, L. paracasei G1-12 and G1-14, L. plantarum G1-15 and G1-20, and Lactobacillus farciminis G1-19, were found to be present during weeks 1 and 17 but did not appear at the end of ripening, while three other genotypes, L. paracasei G2-2 and G2-3 and Lactobacillus parabuchneri G2-1, were detected during weeks 17 and 34 but not during the first week (Fig. 1A, B, and C). The highest titers found during the first week of ripening were the titers of genotypes G1-2 (L. brevis) and G1-15 (L. plantarum), while the lowest titers were the titers of enterococci (approximately 104 CFU/g), represented by Enterococcus faecalis, Enterococcus malodoratus, Enterococcus hirae, and, above all, Enterococcus devriesei, During ripening, however, the Enterococcus species gradually disappeared (Fig. 1A and 1C). At mid-ripening the highest levels were the levels of genotypes G1-15 (L. plantarum) and G1-10 (L. paracasei) (Fig. 1B). During the last month of ripening the levels of the bacteria that had dominated during the first week decreased, leaving genotypes G1-7 (L. brevis), G3-6, G1-10, G2-3, G1-13, G3-10, G3-3, G3-4, and G3-5 (all identified as L. paracasei), G2-1 (L. parabuchneri), and G3-15 (Staphylococcus equorum) as the best-represented genotypes (Fig. 1C).

According to the findings described above, L. paracasei was certainly the most dominant bacterium (55.7%), followed by L. brevis (18.5%), L. parabuchneri (6.3%), and S. equorum (10.5%), while L. rhamnosus (1.3%), Lactobacillus coryniformis (1.3%), Staphylococcus epidermidis (1.3%), Kocuria spp. (1.3%), and Corynebacterium variabile (0.52%) were present at minor levels (Fig. 1C). The highest diversity within a single species was the diversity in L. paracasei, for which 16 different genotypes were isolated (Fig. 1A, B, and C), followed by L. brevis (12 genotypes) and L. plantarum (9 genotypes). Nevertheless, the distribution of Lactobacillus diversity differed according to the stage of ripening. Thus, while during the earliest ripening stage L. plantarum and L. brevis (eight genotypes each) were the most diverse species, L. paracasei showed the highest intraspecific biodiversity from the mid-ripening stage until full maturity. Furthermore, only four genotypes, genotypes belonging to L. brevis (G1-7 and G1-9) and L. paracasei (G1-10 and G1-13), showed high titers throughout the ripening process (Fig. 1A, B, and C).

Throughout the whole ripening period an increase in biodiversity was observed, as demonstrated by the simultaneous presence of L. parabuchneri, L. rhamnosus, and L. coryniformis, and in the final product even S. equorum, S. epidermidis, Kocuria sp., and C. variabile were detected.

TTGE analysis of bacterial microbiota in Cueva de la Magahá cheese and quantification of representative LAB populations.
TTGE fingerprinting of the total bacterial community of Cueva de la Magahá cheese using two different pairs of primers was carried out to amplify the V3 region of the 16S rRNA gene (Fig. 2). The electrophoresis profiles obtained with primers gc338f and 518r showed the presence of four principal bands after the first week, which were identified as L. plantarum (band 1), L. brevis (band 4), L. lactis (band 7), and S. thermophilus (band 8) (Fig. 2). Interestingly, during ripening, new species, including S. equorum (band 3), L. curvatus (band 6), and L. paracasei (band 9), were detected. The intensities of the bands corresponding to L. plantarum and L. brevis were highest at the end of ripening. On the other hand, the most intense bands during the early stage, corresponding to L. lactis and S. thermophilus, were much less intense during the later stages of ripening. The intensities of the bands for the remaining species increased throughout the ripening period.


Figure 2
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  		FIG. 2. TTGE of PCR-amplified 16S rRNA genes in Cueva de la Magahá cheese samples after 1, 17, and 34 weeks of ripening. Bands 1 and 2, L. plantarum; band 3, S. equorum; band 4, L. brevis; band 5, L. coryniformis; band 6, L. curvatus; band 7, L. lactis; band 8, S. thermophilus; band 9, L. paracasei.

