# Microbial composition and viability of natural whey starters used in PDO Comté cheese-making

Jade Lutin, Franck Dufrene, Philippe Guyot, Romain Palme, Christine

Achilleos, Yvette Bouton, Solange Buchin

► To cite this version:

Jade Lutin, Franck Dufrene, Philippe Guyot, Romain Palme, Christine Achilleos, et al. Microbial composition and viability of natural whey starters used in PDO Comté cheese-making. Food Microbiology, 2024, 121, pp.104521. 10.1016/j.fm.2024.104521. hal-05289225

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# Microbial composition and viability of natural whey starters used in PDO Comté cheese-making

Jade Lutin<sup>a</sup>, Franck Dufrene<sup>b</sup>, Philippe Guyot<sup>a</sup>, Romain Palme<sup>b</sup>, Christine Achilleos<sup>b</sup>, Yvette Bouton<sup>a, *</sup>, Solange Buchin<sup>b</sup>

## ARTICLE INFO

Keywords:

Natural whey starters

Biodiversity

Viability

Comté cheese

Streptococcus thermophilus

Lactobacillus helveticus

Lactobacillus delbrueckii

## ABSTRACT

Natural whey starters (NWS) are cultures with undefined multiple-strains species commonly used to speed up the fermentation process of cheeses. The aim of this study was to explore the diversity and the viability of Comté cheese NWS microbiota. Culture-dependent methods, i.e. plate counting and genotypic characterization, and culture-independent methods, i.e. qPCR, viability-qPCR, fluorescence microscopy and DNA metabarcoding, were combined to analyze thirty-six NWS collected in six Comté cheese factories at two seasons. Our results highlighted that NWS were dominated by *Streptococcus thermophilus* (ST) and thermophilic lactobacilli. These species showed a diversity of strains based on Rep-PCR. The dominance of *Lactobacillus helveticus* (LH) over *Lactobacillus delbrueckii* (LD) varied depending on the factory and the season. This highlighted two types of NWS: the type-ST/LD (LD > LH) and the type-ST/LH (LD < LH). The microbial composition varied depending on cheese factory. One factory was distinguished by its level of culturable microbial groups (ST, enterococci and yeast) and its fungi diversity. The approaches used to estimate the viability showed that most NWS cells were viable. Further investigations are needed to understand the microbial diversity of these NWS.

## 1. Introduction

Comté is a traditional cheese with a Protected Designation of Origin (PDO) exclusively produced in a defined geographical area, the Jura mountains, in the East of France. It is a pressed cooked (54–57 °C) and long-ripened cheese manufactured by using raw cow's milk added with starter cultures, including natural whey starters (NWS), named ambient starters in Comté cheese technology. These NWS are obtained using a back-slopping procedure and are traditionally prepared by collecting some of the whey in the cheese vat after curd cooking. The non-acidified whey is incubated overnight in the cheese factory, at ambient temperature to reach a thermophilic lactic acid bacteria level necessary for the cheese-making of the following day.

The back-slopping procedure has been known for centuries (Demarigny and Gerber, 2014) but was gradually being replaced by defined starter cultures. However, it is currently experiencing a resurgence of interest (Von Gastrow et al., 2020) due to NWS adaptation to raw milk, NWS resilience to stress (Bertani et al., 2020) and NWS resistance to phage attacks (Mercanti et al., 2011; Somerville et al., 2022).

Moreover, NWS are a practice for cheesemakers to enrich milk microbiota (Montel et al., 2014).

NWS consist of a rich microbial consortium, with various undefined strains for each species (Bouton et al., 2000; Giraffa and Rossetti, 2004; Smid et al., 2014). They are commonly used to speed up the fermentation process of different varieties of cheeses. The lactic acid bacteria community of NWS of hard cooked cheeses has been investigated in previous studies regarding Grana Padano (Giraffa, 2021), Parmigiano Reggiano (Levante et al., 2021), Trentingrana (Morandi et al., 2019) and Swiss Gruyère cheeses (Moser et al., 2017). The authors found that dominant species were *Lactobacillus helveticus* (LH), *Lactobacillus delbrueckii* (LD), *Streptococcus thermophilus* (ST) and *Lactobacillus fermentum*. However, the inability to cultivate all the microorganisms from a complex environment by direct count methods makes it difficult to determine the biodiversity of communities. Standard culture media may not accurately reflect the biodiversity in a sample because some bacteria may be difficult to culture or not culturable, leading to an underestimate of their abundance. Moreover, this type of analysis is laboratory and time consuming. In order to fully describe microbial communities, culture-based methods are often supplemented by culture-

<footnote><sup>a</sup> Comité Interprofessionnel de Gestion du Comté – Unité R&D, Bât. INRAE, F-39800, Poligny, France</footnote>

<footnote><sup>b</sup> INRAE, Institut Agro, Université de Bourgogne, UMR PAM, F-39800, Poligny, France</footnote>

<footnote>* Corresponding author. Comité Interprofessionnel de Gestion du Comté – Unité R&D, Bât. INRAE, F-39800, Poligny, France. E-mail address: y.bouton@comte.com (Y. Bouton).</footnote>
independent approaches. Low-through-put approaches, such as quantitative PCR (qPCR), have already provided deeper insight into the composition of NWS on the dynamics of bacterial NWS community under technological pressure (Bertani et al., 2020; Chessa et al., 2021; Moser et al., 2017). Technological pressure is known to shape the NWS community (Bertani et al., 2020; Rossetti et al., 2008) during the back-slopping procedure and can impact the viability of cells. Different authors tried to estimate the viability through other culture-independent approaches (Gatti et al., 2006; Santarelli et al., 2008) focused on NWS viability using fluorescence microscopy based on stained live/dead cells for Grana Padano cheese to evaluate the global microbial viability. A recent study carried out by Bellassi et al. (2023) investigated cells physiological state of Grana Padano and Parmigiano Reggiano NWS using a flow cytometric approach with staining protocols. Another approach known as viability-qPCR combining qPCR with a DNA cross-linking agent, the propidium monoazide (PMA) dye, was developed to detect viable bacteria. PMA dye is membrane-impermeable and binds covalently to the DNA of cells with damaged membrane after photoactivation. The bound DNA cannot be amplified using PCR (Nocker et al., 2006). Viability-qPCR is becoming a convenient and stable technique for estimating and quantifying bacterial viability. However, these techniques are based on cell membrane integrity, assuming that non-viable cells have damaged membrane while presumably viable cells have intact membranes. This approach has been successfully used to investigate the dynamics of starters in long-ripened cheddar cheese (Barzideh et al., 2022), the quantification of viable lactic acid bacteria in fermented milk (Shi et al., 2022) and in milk (Kable et al., 2019).

