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Article

Alcohol-Free Beer Produced Using Maltose-Negative Wine Yeast Saccharomyces cerevisiae with Probiotic Potential

by
Emre İlpars
1,2,
Štěpánka Titlová
1,
Katarína Hanzalíková
1,2,
Ivana Křížová
1 and
Tomáš Brányik
1,2,*
1
Department of Biotechnology, University of Chemistry and Technology Prague, Technická 5, 166 28 Prague, Czech Republic
2
Research Institute of Brewing and Malting, Lípová 15, 120 44 Prague, Czech Republic
*
Author to whom correspondence should be addressed.
Fermentation 2023, 9(9), 805; https://doi.org/10.3390/fermentation9090805
Submission received: 10 August 2023 / Revised: 26 August 2023 / Accepted: 30 August 2023 / Published: 31 August 2023
(This article belongs to the Section Fermentation for Food and Beverages)
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Abstract

:
The ideal yeast for the production of alcohol-free beer does not form ethanol, produces a distinct and pleasant taste and has probiotic properties. This study characterized the potential of a wine yeast, Saccharomyces cerevisiae CCM 9181, to be an ideal alcohol free beer strain. It was found to be maltose-negative, and the ethanol content in fermented all-malt wort has never exceeded the legal limit of 0.5% v/v. Its specific growth rate (µ) was the highest at 25 °C (μ = 0.41 ± 0.01 h−1) and it was not affected by iso-α-bitter acids (15–50 IBU, international bitterness units). A response surface methodology was used to optimize the temperature and pitching rate affecting the formation of total higher alcohols and esters. A statistical analysis of the experimental data revealed that temperature affected esters most significantly, while both temperature and pitching rate had the most significant effects on higher alcohols. The sensory properties of beers were evaluated by trained panelists and they were described as malty, clove-like, having a very mild bitterness and a bouquet of white wine. The survival rate of S. cerevisiae CCM 9181 after simulated passage through the gastrointestinal tract was investigated as a first step to evaluate its probiotic properties. Our analyses show that Saccharomyces cerevisiae CCM9181 is a suitable candidate for the large-scale commercial production of alcohol-free beer and has probiotic potential that needs to be studied further.

1. Introduction

Beer is one of the most widely consumed beverages worldwide. Raw ingredients and fermentation by-products are sources of a variety of antioxidants, such as phenolic compounds, melanoidins, vitamins B6, B12, E, and C, and selenium [1,2,3]. However, the presence of more than 1.2% v/v of ethanol prevents beer from being described as having positive nutritional or health benefits [4].
With the growing awareness of the importance of health and wellbeing, as well as the harm associated with alcohol consumption, the availability and demand for alcohol-free beverages has increased in recent years [5,6,7]. In addition to this awareness, lifestyle trends and improvements in production methods are two of the primary contributing factors that make alcohol-free beers (AFB) popular among consumers [8].
Parallel to this consumer demand, interest in the potential health benefits of AFB has also grown. Recent publications suggest that AFB can prevent oxidative stress, preserve endothelial function, inhibit thrombogenic activity and tumor cell growth by inducing DNA damage and modifying methylation status of such cancer cells [1,9]. Meanwhile, a lack of alcohol, the primary contributor of the energy content in beer, reduces the calorie content of the AFB as a healthier alternative [10].
However, as alcohol contributes to the organoleptic properties of the beer, its absence is easily perceived. Moreover, negative views on the taste of AFB influence its consumption frequency [11]. Preserving the aroma and flavor of AFB using physical or biological methods is one of the key production challenges [12,13,14,15]. A valuable alternative to these methods is the use of yeasts from sources other than beer and that have a limited ability to utilize wort carbohydrates, i.e., maltose-negative yeasts, but are able to produce typical beer-flavor compounds [16,17].
In addition to being able to produce favorable AFB, alternative yeasts enable the development of functional beers [8,18]. Using probiotic yeast as a starter culture or in a co-culture is a novel approach to producing AFB with increased potential health benefits [19,20,21]. Survival through the gastrointestinal track is a crucial factor for the preliminary evaluation of probiotic functionalities; moreover, recent studies suggest the following: (a) that a viable-but-not-culturable (VBNC) state exists in yeast, and therefore culturability should not be the only criterion to determine microbial viability and alternative methods can be employed [22,23,24]; (b) that significant health benefits can arise from dead/inactivated cells and their metabolic byproducts, expanding probiotic terminology [25,26].
In this study, we investigate the fermentation and probiotic potential of Saccharomyces cerevisiae CCM 9181 isolated via wine fermentation. We analyzed the growth characteristics of the yeast at different temperatures and in the presence of varying levels of ethanol and iso-alpha-bitter acids. Then, we evaluated the effect of temperature and pitching rate on the production of volatile compounds in beer and optimized these process variables using a response surface model (RSM). Finally, we used both plate counting and flow cytometry to test the survival rates of yeast under in vitro simulated gastrointestinal conditions.