The same bacterial species were detected using the HDA1 and HDA2 primers, except for L. coryneformis (band 5), which was present only at the end of ripening. Several quantitative differences were observed, however. Thus, for example, the most intense bands after 34 weeks of ripening corresponded to L. plantarum and S. thermophilus. What is noteworthy are the differences in intensity between S. thermophilus and L. lactis depending on the primers used (Fig. 2).

To confirm and quantify the most representative bacterial populations identified by TTGE analysis of mature cheeses (after 34 weeks of ripening), two series of TTGE fingerprints were obtained for total DNA extracted from enrichment cultures obtained by dilution of cheese in MRS broth and Rothe broth. None of the enrichment cultures yielded a fingerprint identical to that of the total community DNA (Fig. 3) since the TTGE patterns of the diluted enrichment cultures contained fewer bands than those of the nonenriched original cheese. As expected, the number of bands decreased throughout the dilution steps (Fig. 3). The dominant species, L. paracasei and L. brevis (bands 9 and 4), accounted for up to 107 cells g–1, S. equorum (band 3) accounted for up to 106 cells g–1 in MRS broth and 105 cells g–1 in Rothe broth, and L. plantarum (band 1) accounted for up to 106 cells g–1. Nevertheless, none of the L. paracasei and L. brevis bands could be detected at lower dilutions (10–1 to 10–4). L. curvatus (band 6) accounted for up to 105 cells g–1 in MRS broth and 104 cells g–1 in Rothe broth. Other minor bacteria, such L. lactis (band 7) and E. faecalis/Enterococcus faecium, appeared only at dilutions of 10–2 to 10–4 and 10–1 to 10–3, respectively. E. faecalis and E. faecium could not be detected in the TTGE fingerprints of mature cheese. Although bands corresponding to S. thermophilus, L. parabuchneri, S. epidermidis, Kocuria sp., and C. variabile could not be detected in TTGE preparations from any of the enrichment cultures, quantification of some of the bacteria, such as L. paracasei, L. brevis, L. plantarum, L. curvatus, L. lactis, E. faecalis, and E. faecium, was confirmed by species-specific PCR using enrichment cultures (Fig. 3B).


Figure 3
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  		FIG. 3. Estimation of relative abundance of bacterial species obtained from enrichment cultures in MRS broth and Rothe broth for mature cheese. (A) TTGE fingerprinting of PCR-amplified 16S rRNA gene fragments of DNA extracted from enrichment cultures. The numbers indicate the band numbers for total community DNA, as follows: band 1, L. plantarum; band 3, S. equorum; band 4, L. brevis; band 5, L. coryniformis; band 6, L. curvatus; band 7, L. lactis; band 9, L. paracasei. (B) Quantification of representative bacterial species by specific PCR. The lane numbers at the top of each gel indicate enrichment of different dilutions (10–1 to 10–7) in broth media. Lane M contained a 1-kbp DNA ladder (Biotools B&M Labs, Madrid, Spain), lane M1 contained a 100-bp DNA ladder (Biotools B&M Labs, Madrid, Spain), and lane Q contained genomic DNAs from cheese.

Analysis of the Lactobacillus population by LH-PCR.
Separation of the PCR products by capillary electrophoresis enabled us to distinguish between fragments whose lengths differed by only 1 bp. This method allowed us to fingerprint the Lactobacillus diversity of the cheese during ripening (Fig. 4). A database with reference strains (Table 2) was established, and this was followed by performing LH-PCR with the total community DNA during the different ripening periods. On the basis of the peak sizes, four groups could be distinguished (peak 203, peaks 207 and 208, peaks 213 and 214, and peak 218) (Table 2). Three Lactobacillus groups were commonly detected during all the ripening stages: L. plantarum (peaks 207 and 208), L. curvatus/L. coryniformis (peak 213), and L. paracasei/L. rhamnosus/L. brevis (peak 218). Similar quantities of the three Lactobacillus groups were detected during early ripening, and the signal for the L. plantarum group was always the most intense signal. The remaining groups produced similar signals during the mid-ripening period, but in the final product the intensity of the signal of the L. paracasei/L. rhamnosus/L. brevis group increased compared to that of the L. curvatus/L. coryniformis group. Other minor peaks (peaks 191, 194, and 201) were also detected in the mature cheese. Peak 191 could be assigned to Lactobacillus paraplantarum, but the other two minor peaks could not be identified using our database.