Nowadays, high-throughput approaches based on next-generation sequencing complement these methods to determine the composition of dairy products. Among these methods, the metabarcoding approach using variable regions of the rRNA gene as a target, 16S for bacteria or Internal Transcribed Spacer (ITS) for fungi, can identify microorganisms at the genus level, and sometimes at the species level. 16S metagenomic has been used to describe the composition of NWS used for the production of Italian hard-cooked cheeses (Bertani et al., 2020; De Filippis et al., 2014; Sola et al., 2022).

NWS have not been extensively studied in Comté cheese, and as a result, little is known about their microbial diversity and the viability of their thermophilic cells. These aspects were investigated in NWS from six Comté cheese factories at two seasons (summer and winter) by means of several culture-dependent (plate count medium, Rep-PCR on isolates) and culture-independent methods (qPCR, viability-qPCR, fluorescence microscopy, 16S and ITS metabarcoding).

## 2. Material and methods

### 2.1. NWS samples

Thirty-six NWS samples were obtained from six different Comté cheese factories (F1 to F6) geographically dispersed in the PDO cheese production area at two seasons (winter, from December 2021 to February 2022, and summer in June 2022) during three consecutive days of cheese-making. Around 180 mL of NWS were collected in sterile flasks in the morning, just before addition to the vat milk. Samples were transported to the laboratory under refrigerated conditions and immediately analysed. Information on NWS preparation is detailed in Table 1.

### 2.2. Microbial quantification

#### 2.2.1. Culturable populations

The concentrations of NWS major microbial culturable groups were assessed by plate counts. One mL of NWS was serially diluted in 9 mL of 0.1% peptone water and 50 µL of the cell suspension of the suitable dilution were plated on selective media for enumeration. Lactococci were enumerated on M17 agar (Terzaghi and Sandine, 1975) with 0.4% nalidixic acid w/v aerobically incubated at 20 °C for 48h; thermophilic streptococci on M17 agar 45 °C 48h aerobically; thermophilic lactobacilli (TL) on MRS agar pH 5.50 (Difco™ MRS, Fisher Bioblock Scientific) 45 °C 3 d anaerobically; Gram-negative bacteria on PCAL (plate count agar with skimmed milk, Biokar Diagnostics) with 0.1% crystal violet and 0.1% vancomycin 30 °C 3 d aerobically; ripening bacteria (Gram and catalase positives bacteria e.g. *Staphylococcaceae*, *Brachybacterium*, *Brevibacterium* and *Corynebacterium*) on CRBM (Denis et al., 2001) with 0.9% pimaricin and 0.4% nalidixic acid 25 °C 5 d aerobically; yeast and fungi on OGA (oxytetracycline glucose agar, Biokar Diagnostics) 25 °C 3 d aerobically; facultatively heterofermentative lactobacilli (FHL) on FH agar pH 5.40 (Isolini et al., 1990) 37 °C 3 d anaerobically; propionic acid bacteria (PAB) on SLAC agar (Drinan and Cogan, 1992) 30 °C 6 d anaerobically; enterococci on CE (compass *enterococcus* agar, Biokar Diagnostics) 42 °C 48h aerobically. OH broth (Isolini et al., 1990) aerobically incubated at 37 °C for 3d was used for the determination of the most probable number of obligatory heterofermentative lactobacilli (OHL). Plate counts were carried out in duplicate.

#### 2.2.2. Thermophilic total and viable cells

The concentrations of NWS viable thermophilic bacteria were assessed by a molecular technique combining qPCR and PMAxx (Biotium, Inc. Fremont, CA, USA) (viability-qPCR). Forty-five mL of NWS sample were centrifuged at 13,000 × g for 10 min at 4 °C. The resulting pellet was washed once with 45 mL of phosphate-buffered saline (PBS) solution. After centrifugation 13,000 × g 10 min 4 °C, the cell pellet was resuspended in 10 mL of PBS solution. One milliliter was used for PMAxx treatment and further viability-qPCR. PMAxx treated cells allowed to

<caption>**Table 1**</caption>

Summary of the main practices specific to each cheese factory involved in this study for natural whey starters preparation. RT: room temperature (incubation under a natural gradually decreasing temperature).

<table><thead><tr><th>Factory</th><th>Altitude of the factory (m)</th><th>Season</th><th>Quantity of whey collected (L)</th><th>Temperature in the cheese vat at sampling (°C)</th><th>Overnight incubation</th><th>Container</th><th>Cleaning of the container</th></tr></thead><tbody><tr><td>F1</td><td>550</td><td>Summer/Winter</td><td>30</td><td>55.5</td><td>RT</td><td>stainless steel</td><td>soap and brushing</td></tr><tr><td>F2</td><td>850</td><td>Summer/Winter</td><td>15</td><td>55.5</td><td>RT</td><td>stainless steel</td><td>soap and brushing</td></tr><tr><td>F3</td><td>750</td><td>Summer/Winter</td><td>20</td><td>54.0<br>54.5</td><td>RT</td><td>Plastic food container</td><td>hot water rinse</td></tr><tr><td>F4</td><td>500</td><td>Summer/Winter</td><td>15</td><td>56.0</td><td>RT</td><td>stainless steel</td><td>soap and brushing</td></tr><tr><td>F5</td><td>560</td><td>Summer/Winter</td><td>20</td><td>56.0</td><td>RT for 4h then 12 °C</td><td>stainless steel</td><td>soap and brushing</td></tr><tr><td>F6</td><td>690</td><td>Summer/Winter</td><td>20</td><td>56.0</td><td>RT</td><td>stainless steel</td><td>soap and brushing</td></tr></tbody></table>
quantify viable cells based on the membrane integrity. One mL was used for qPCR. Untreated cells allowed to quantify total cells.