2. Materials and Methods

2.1. Microorganisms

The yeast strain Saccharomyces cerevisiae CCM 9181 (S. cerevisiae) was isolated at the end of the spontaneous fermentation of grape must and prepared for further use via selection and repeated inoculation on malt agar with tetracycline [27]. The sugar metabolism of the yeast was initially determined using API ID 32c Set (Biomerieux, Marcy-l’Étoile, France) and the molecular identification of the yeast was performed with specific backward and forward primers (ITS 4 and ITS 1) and compared using BLAST [28].
The brewing yeast Saccharomyces pastorianus RIBM 95 (S. pastorianus) and probiotic yeast Saccharomyces cerevisiae var. boulardii RIBM 170 (S. boulardii) were used as control strains. All three strains were obtained from the culture collection of the Research Institute of Brewing and Malting (RIBM), Czech Republic.

2.2. Media, and Cultivation

Yeast peptone dextrose (YPD) medium containing 20 g/L of glucose, 20 g/L of bacteriological peptone and 10 g/L of yeast extract was used to propagate the yeast, and to test growth kinetics at different temperatures (3–30 °C), and in the presence of either ethanol (0.5, 2.5 and 5.0% v/v) or iso-alpha-bitter acids (15, 30 and 50 IBU). YPD agar plates containing 17 g/L of agar were used to store the yeasts at 4 °C.
Prior to pitching, yeasts were propagated in 250 mL of YPD medium for 24 h at 25 °C on a laboratory shaker (120 rpm) and collected using a centrifuge at 3000 rpm for 20 min. The pellet was washed with sterile water and 2.5 g of washed yeast pellet was pitched into 750 mL of YPD medium on a shaker until the yeast inoculum was homogenous. The absorbance was measured at 600 nm (SPEKOL 1300, Analytik Jena GmbH, Jena, Germany), using pure YPD medium as the reference. The suspension was then divided equally into three 500 mL Erlenmeyer flasks and cultivated further on a laboratory shaker in an incubator at a given temperature with the possible addition of ethanol or iso-alpha-bitter acids. The samples were collected and analyzed for biomass and glucose content. The process was carried out aseptically, and media and all glassware were autoclaved at 121 °C for 20 min.

2.3. Wort Fermentation

S. cerevisiae CCM 9181 was propagated in 250 mL of YPD medium in 500 mL Erlenmeyer flasks at 10 °C for 9 days on a laboratory shaker prior to pitching. All-malt wort was prepared in a pilot-scale brewhouse (Pacovske strojirny, Pacov, Czech Republic) at an original extract concentration of 10% (w/w) and diluted to 6% (w/w) with sterile tap water. Fermentation was carried out in 500 mL sterile fermentation cylinders with 400 mL of wort at different temperatures and pitching rates (Table 1). The wort was not aerated prior to pitching. Yeasts were counted under a microscope using a hematocytometer (Bürker Chamber, 0.100 mm depth, 0.0025 mm2, Hecht Glaswarenfabrik GmbH & Co KG, Sondheim vor der Rhön, Germany). Fermentation was monitored with a refractometer (PR-32α, Atago, Kyoto, Japan) until the apparent extract was constant for 3 consecutive days. At the end of fermentation, beer samples were transferred to centrifuge bottles, and centrifuged at 8500 rpm (Sorvall SLC-6000, Thermo Fisher Scientific, Waltham, MA, USA) for 15 min at 4 °C. Then, the supernatant was transferred into sterile collection bottles and frozen at −20 °C until instrumental analysis was performed.