Figure 4
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  		FIG. 4. LH-PCR of lactobacilli present in Cueva de la Magahá cheese. (A) One week of ripening. (B) Seventeen weeks of ripening. (C) Thirty-four weeks of ripening.


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DISCUSSION
 
Currently, the microbiological diversity in cheese is of interest, and it has been the subject of many studies, which have generally used classical culture methods relying on investigation of phenotypic characteristics. Very little is known about the biochemistry or microbial content of a great many traditional Spanish cheeses (22). Nevertheless, such information about the cheese-making process could benefit the growth of local industries and the marketing of their traditional products, together with improving the hygienic safety of the final product, thus avoiding spoilage of raw materials.

We studied the microbial communities of Cueva de la Magahá cheese, monitoring them throughout their 8 months of ripening using a combination of classical and molecular techniques with the intention of minimizing the biases inherent in both culture-dependent and culture-independent methods. The concentration of microorganisms in Cueva de la Magahá cheese was high, ranging from 4.6 to 7.98 log CFU/g, values which correspond to those usually found in cheeses during ripening (4, 20, 39, 42). During the first week the LAB levels were 107 CFU/g, and they increased by 1 logarithmic unit during the mid-ripening period to finally stabilize once more at 107 CFU/g. Low levels of enterococci were isolated during the initial ripening period but not thereafter. The presence of this bacterial group in cheese seems to vary depending upon the type of cheese, and this presence has been associated with the use of raw milk (11, 33, 38) and also the season when the cheese is made. As far as non-LAB populations are concerned, no Enterobacteriaceae were detected and 104 CFU/g of staphylococci were found in the final product.

A collection of bacterial isolates obtained from cheese during the ripening period was used as the starting material for this study. Biochemical characterization, although useful for general identification purposes, is less able to distinguish between individual strains; thus, we used molecular techniques, which are powerful tools for fingerprinting the specific DNA patterns of a single strain. PCR-based DNA fingerprinting methods using arbitrary primers, such as arbitrary primer PCR and RAPD-PCR, have been used for studying genomic DNA polymorphisms of LAB and thus for distinguishing between different strains in a population. The use of RAPD to investigate the diversity of the isolates from the cheese allowed us to distinguish 51 different genotypes among the strains isolated (mainly lactobacilli), which were present at various percentages throughout the ripening period. These genotypes were subsequently identified by 16S rRNA sequencing or species-specific PCR amplification. Overall, the strains present at the beginning of ripening were different from those present at the end, although a few (two or three strains of each Lactobacillus species) persisted throughout the process. Changes in environmental parameters, such as humidity, salt concentration, pH (pH 5.44 at the beginning of the process to pH 5.41 at the end of ripening), and the presence of proteins, fatty acids, free amino acids, and other nutrients, could well explain the succession of strains observed, a succession that has been reported for other cheeses, such as Cheddar cheese (20). When we analyzed our results, we found that most of the genotypes appeared either at the beginning (26 genotypes) or at the end of ripening (19 genotypes not detected previously plus 7 genotypes also found at the beginning or at the mid-ripening stage). After 17 weeks of ripening, only six new genotypes were detected compared to the genotypes found after the first week, three of which reappeared during week 34. In any case, lactobacilli predominated throughout the ripening period, and only 0.05% of the strains isolated from the first samples were enterococci. At the end of the ripening period, 11% of the isolates were staphylococci, which may be considered a normal consequence of the lower humidity of the cheese at this stage, given the higher tolerance of Staphylococcus spp. to dryness. Furthermore, Kocuria and Corynebacterium each accounted for 1% of the total strains isolated during this period. Brine is often a source of contamination of cheese by salt-tolerant microorganisms, such as staphylococci, micrococci, enterococci, and corynebacteria.