PMAxx dye was dissolved in ultra-pure water to a 1 mM stock solution and stored at -20 °C protected from light until use. PMAxx treatment of bacterial cells was adapted from Chen et al. (2021). Sixty microliters of PMAxx stock solution were added to 1 mL of the cell suspension to achieve a final concentration of 60 µM PMAxx. Samples were mixed for 5 min in the dark at room temperature to allow the PMAxx to enter into the cells with compromised membrane. Photoactivation of PMAxx was carried out under direct irradiation of a 711 LED lamp (AS Schwab) for 15 min with a gentle agitation every 2 min. During photoactivation, samples were placed at a distance of 20 cm from the light source and laid horizontally on ice. The samples were washed twice with 1 mL of PBS solution and cell pellets collected by centrifugation 6,000×g 5min 4 °C. The cell pellets were then stored at -20 °C until DNA extraction.

Genomic DNA from PMAxx treated cells and untreated cells was extracted using DNAzol reagent (Molecular Research Center, Inc. Cincinnati, OH, USA) and isopropanol for DNA precipitation as previously described by Achilleos and Berthier (2013). The concentration and quality of DNA extracts were determined by spectrophotometric measurements at 260/280 and 260/230 nm using a NanoDrop 2000c (Thermo Fisher Scientific, Wilmington, DE, USA). Genomic DNA was stored at -20 °C.

PCR reactions were performed in a MX3000P real-time thermal cycler (Agilent Technologies, Santa Clara, CA, USA) using SYBR Green DNA-intercalating dye as previously described by Achilleos and Berthier (2017). Primers were designed by Achilleos and Berthier (2013) to specifically target factor Tu gene (tuf) of ST, LD and LH.

## 2.3. Viable cells in overall bacterial community

An overall estimate of NWS viable cells was also assessed by viability staining using 5(6)-carboxyfluorescein diacetate (cFDA) (Sigma-Aldrich, Saint-Louis, MO, USA) and propidium iodide (PI) (Sigma-Aldrich, Saint-Louis, MO, USA) based on the detection of membrane integrity and enzymatic activity. cFDA was used as a live stain yielding the green fluorescent carboxyfluorescein upon hydrolysis by cellular esterase. PI was used as a dead stain supposed to enter only cells with damaged membranes. Intact or viable cells emit green fluorescence while damaged cells emit red fluorescence.

Twenty-five milliliters of NWS sample were centrifuged at 10,000×g for 10 min at 4 °C. The resulting pellet was dissolved in 2 mL saline solution (0.85% NaCl w/v) with 0.5% cysteine w/v. One milliliter was washed once with 20 mL of saline solution with cysteine. After centrifugation at 13,000×g for 1 min at room temperature, the pellet was resuspended in 10 mL of saline solution with cysteine. cFDA and PI were added to 1 mL of the cell suspension to achieve final concentrations of 25 µM cFDA and 30 µM PI. The suspension was mixed and incubated for 30 min in the dark at 37 °C. After staining and centrifugation 4,000×g for 5 min at room temperature, the sample was washed once with 1 mL of saline solution with cysteine. Depending on the optical density of the suspension, the samples were diluted from 3/1000 to 5/10000 in the saline solution with cysteine. Then, 1 mL of the diluted sample was filtered through a sterile Isopore™ membrane filter 0.2 µm, 13 mm (Merck Millipore, Burlington, MA, USA). The filter that retained the cells was recovered and mounted between a glass slide and a glass coverslip to be observed with a fluorescent microscope.

Stained cells count was performed on 10 fields by using a fluorescent microscope BX43 (Olympus Life Science, Tokyo, Japan). Cells were observed with ×100 objective lens and 2 filters (Chroma U-M41018 Endow GFP/EGFP Longpass Fluorescence Filter Cube and Omega TRITC Fluorescence Filter Cube) were used to collect the fluorescent signals. Epifluorescence images were recorded with EPview 3.1 software (Olympus Life Science, Tokyo, Japan) and images were

processed with the free software package NIH ImageJ v1.53t (Schneider et al., 2012). Each sample was measured in triplicate.

## 2.4. Genotyping

The second day of cheese-making, intraspecific diversity was assessed for thermophilic streptococci and TL isolates selected depending on different morphologies. Twelve selected colonies from the M17 (thermophilic streptococci) and MRS (TL) plates were purified and stored at -80 °C in their respective media (M17 or MRS broth) with 15% (v/v) glycerol. Purity was checked by microscopic examinations. DNA was extracted from 1 mL of fresh M17 or MRS culture in the exponential growth phase with a chemical method adapted from Godon et al. (1997). Two hundred and thirty µL of 4 M guanidinium thiocyanate with 10% N-lauroylsarcosine were added to the samples and mixed for 5 s. Cell lysis was carried out by a thermal shock by heating the tubes in the microwave for 1 min at 700 W then placing in ice for 1 min and heating them one more time in the microwave for 1 min at 700 W. Then, 250 µL of 5% N-lauroylsarcosine were added and mixed for 5 s. DNA was ethanol precipitated for 10 min with 1 mL of 50 mM sodium acetate in 100% ethanol. The precipitate was collected after centrifugation 15,000×g for 10 min at 4 °C, dissolved in 250 µL of potassium acetate 0.5 M and incubated in ice at 4 °C for 1 h 30. After 30 min of centrifugation 15,000×g at 4 °C, the supernatant was added to 525 µL of 50 mM sodium acetate in 100% ethanol and incubated at -20 °C for 20 min. The pellet was collected by centrifugation 12,300×g for 10 min at 4 °C and washed with 500 µL of 70% ethanol. DNA was collected by centrifugation 12,300×g for 10 min at 4 °C and traces of ethanol were eliminated by centrifugation with a vacuum-centrifuge Univapo 100 H (Uniequip, Planegg, Germany) for 20 min. DNA was added to 40 µL of 10 mM Tris- 1 mM EDTA concentration RNase and incubated in a water bath at 37 °C for 15 min to eliminate RNA. DNA was stored at -20 °C until PCR reaction.