2.4. Experimental Design Based on Response Surface Methodology

To investigate the influence of process variables on the formation of sensorially active compounds by S. cerevisiae CCM 9181 during AFB fermentation, a response surface methodology (RSM) was applied using Design Expert (version 10.0, Stat-Ease Inc., Minneapolis, MN, USA). An alpha face-centered central composite design, comprising two independent factors, temperature (T) and pitching rate (P), and two replications was chosen (Table 1). In total, 11 lab-scale rounds of fermentation were conducted to investigate the production of total higher alcohols (HA) and total esters (ES) (Table 2). A multiple regression analysis of the experimental data was processed, a quadratic model was developed, the polynomial equations were visualized as a 3D surface model, and the experimental data were statistically evaluated via an analysis of variance (ANOVA).

2.5. Analytical Methods

The analysis of wort carbohydrates, fructose, glucose, maltose, maltotriose and dextrins was performed via HPLC with RI detection on an ion-exchange chromatographic column in an Ag+ cycle in the isocratic mode. Calibration solutions were prepared from standards of the basic carbohydrates: D(+), glucose; D(−), fructose and maltose. Oligosaccharides were calibrated to a maltose standard [29].
A basic beer analysis (of the original, real, and apparent beer extract) was carried out on DMA 5000 (Anton Paar GmbH, Graz, Austria) in accordance with EBC method 9.4, 2010 [30]. Beer alcohol content was measured via NIR spectroscopy (Anton Paar GmbH, Graz, Austria) on Alcolyzer in accordance with EBC method 9.2.6, 2010 [31]. Diacetyl content was measured via gas chromatography in accordance with EBC method 9.24.2, 2010 [32]. Lower-boiling-point volatile compounds (ethyl acetate, isoamyl acetate, ethyl formate, 2-phenylethyl acetate, isobutanol, n-propanol, 2-phenylethanol, and 2- and 3-methylbutanol) were evaluated via gas chromatography in accordance with EBC method 9.39, 2009 [33]. All analyses were carried out three times and the average values are presented with absolute deviations.

2.6. Sensory Evaluation

Two samples of AFB fermented at 15 and 20 °C were prepared with a pitching rate of 2 × 106 cells/mL and submitted for sensory evaluation by a panel of ten trained evaluators who rated the sensory perceptions: bitterness, fullness, bitterness after swallowing, maximum bitterness intensity, bitterness decay, astringency, sweetness, acidity (0—none, 1—very weak, 2—weak, 3—medium, 4—strong, and 5—very strong) and overall impression rated on a nine-point scale (1—excellent without defects, 5—average, and 9—undrinkable beer). The sensory analysis was carried out at the Research Institute of Brewing and Malting, a.s., in accordance with an accredited method (ČSN 56 0186-2; ČSN EN ISO 5495; ČSN EN ISO 4120; ČSN ISO 8587).

2.7. Resistance to the Simulated Gastrointestinal Conditions

In vitro gastrointestinal (GI) transit simulation was performed as described in Pennacchia et al., 2008, with slight modifications [34]. Artificial gastric juice (AGJ) was prepared with 6.2 g/L of NaCl, 2.2 g/L of KCl, 0.22 g/L of CaCl2, 1.2 g/L of NaHCO3, and 3 g/L of pepsin (added after sterilization by membrane filtration; PTFE 0.45 µm, Labicom, Prague, Czech Republic), the pH was adjusted to 2.5 with HCl and it was autoclaved at 110 °C for 25 min. S. cerevisiae, S. boulardii, and S. pastorianus were propagated in triplicate for 24 h in 20 mL of 6% (w/v) malt extract with 7 g/L of glucose on a laboratory shaker. Cells were collected via centrifugation (4000 rpm for 10 min), resuspended in 10 mL of AGJ and incubated at 37 °C for 2.5 h on a laboratory shaker at 120 rpm. Artificial intestinal fluid (AIF) was prepared with 1.28 g/L of NaCl, 0.239 g/L of KCl, 6.4 g/L of NaHCO3, 0.3% (w/v) bile salts, and 0.1% (w/v) pancreatin (the latter two were added after sterilization via membrane filtration), the pH was adjusted to 7.5 with HCl and the AIF was autoclaved at 110 °C for 25 min. All three strains were propagated and incubated in AGJ as described above, collected via centrifugation at 4000 rpm for 10 min, resuspended in 10 mL of AIF and incubated at 37 °C for 5 h on a laboratory shaker at 120 rpm.
Samples obtained from AGJ and AGJ + AIF incubations were collected and serially diluted with Ringer’s solution (Sigma Aldrich, St. Louis, MI, USA) for plate counting. Cells were inoculated on malt agar (malt extract agar in an amount of 17 g/L, and glucose in an amount of 7 g/L) plates and kept for two days at 25 °C, and the survival rate (%) was calculated from the comparison of colony forming units (CFU’s) with/without the simulation of GI conditions. A post hoc Scheffe’s test was used to support the statements on the significance (p-value < 0.05) between results. Statistical parameters were obtained using MS Excel software (version: Microsoft 365, Microsoft Corp., Redmond, WA, USA).