During the early ripening period, the predominant species were L. brevis (38.97%), L. plantarum (34%), and L. paracasei (25.8%), while during late ripening the predominant strains were L. paracasei (55.7%) and L. brevis (18.5%). We detected high intraspecific biodiversity in L. paracasei from mid-ripening to the end of ripening, although L. plantarum and L. brevis showed the highest intraspecific biodiversity at first. L. plantarum could be considered one of the predominant species in the first week of ripening, but the L. plantarum populations then declined in favor of L. paracasei. Sánchez et al. (43) reported similar results for isolates obtained from several farmhouse Manchego cheeses, and Zarate et al. (47) reported that in Tenerife goat's milk cheeses there were high proportions of L. plantarum in 2-day-old cheese but that the count decreased during ripening, whereas L. paracasei was present initially at low densities but the concentration increased during ripening so that this species became the dominant Lactobacillus species in 60-day-old cheeses. In other Spanish fresh cheeses, however, L. plantarum was the main Lactobacillus species in the mature cheese (7). These differences could easily be attributed to the distinct microbial compositions of these cheeses, because the activity, growth, and survival of a species are determined mainly by the other microorganisms present in its environment (23). In this respect the microbiota of any particular cheese is determined by the source of the milk, the manufacturing process, and the hygienic practices observed during milking, cheese making, and ripening (7).

Cheeses, especially farmhouse style cheeses, can be considered natural ecosystems. It has been proved that some microorganisms in natural ecosystems are extremely difficult to culture (24). Thus, in addition to culture-dependent methods, we directly applied molecular techniques to total cheese DNA in order to obtain a more complete understanding of the ecology of Cueva de la Magahá cheese. Since the results are simple to interpret and mistakes due to problems related to growth failure in culture media are avoided, dominant strains during fermentation can be easily detected and identified in this way. In this work we used TTGE fingerprinting to monitor the population dynamics during cheese ripening, and to circumvent the biases inherent in subjective interpretation, we confirmed the species assignments of the bands by direct sequencing. With the two specific primer pairs for the V3 region of the 16S rRNA gene used in these TTGE studies, we obtained different band intensities depending on which pair was used, and the best results were obtained with HDA1-gc and HDA2. Nevertheless, all the profiles obtained by TTGE allowed us to distinguish between the main bacterial groups; L. lactis and S. thermophilus were the primary species detected, and L. plantarum and L. brevis were present at lower levels. It is worth mentioning that L. lactis and S. thermophilus were not detected by direct isolation. Our failure to recover these bacteria, which are generally ubiquitous in cheese, might be explained by their inability to grow on solid media because they were either stressed or in a viable but noncultivable (VBNC) state. In fact, their presence was established by the strategic use of the culture-independent method TTGE. During ripening the increasing number of TTGE bands revealed an increase in diversity. For the final product nine bands appeared, corresponding to L. plantarum, L. brevis, L. coryniformis, L. curvatus, L. paracasei, L. lactis, S. thermophilus, and S. equorum. It is quite surprising that the band corresponding to L. plantarum was very well defined in the final product, while this species was not isolated at this time. High levels of L. paracasei, on the other hand, were isolated from all the samples, while this species was detected by TTGE at the end of ripening only as a very weak band. So, although in general our findings suggest that TTGE analysis can provide better results for species present at high concentrations, amplification results may vary depending on the efficacy of DNA extraction, which depends in turn on the bacterial species and food matrices (1, 40). Alternatively, target competition by primers during PCR may occur, as suggested by Heuer and Smalla (27). Accordingly, Muyzer et al. (36) and Heuer and Smalla (27) reported that species representing less that 1% of the total community would not be visible in denaturing gradient gel electrophoresis profiles of the microbial community, and Ogier et al. (37) indicated that TTGE analysis results reflect only the most abundant microbes. To obviate this problem, we considered the possibility that a preenrichment step before DNA extraction might help us to recover less dominant microorganisms, as suggested by Giraffa and Neviani (24). Thus, we carried out TTGE analyses of DNA extracted after we enriched the cheese dilutions in broth in order to supplement our findings, in a semiquantitative way, for the main culturable microbial groups. A comparison of TTGE profiles obtained for the total DNA of the cheese community and for DNA extracted from enrichment cultures revealed some important differences. For example, E. faecalis and E. faecium, which could not be isolated from mature cheese, were detected in enriched MRS and Rothe broth media. We cannot ignore the possibility that these bacteria might have been present in a VBNC state, which would have made it difficult to isolate them directly in a selective medium. In fact, a VBNC state has been induced experimentally in E. faecalis (14), and under suitable conditions the cells are able to recover from the debilitated state. This may well explain why we did not isolate enterococci from selective plates (KFA), although growth was observed in a general medium (MRS broth) and even in selective broth (Rothe broth). This was also true for L. curvatus, which was detected at titers of 104 and 105 CFU/g in Rothe broth and MRS broth, respectively, only when the culture-independent technique was used. Similarly, L. plantarum was determined to be present at a level of 106 CFU/g by QPCR, whereas it could not be isolated from mature cheese.