REP-PCR and ERIC-PCR were performed on isolates according to Berthier et al. (2001). The resulting profiles were analysed by the BioNumerics software v7.1 (Applied Maths NV, BioMérieux, Marcy-l'Étoile, France). The similarity among profiles was calculated using the Pearson correlation. An average linkage (UPGMA) dendrogram was stem from these profiles. Only isolates exhibiting profiles with 85% or more similarity were considered to be the same strain. This level corresponded to the lowest similarity level obtained by repeated analyses of the same strain (data not shown).

PCR for species identification was applied to isolates representative of each Rep-PCR profile. Species-specific PCR for ST, LD and LH were performed as previously described by Bouton et al. (2002) and Depouilly et al. (2004).

## 2.5. DNA metabarcoding

Forty-five mL of NWS sample were centrifuged at 9,000×g for 15 min at 4 °C. The cell pellets were resuspended in 3 mL of physiological water at 4 °C and a 2 mL aliquot was centrifugated at 13,000×g 2 min 4 °C. The supernatants were removed and DNA extraction was performed using DNeasy PowerFood® Microbial Kit (Quiagen, Courtaboeuf, France) according to the manufacturer's instructions. The concentration and purity of the extracted nucleic acids were determined by Qubit (Thermo Fisher Scientific, Waltham, MA, USA). The extracted DNA was stored at -20 °C until PCR reaction.

The bacterial and fungal composition of NWS were determined by targeting the V3-V4 region of the 16S rRNA gene using the PCR primers 16S_V3F (5'-ACGGRAGGCWGCAG-3') and 16S_V4R (5'-TACCAGGGTATCTAATCCT-3'), and the ribosomal ITS2 using the primers ITS3f (5'-GCATCGATGAAGAACGCAGC-3') and ITS4_KYO1 (5'-TCCTCCGCTTWTTGWWTWTGC-3'), respectively (Irlinger et al., 2023; Rué et al., 2023). The reaction mixture (25 µL) contained 10 ng ge-
nomic DNA, 200 µM of Taq buffer (Q Biogene, Illkirch-Graffenstaden, France), 400 µM of dNTP mix, 0.02 µM of Taq polymerase (Q Biogene, Illkirch-Graffenstaden, France) and 0.4 µM of each primer. PCR thermal cycling conditions were applied as follows: initial denaturation at 94 °C for 60s, followed by 30 cycles at 94 °C 60s for denaturation, 65 °C 60s for primer annealing, 72 °C 60s for elongation, and 72 °C 10 min to ensure final elongation, using GeneAmp PCR System 9700 (Applied Biosystems, Waltham, MA, USA).

Samples were sent to the GeT - Biopuces platform (GenoToul Geno-pole, Toulouse, France) for paired-end library preparation sequencing (Illumina MiSeq). For processing of metabarcoding sequencing reads, the FROGS 4.1.0 pipeline on Galaxy interface was used (Bernard et al., 2021; Escudié et al., 2018) with the parameters presented in Table 2. Taxonomy assignment of ASV was carried out with Dairydb (Meola et al., 2019) database for bacteria and with ITS UNITE for fungi (Nilsson et al., 2019). The taxonomic annotation of 16S rRNA gene sequences was manually checked and blasted against EZBiocloud database (Yoon et al., 2017) when necessary.

## 2.6. Data analysis

The enumeration results expressed as colony forming units (CFU) per mL of NWS were converted to log for statistical analysis, as was DNA quantification by qPCR and viability-qPCR expressed as genome unit (GU) per mL of NWS. Data were presented as mean ± standard deviation of three replicates for each sample.

<table><caption>**Table 2**
FROGS 4.1.0 parameters.</caption><thead><tr><th>Tool</th><th>16S rRNA V3-V4</th><th>ITS region ITS2</th></tr></thead><tbody><tr><td rowspan="7">Pre-processing</td><td>illumina</td><td>illumina</td></tr><tr><td>min amplicon size 400</td><td>min amplicon size 50</td></tr><tr><td>max amplicon size 520</td><td>max amplicon size 1000</td></tr><tr><td>5' primer</td><td>5' primer</td></tr><tr><td>ACGGRAGGCWGCAG</td><td>GCATCGATGAAGAACGCAGC</td></tr><tr><td>3' primer</td><td>3' primer</td></tr><tr><td>AGGATTAGATACCCTGGTA</td><td>GCAWAWCAAWAAGCGGAGGA</td></tr><tr><td rowspan="2">Clustering swarm</td><td>R1 size 250</td><td>R1 size 250</td></tr><tr><td>R2 size 250</td><td>R2 size 250</td></tr><tr><td rowspan="2">Remove chimera</td><td>distance clustering 1</td><td>distance clustering 1</td></tr><tr><td>fastidious swarm option default</td><td>fastidious swarm option default</td></tr><tr><td>Cluster filter</td><td>min abundance 0.00005</td><td>min abundance 0.00005</td></tr><tr><td>Taxonomic affiliation</td><td>Reference database 16S DAIRYdb v2.0</td><td>Reference database ITS UNITE Fungi 9.0</td></tr></tbody></table>

For microbial quantification, analysis of variance (ANOVA) was performed to determine the effect of the two factors (the cheese factory with six levels and the season with two levels) with significant differences among the means determined with the Newman-Keuls test. The differences were considered significant with p-value <0.05. Analyses of data were performed using RStudio v4.2.1 (RStudio Team, 2021) and XLSTAT v2023.1.3 (Addinsoft, 2023).