2.8. Determining Viability by Flow Cytometry

Two milliliters of samples was collected in Eppendorf tubes following AGJ and AGJ + AIF incubations, centrifuged (10,000 rpm, 3 min) and resuspended in Ringer’s solution. Five microliters of propidium iodide (PI, 30 mM) were added and incubated in the dark for 15 min [35,36]. The survival rate of yeasts was determined from ten thousand cells using a BD FACSAria III flow cytometer (excitation, 488 nm; emission recorded at 562–588 nm), and the results were processed with the BD FACSDiva software (version 8, BD Biosciences, Franklin Lakes, NJ, USA). A post hoc Scheffe’s test was used to support the statements on significance (p-value < 0.05) between results. Statistical parameters were obtained using MS Excel software (version: Microsoft 365, Microsoft Corp., Redmond, WA, USA).

3. Results

3.1. Growth Characteristics of Cultures in Laboratory Settings

The strain S. cerevisiae CCM 9181 has been shown to be non-maltose-fermenting via API tests. Its growth characteristics were investigated at different temperatures (3–30 °C), and under the impact of different concentrations of ethanol (0–5% v/v) and iso-alpha-bitter acids (0–50 IBU). The highest specific growth rate (μ) was achieved at 25 °C (μ = 0.41 h−1) and the lowest measurable growth rate was achieved at 8 °C (μ = 0.08 h−1) with a 24 h lag phase (Table 3). Similarly, the highest biomass yield (Yx/s—gbiomass/gglucose) was observed at 25 °C (Yx/s = 1.82) and the lowest (Yx/s = 0.44) was observed at 8 °C (Table 3). The yeast did not show any sign of growth at 3 °C.
Growth curves of S. cerevisiae were also measured in YPD medium at 20 °C with different concentrations of iso-α-bitter acids and ethanol. Specific growth rate (μ) was affected by the presence of iso-α-bitter acids, with values that were 17.6% lower at 50 IBU compared to those at 15 and 30 IBU (Table 3). The biomass yield coefficients (Yx/s = 1.3) were uniform throughout these experiments.
A slight decrease in μ of 23.5% was observed in YPD with 5.0% (v/v) ethanol compared to the value in the absence of ethanol (Table 3). The μ value at 2.5% (v/v) ethanol decreased by 9% (Table 3). The yield coefficients (Yx/s = 1.1) in the presence of ethanol (2.5 and 5.0% v/v) were 15% lower than those in the control trial without ethanol.

3.2. Optimization of Process Variables

The optimization of two variable factors, fermentation temperature (T) and pitching rate (P), for the formation of total higher alcohols (HA) and esters (ES), was carried out. The alcohol content of the fermented wort (6% w/w) was always below 0.5% v/v (Table 2), the legally defined limit for AFB in the EU, per Decree No 248/2018 of the Ministry of Agriculture [37].
The laboratory-scale experiments aimed at the optimization of process variables were accompanied by carbohydrate analyses. Prior to fermentation, the maltose concentration in 6% (w/w) wort was 21.2 g/L. After fermentation at each temperature studied (5, 10 and 15 °C), the final concentration of this disaccharide was unchanged, confirming the result of the API test. The monosaccharides, glucose and fructose were completely consumed at fermentation temperatures of 15 and 10 °C, whereas at 5 °C, fructose was not used (2.0 g/L) and the glucose concentration decreased by about 50% from 6.9 g/L to 3.5 g/L. The amount of sugars metabolized also corresponded to the trend in alcohol production, with the highest concentrations at 15 and 10 °C ranging from 0.38 to 0.46% (v/v), while at 5 °C the ethanol concentration ranged from 0.09 to 0.017% (v/v) (Table 2).