In the same way, L. lactis, although not detected by direct isolation on agar, was determined to be present by QPCR-TTGE at titers of 104 CFU/g in mature cheese, thus confirming the results obtained by temperature gradient gel electrophoresis analysis. Nevertheless, the approximate levels of lactococci found are much lower than the levels expected as the levels of these bacteria generally are more than 108 CFU ml–1 during milk curding. Our interpretation of this finding is that L. lactis may be especially susceptible to the environmental conditions formed by the microbiota in this cheese (for instance, acetic acid produced by heterofermentative lactobacilli, which would kill most of the lactococci or else drive them into a VBNC state).

Finally, our monitoring of the Lactobacillus composition by LH-PCR revealed the increasing predominance of L. plantarum throughout ripening, followed by abundant representation of the L. rhamnosus/L. paracasei/L. brevis group. Apart from this, L. curvatus/L. coryniformis, L. paraplantarum, and two other unidentified lactobacilli were found in the mature cheeses.

This study provides a complete view of the composition of the microbial community in Cueva de la Magahá cheese obtained using a polyphasic approach combining culture-dependent and culture-independent methods. Such a combined approach was vital for obtaining a realistic view of the existing microbial ecosystem because of the proven variations between the results obtained by the two types of methods. Our results suggest that the failure of culture-dependent methods may be explained by overshadowing of minor populations by the predominant populations and also by the transition to a VBNC state, probably caused by environmental stress.


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ACKNOWLEDGMENTS
 
This work was supported by research project CAL02-078 of the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA, Ministerio de Ciencia y Tecnología) and by the Research Plan of the Junta de Andalucía (research group CVI 0160). A. M. Martín-Platero had a grant from the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía).

We thank the Cueva de la Magahá cheese factory for supplying the samples and J. Purswani for her assistance with the manuscript. We also thank J. Trout for reviewing the English text.


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FOOTNOTES
 
* Corresponding author. Mailing address: Departamento de Microbiología, Facultad de Ciencias, Fuentenueva s/n, 18071 Granada, Spain. Phone: 34 958 243184. Fax: 34 958 249486. E-mail: mmartine{at}ugr.es Back

{triangledown} Published ahead of print on 25 July 2008. Back


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Applied and Environmental Microbiology, September 2008, p. 5662-5673, Vol. 74, No. 18
0099-2240/08/$08.00+0     doi:10.1128/AEM.00418-08
Copyright © 2008, American Society for Microbiology. All Rights Reserved.




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