The microbial communities were characterized using Ex-ploreMetabar v2.0.1 (Theil and Rifa, 2021). All the samples were raro-fied to the minimum number of reads (8401 for 16S and 1699 for ITS2) for subsequent analysis, to prevent any biases, due to different depths of sequencing. The results were expressed in relative abundance. Alpha-diversity was estimated from observed ASVs and Shannon index whose differences between the groups of NWS were underlined using an ANOVA. Beta-diversity was evaluated on Bray-Curtis distance method and a Non-Metric multi-Dimensional Scaling (NMDS) plot was performed on each distance matrix to represent the samples of NWS. A Per-manova was carried out to show significant differences between the groups.

## 3. Results

### 3.1. Microbial quantification of culturable populations

The concentration of the major microbial culturable groups in NWS was assessed by plate counts using different selective media (Fig. 1). Thermophilic species were dominant species for all the factories and both seasons. Thermophilic streptococci counts were 8.5 log CFU/mL on average except in samples from F3 (6.2 log CFU/mL). TL counts ranged from 6.8 to 8.3 log CFU/mL depending on the factory and the season. Minor populations were encountered but their presence varied depending on the factory or the season; lactococci counts were up to 5.6 log CFU/mL, enterococci, yeast and gram-negative bacteria up to 4.4 log CFU/mL, ripening bacteria and OHL up to 2.5 log CFU/mL, and PAB up to 1.3 log CFU/mL. No mold nor FHL were detected in NWS. F3 dif-fered from the other factories by significant lower thermophilic strepto-cocci counts (a difference of at least 2 logs), and significant higher counts of enterococci and yeast. The effects of the factory, the season and the interaction factory x season are presented in the Supplementary file S1. Differences between the factories for thermophilic streptococci, TL and ripening bacteria although significant were small (<0.5 log), except for ST in F3 and to a lesser extent for TL in F4. The significant differences obtained for the ANOVAs on the culturable yeast and ente-rococci population levels (Supplementary file S1) were attributable to

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Plate counts of the culturable populations in Comté cheese natural whey starters. Comparison of six different factories (F1 to F6) at two seasons (S. summer, W. winter). FHL: facultatively heterofermentative lactobacilli; OHL: obligatory heterofermentative lactobacilli. Microbial counts were expressed as log CFU/mL ± standard deviation. Asterisks indicate significant differences among the factories for each season (*p < 0.05; **p < 0.01; ***p < 0.001).</figcaption></figure>
the count values measured for F3 which were higher in winter than in summer; counts between the other factories being similar for a given season (Fig. 1). The other populations were at low levels and it is difficult to conclude on the effect of the factors.

## 3.2. Molecular quantification of the total thermophilic populations

Levels of ST, LD and LH total cells in NWS were investigated through a culture-independent approach using qPCR. The total cells from all factories and both seasons are presented in Figs. 2 and 3. Total ST cells in NWS were found to be around 9.0 log GU/mL, except for F3 in winter which had higher levels (10.5 log GU/mL). Total LD cells ranged from 5.2 to 9.7 log GU/mL, with significantly higher levels for F1 and F3 and the lowest levels for F2. Total LH cells ranged from 6.1 to 7.9 log GU/mL, with significantly higher levels for F4 and F5. The ratio of total LD to LH cells was different according to the factory. NWS showed higher total LD cells than total LH cells for F1, F3, F5 in winter and F6, lower total LD cells than total LH cells for F2 and F4 in winter, and similar levels for F4 and F5 in summer. The factory had a significant impact on the levels of the total number of cells of thermophilic populations in NWS, the classification of factories depending on the season (Supplementary file S2). However, for ST and LH total cells, differences between factories were small (<0.5 log) and therefore due to good repeatability of the analytical method rather than to a biological

difference, despite statistical significance (P < 0.001). These differences may only be considered for F3.

## 3.3. Viability of NWS cells

The percentage of viable cells of NWS, evaluated by fluorescence microscopy, was very high for all NWS analysed, ranging from 98.4% to 99.8% (data not shown). Levels of viable cells of thermophilic populations in NWS were assessed by viability-qPCR. The viable cells from all factories and both seasons are presented in Figs. 2 and 3. Viable ST cells ranged from 8.7 to 10.3 log GU/mL according to factories (Fig. 2). F3 had significantly higher levels of viable ST cells in winter. Levels of viable LD cells ranged from 5.0 to 9.4 log GU/mL, with significantly higher levels for F1 and F3 and lower levels for F2 (Fig. 3). Levels of viable LH cells ranged from 5.4 to 7.6 log GU/mL, with significantly higher levels for F4 and lower levels for F1 in summer (Fig. 3). As observed for total cells, the ratios of viable LD to LH cells were different according to the factory (>1 for F1, F3, F5 and F6; <1 for F2 and F4). The differences between total cells and viable cells counts were small for LD (from 0.0 to 0.4 log GU/mL) and ST (from 0.0 to 0.2 log GU/mL), and higher for LH (from 0.1 to 1.6 log GU/mL), which suggests that the majority of the thermophilic cells were viable. This approach provides more accurate results than fluorescence microscopy. The factory had a significant impact on the levels of thermophilic viable cells in NWS, the classification of cheese factories depending on the season (Supplementary

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Levels of *Streptococcus thermophilus* in natural whey starters from six Comté cheese factories (F1 to F6) at two seasons (S. summer, W. winter). Levels of total cells were obtained by qPCR and viable cells by viability-qPCR and expressed as log GU/mL ± standard deviation. Asterisks indicate significant differences among the factories for each season (*p* < 0.05; **p* < 0.01; ***p* < 0.001) and different letters within a class of cells represent significant differences as analysed using Newman-Keuls test (p < 0.05).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Levels of *Lactobacillus delbrueckii* and *Lactobacillus helveticus* in natural whey starters from six Comté cheese factories (F1 to F6) at two seasons (S. summer, W. winter). Levels of total cells were obtained by qPCR and viable cells by viability-qPCR and expressed as log GU/mL ± standard deviation. Asterisks indicate significant differences among the factories for each season (*p* < 0.05; **p* < 0.01; ***p* < 0.001) and different letters within a class of cells represent significant differences as analysed using Newman-Keuls test (p < 0.05). LD: *Lactobacillus delbrueckii*; LH: *Lactobacillus helveticus*.</figcaption></figure>
tary file S2). The difference between LH viable cells in summer and winter, despite statistical significance (P < 0.05) was small (<0.5 log) and was not expected to affect the technological properties of NWS.

### 3.4. Genotyping of thermophilic populations

The diversity within the most abundant thermophilic species, ST, LD and LH, was investigated by Rep-PCR. Twelve strains of ST, seven strains of LD and four strains of LH could be identified in NWS samples based on DNA banding patterns using REP and ERIC primers (Table 3 and Supplementary file S3). Of the twelve ST strains identified, eleven were factory specific and eight were season specific. The strain St6 was the most widespread in NWS (two out of six factories in summer, four out of six factories in winter). NWS from F1, F2, F3 and F5 in summer, and F6 for both seasons, were single-strains. The maximum number of different strains observed in NWS was three for F3 in winter.

Of the seven LD strains identified, six strains were factory and season specific. On the four LH strains identified, only the strain Lh4 was factory specific and two strains were season specific. The strains Ld4 and Lh3 were the most widespread in NWS. The proportions of LD and LH varied depending on the factory. On the twelve isolates identified, F1 and F3 showed a majority of LD (67–100% isolates affiliated to LD) while the other factories showed a majority of LH (67–100% isolates affiliated to LH) regardless to the season. NWS from F1 and F4 for both seasons, as well as F2 in summer, were single-strains for LD (F1) or LH (F4). The majority of the strains were specific to a factory and/or a season.

### 3.5. DNA metabarcoding analysis

Bacterial sequences were more than 99% assigned to the *Firmicutes* phylum. A total of 95 ASVs were identified of which the ten most abundant taxa are presented in Fig. 4. ST represented the most abundant

species in all NWS samples, with mean values of 86.5%. LD (8.4%) and LH (4.5%) were also dominant species in NWS depending on the factors. The dominance of thermophilic species agreed with previous cell count results. As observed by qPCR, LD was the dominant TL for F1, F3, F5 (winter) and F6, and LH for F2, F4 and F5 (summer). Other species (e.g. *Streptococcus gordonii* and *Lactobacillus psittaci*) represent less than 1%. Fungal sequences were more than 96% assigned to *Ascomycota* phylum and more than 3.8% to *Basidiomycota* phylum. A total of 152 ASVs were identified of which the ten most abundant taxa are presented in Fig. 5. These ten most abundant taxa belonging mainly to the genus *Candida*, *Debaryomyces*, *Kluyveromyces*, *Magnusomyces*, *Pichia* and *Saccharomyces*.

Richness (observed ASV) and evenness (Shannon index) were used to evaluated alpha diversity which represents the microbial variation within a sample (Table 4). A significant difference (p < 0.05) was observed in the alpha-diversities of the microbiota of factories for both bacteria and fungi. F3 had the largest bacterial ASV numbers and a higher Shannon index than other cheese factories. On the contrary, F3 had the lowest fungal ASV numbers and a lower Shannon index than other factories. No significant seasonal variation was observed in the bacterial and fungal alpha-diversity indexes.

Beta-diversity, which represents the diversity between samples showed an overview of the dissimilarities in the bacterial and fungal communities between cheese factories (p < 0.05) (Fig. 6). This factory factor explains 81% of the bacterial variability between samples. The grouping of samples according to factory was linked in part to the presence of either LH or LD in the NWS. The cheese factory factor also explained the 50% fungal variability between samples. Beta-diversity did not reveal any significant difference between the two seasons.

**Table 3**

Strain diversity among thermophilic isolates from natural whey starters for six different factories (F1 to F6) at two seasons, summer and winter, isolated on A. M17 medium (ST: *Streptococcus thermophilus* (St)); B. MRS medium (TL: *Lactobacillus delbrueckii* (Ld) and *Lactobacillus helveticus* (Lh)). Results based on UPGMA clustering of Pearson coefficient. 100% means that the total number of isolates was affiliated to a single strain. Results come from one day out of three days of cheese-making.

<figure><img src="image_6.png" /></figure>
<figure><img src="image_7.png" /><figcaption>Fig. 4. Incidence of ASVs based on 16S rRNA gene of natural whey starter samples from six Comté cheese factories (F1 to F6) at two seasons. The bar graph represents the relative abundance of each species. Only the ten most abundant species are reported, the remaining ASVs are grouped in the category “Others”.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 5. Incidence of ASVs based on ITS2 gene of natural whey starter samples from six Comté cheese factories (F1 to F6) at two seasons. The bar graph represents the relative abundance of each species. Only the ten most abundant species are reported, the remaining ASVs are grouped in the category “Others”.</figcaption></figure>

<caption>**Table 4**</caption>

Richness and evenness of natural whey starters microbiota. Means values (±Standard Deviation) of richness (ASVs observed) and evenness, calculated using Shannon diversity index.

<table><thead><tr><th rowspan="2">Fromagerie</th><th rowspan="2">Season</th><th colspan="2">Bacteria</th><th colspan="2">Fungi</th></tr><tr><th>Richness</th><th>Evenness</th><th>Richness</th><th>Evenness</th></tr></thead><tbody><tr><td rowspan="2">1</td><td>Summer</td><td>35.00 ± 3.74</td><td>0.69 ± 0.04</td><td>41.67 ± 4.50</td><td>1.69 ± 0.11</td></tr><tr><td>Winter</td><td>30.00 ± 2.83</td><td>0.59 ± 0.07</td><td>32.67 ± 2.05</td><td>1.81 ± 0.42</td></tr><tr><td rowspan="2">2</td><td>Summer</td><td>25.67 ± 4.78</td><td>0.52 ± 0.09</td><td>52.00 ± 2.45</td><td>1.58 ± 0.08</td></tr><tr><td>Winter</td><td>23.33 ± 2.36</td><td>0.44 ± 0.02</td><td>57.33 ± 2.05</td><td>2.55 ± 0.01</td></tr><tr><td rowspan="2">3</td><td>Summer</td><td>43.00 ± 1.63</td><td>1.01 ± 0.99</td><td>30.33 ± 6.60</td><td>0.49 ± 0.19</td></tr><tr><td>Winter</td><td>40.00 ± 7.26</td><td>0.96 ± 0.04</td><td>26.67 ± 4.11</td><td>0.31 ± 0.05</td></tr><tr><td rowspan="2">4</td><td>Summer</td><td>37.67 ± 2.05</td><td>0.71 ± 0.01</td><td>62.00 ± 6.53</td><td>2.10 ± 0.09</td></tr><tr><td>Winter</td><td>28.67 ± 1.70</td><td>0.51 ± 0.01</td><td>56.33 ± 8.99</td><td>2.22 ± 0.23</td></tr><tr><td rowspan="2">5</td><td>Summer</td><td>32.67 ± 1.89</td><td>0.38 ± 0.05</td><td>79.33 ± 1.70</td><td>2.74 ± 0.14</td></tr><tr><td>Winter</td><td>35.00 ± 2.16</td><td>0.60 ± 0.09</td><td>67.33 ± 7.59</td><td>1.99 ± 0.05</td></tr><tr><td rowspan="2">6</td><td>Summer</td><td>41.67 ± 3.40</td><td>0.75 ± 0.00</td><td>70.00 ± 3.56</td><td>1.94 ± 0.05</td></tr><tr><td>Winter</td><td>39.00 ± 1.63</td><td>0.61 ± 0.01</td><td>58.33 ± 4.99</td><td>2.42 ± 0.14</td></tr></tbody></table>

## 4. Discussion

NWS cultures are known to be a complex bacterial community with only few dominant species (Parente et al., 2016). This study enhances our comprehension of the microbial composition, diversity, and viability of Comté cheese NWS microbiota, as similarities and differences were investigated across six factories and two seasons using both culture-dependent and DNA-based culture-independent methods for microbial group levels, and species and strain compositions. The results showed that the dominant species were LD, LH and ST, with culturable population levels of the same order of magnitude, for all the factories whatever the season. This is consistent with previous studies carried out on NWS of Comté and Italian cheeses (Bouton et al., 2002; Gatti et al., 2014; Santarelli et al., 2008). Moreover, our work highlighted that the majority of these thermophilic bacteria were viable. It was also observed that the ratio of LD/LH cells varied depending on the cheese factory, with three out of six NWS analysed at both seasons (and one in winter) exhibiting a dominant LD population (up to 3 logs unit difference). The fungi diversity of NWS was also dependent on the cheese factory.
<figure><img src="image_9.png" /><figcaption>**Fig. 6.** Bacterial (16S) and fungal (ITS2) beta-diversity (Bray-Curtis index) of NWS according to the factory (A. 16S, B. ITS2) and season (C. 16S, D. ITS2).</figcaption></figure>

The main aim of the use of NWS in Comté cheese technology was to provide ST whose role is essential during the manufacturing process. Our results confirmed that ST is the dominant species in NWS for all the factories. The adaptive features of ST from NWS allowed to retain its technological function (Bertani et al., 2020). Apart from these thermophilic bacteria, the other microbial groups were much more weakly represented in all NWS. A certain number of these subdominant species were, however, detectable by 16S rRNA and ITS metabarcoding.

No culturable mold were detected on the OGA medium, suggesting they are subdominant in all NWS. Culturable yeast could be counted on OGA medium up to 4.4 log CFU/mL. These results were in accordance with those previously reported in the literature for Parmigiano Reggiano NWS (Coloretti et al., 2016). *Kluyveromyces marxianus* was identified as the dominant yeast species with the highest occurrence (61.5%) followed by *Wickerhamiella pararugosa* (23.1%), *S. cerevisiae* (12.1%) and *Torulaspora delbrueckii* (3.3%). The Bray-Curtis dissimilarity index highlighted significant differences between the factories which is explained by different relative abundances of these species. In our work, ITS analyses results revealed that a majority of yeasts were of the Saccharomycetales order in Comté NWS. This explains why only yeasts were obtained by enumeration on culture medium. In the six cheese factories studied by metabarcoding, the same ten main species of fungi were found, mainly yeasts. The work of Zambonelli et al. (1996) had shown that lactose-fermenting yeasts can co-exist with LAB present in NWS. In the case of Parmigiano Reggiano cheese, it has been shown that these yeasts are not only spoilage agents and they can be beneficial for the factory (Martini et al., 2021).

The use of culture-independent methods provided an additional level of precision regarding TL species that the use of MRS growth medium cannot reliably give. qPCR and 16S rRNA metabarcoding made it possible to highlight differences in the ratio of LD to LH levels between the NWS. As a result, four out of six factories (F1, F3, F5 in winter and F6) showed LD population levels higher than LH levels in NWS. Genotyping confirmed the results for F1 and F3, but showed that LD isolates were in the minority for F5 and F6. This discrepancy may be attributed to the methodology used, i.e. only twelve isolates collected on

only one day of cheese-making instead of three consecutive days for the other methods.

The two culture-independent methods highlighted two types of NWS: the type-LD (LD > LH) and the type-LH (LD < LH), as described by Sola et al. (2022) for the case of Parmigiano Reggiano, except that in this present work LD and LH are always associated with ST. The origin of the dominance of LH or LD could be attributed to the composition of the raw milk used for the preparation of NWS. Unfortunately, qPCR failed to analyze TL composition of milk due to low quantity of extracted DNA. The metabarcoding analyses of raw milk revealed also low percentages of LD and LH, except for LH in F2 and F4 in winter, which would support our hypothesis (data not shown). Otherwise, the technological treatment may shape NWS microbial composition as suggested by Bertani et al. (2020) and Bottari et al. (2010).

NWS are characterized by a low complexity in lactic acid bacteria species. But the study at the strain level showed the coexistence of thermophilic strains as previously observed (Schmid et al., 2018; Somerville et al., 2022). In this present study, the composition of the ST, LD and LH strains differed from one factory to another, offering strain-level diversity. As in the works of Sola et al. (2022) and Erkus et al. (2013), genotyping data showed a significant degree of heterogeneity at strain level with different biotypes among the factories. Similar strains could be also widely dispersed as previously observed by Bouton et al. (2002). For each cheese factory, the composition of the strains also differed between the two seasons. LD strains showed greater diversity than LH strains.

Among the six cheese factories studied, F3 differs from the other factories regarding its microbial composition. It was characterized by a greater diversity of subdominant cultivable populations in winter, notably yeasts and enterococci. However, its fungi diversity was much lower than other factories for both seasons. Regarding dominant thermophilic populations, F3 culturable ST levels were lower than in other factories, but total and viable ST levels obtained by qPCR and viability-qPCR were similar in summer or higher in winter than in other factories. This difference between culturable and viable cells suggests the presence of viable but non culturable cells. However, these viability lev-
els reflected the permeability of the cells without providing information on their metabolic activity. The differences observed between the levels of viable cells and the lower levels of culturable populations highlighted a proportion of viable cells unable to duplicate in the agar medium. This proportion of viable non-culturable cells was previously already discussed in the works of Bottari et al. (2010) and Gatti et al. (2006). The data obtained for Comté NWS agree with the observations made for Grana Padano and Parmigiano Reggiano. F3 also presented a composition of thermophilic bacteria which differed by a lower relative abundance of ST and a higher relative abundance of TL. These observed differences may come from NWS-preparation. Data from previous studies have already highlighted the importance of the technological pressure during NWS preparation in the development of the most abundant microbial species, notably the composition of the environment and raw milk as well as the temperature gradients during NWS-making and cheese-making (Bertani et al., 2020; Rossetti et al., 2008). The lower temperature of curd cooking in F3 (54 or 54.5 °C vs 55.5 or 56 °C in the other factories) may have favoured the development of TL as well as that of subdominant populations. Moreover, the preparation of NWS from F3 was made in a plastic food container rinsed with hot water, which could have allowed the conservation and then the development of subdominant populations such as yeasts and enterococci.

Differentiation of viable and non-viable cells is important to evaluate the ability of NWS to perform its role during cheese-making. The level of viability of NWS can be regulated by different stress factors directly influenced by the NWS-making process, such as freezing for NWS storage, or cheese manufacture process, such as curd cooking (Gatti et al., 2006). Our approach of the global viability measurement using double fluorescent staining showed that 98.4%–99.8% of NWS cells had an intact membrane and intracellular esterase activities, whatever the cell level in NWS. These levels may correspond to the sum of viable cells of the dominant species found in Comté NWS (ST, LD and LH). qPCR carried out on DNA extracted from both non-PMA and PMA-treated cells allows to quantify viable cells specific for each thermophilic species. PMA treatment should prevent amplification of DNA from cells with compromised membrane, so that amplification represents live cells based on membrane integrity. This approach showed that NWS essentially contain viable thermophilic cells, whatever the cell level (Figs. 2 and 3). As highlighted by the fluorescence microscopy results, qPCR and viability-qPCR confirmed that NWS contains mainly live cells.

The effect of the season on the NWS microbial consortium composition and viability was studied because breeding (diet, bedding material) and weather conditions (Chemidlin Prévost-Bouré et al., 2021; Li et al., 2018; Montel et al., 2014) vary, which may affect milk microbiota. However, the effect of the cheese factory prevailed.

## 5. Conclusion

This study offers an in-depth understanding of NWS composition in PDO Comté cheese production. The combination of media culture, qPCR and metabarcoding allowed a "picture" of NWS microbiota, complementing each other for the identification and quantification of microbial groups and species. Genotyping provided an additional level of information on the different thermophilic strains. Viability-qPCR allowed absolute quantification of microbial species and was shown to be more informative than fluorescence microscopy, in the case of the study of NWS. However, the use of qPCR required previous knowledge of the microbial population composition. Our findings highlight that the cheese factory plays a pivotal role in shaping the microbiota composition and its viability within the NWS. Notably, we identified two distinct types of NWS, differentiated primarily by their respective abundances of ST/LD and ST/LH populations. This bifurcation presents a new avenue for exploring the reasons behind this difference LH/LD abundance among factories e.g. raw milk microbial composition, dynamic interactions between these microbial communities during NWS

preparation (incubation at a decreasing temperature). Further investigation is essential to decipher the implications of these two NWS types on Comté cheese's overall quality and sensory attributes. A particularly intriguing aspect for future research is understanding how variations in NWS composition, especially in the context of non-viable cell content, influence the cheese's flavor profile and texture. Such insights will not only enrich our comprehension of Comté cheese microbiology but also guide optimized cheese-making practices that could enhance quality.

## Funding

This work was financially supported by a CIFRE grant from the « Assoction Nationale de la Recherche et de la Technologie, France », by the Bourgogne-Franche-Comté Region and by the Comité Interprofessionnel de Gestion du Comté.

## Uncited references

Irlinger et al., 2023.

## CRediT authorship contribution statement

**Jade Lutin:** Writing – review & editing, Writing – original draft, Visualization, Investigation, Conceptualization. **Franck Dufrene:** Visualization, Investigation. **Philippe Guyot:** Visualization, Investigation. **Romain Palme:** Investigation. **Christine Achilleos:** Writing – review & editing, Supervision, Conceptualization. **Yvette Bouton:** Writing – review & editing, Supervision, Conceptualization. **Solange Buchin:** Writing – review & editing, Supervision, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

The authors kindly acknowledge Quentin Trouillot (CTFC) who collected the whey starter cultures analysed in this work. They also thank the six different cheesemakers for the supply of NWS. The authors thank the INRAE GeT-Biopuces Platform (http://get.genotoul.fr) for assistance in 16S rDNA and ITS2 amplicon sequencing and the INRAE MIGALE bioinformatics platform (http://migale.jouy.inra.fr) for providing computational resources. They also thank the reviewers for their constructive comments and S.E. Anderson for reviewing the English of the manuscript.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.fm.2024.104521.

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