3.3. Statistical Evaluation of Process Variables

The results of the ANOVA analysis of the experimental data are shown for ES (Table 4) and HA (Table 5). The models for the formation of ES and HA by the yeast Saccharomyces cerevisiae CCM 9181 had high F-values (39.86 and 50.01, respectively) and low p-values (0.0005 and 0.0003, respectively) (Table 4 and Table 5). These values indicate that the models are highly significant. The closeness of the R2 values and the adjusted Adj.R2 confirms the good correlation between experimental and predicted values. All parameters show that the obtained models were able to predict the responses correctly. Sufficient accuracy is indicated by the signal-to-noise ratio, which for both ES and HA models reached the desired high values (18.144 and 19.337, respectively) (Table 4 and Table 5).
Via a multiple regression analysis of the experimental data performed in Design Expert software second-order polynomial equations were generated.
Ester formation by the yeast S. cerevisiae CCM 9181 was statistically most influenced by the linear term of T (p-value ˂ 0.05). The linear term of P had a statistically less significant (p-value ˂ 0.1) effect on ES formation (Table 4). The interaction term TP and the quadratic terms T2 and P2 were not statistically significant (p-value ˃ 0.1). The formation of HA was influenced by the linear terms T and P and by the quadratic term T2 (p-value ˂ 0.05). The other terms of the quadratic equation had no statistically significant (p-value ˃ 0.1) effect on the formation of HA (Table 5). The resulting equations for the formation of the different groups of volatiles formed by S. cerevisiae CCM 9181, expressed using the coded factors, are as follows:
ES = 0.38 + 0.18 ∙ T − 0.03 ∙ P − 0.03 ∙ T ∙ P + 3.18 ∙ 10−2 ∙ T2 + 1.18 ∙ 10−2 ∙ P2
HA = 25.01 + 8.10 ∙ T + 1.60 ∙ P + 0.03 ∙ T ∙ P − 3.93 ∙ T2 − 1.12 ∙ P2
A graphical representation of these regression equations is shown in the 3D response plots (Figure 1 and Figure 2). In the case of ES formation by yeast, the amount of ES increased with increasing T and also slightly decreased with decreasing P. Increasing T also contributed significantly to the formation of HA, the production of which increased significantly, and the same trend was observed in the case of P. The local maximum for HA formation was reached at 15 °C and 10 × 106 cells/mL (Figure 2), whereas for ES formation, this was reached at 15 °C and 2 × 106 cells/mL (Figure 1). The combination of optimal independent variables to produce AFB was determined to be a temperature of 15 °C and a concentration of 2 × 106 cells/mL.

3.4. Sensory Evaluation of the Alcohol-Free Beer

Based on the results of process optimization, an AFB (T = 15 and 20 °C, P = 2 × 106 cells/mL) was produced using S. cerevisiae CCM 9181 and subjected to sensory analysis by the tasting panel of RIBM. The AFB obtained a final score of 6.5, where its flavor was described as malty, clove-like, having very mild bitterness and a bouquet of white wine. The overall subjective impression of the AFB was very good. The content of the selected analytes in AFB (Table 6) did not exceed sensory threshold concentrations, with the exception of diacetyl, which can taste like butter at concentrations above 0.1 mg/L [38]. However, the detected concentration of diacetyl was in the range usually found in AFB produced via limited fermentation [13]. A buttery off-flavor was not detected in AFB by the tasting panel.

3.5. Gastrointestinal Survival Rate

The survival abilities of S. boulardii, S. pastorianus and S. cerevisiae in the simulated human GI track were evaluated. All three strains were exposed initially to artificial AGJ for 2.5 h at 37 °C. While the cell number of S. boulardii showed no change after this exposure, the survival rates of S. cerevisiae and S. pastorianus were significantly reduced (Table 7). The differences in survival rates of each strain in AGJ were statistically significant (p-value < 0.05).
To determine the survival percentage of the yeasts under intestinal conditions, the samples that were exposed to AGJ as described above were subsequently incubated in AIF for five hours at 37 °C. Two yeast strains, S. boulardii and S. cerevisiae, showed almost identical survival rates of 4.1 ± 0.3% and 4.0 ± 0.01%, respectively, while only 1.1 ± 0.2% of the original population of S. pastorianus survived the combined effect of AGJ + AIF (Table 7). The survival rate of S. pastorianus in AGJ + AIF was lower by a statistically significant amount (p-value < 0.05).
Survival abilities of tested yeast strains were also evaluated by staining with propidium iodide (PI) and flow cytometry. All three strains showed almost no PI positive signals when they were exposed only to AGJ. The differences in the survival rates of the three strains in AGJ were statistically insignificant (p-value ˃ 0.05). Subsequent exposure to AIF had a major impact on the brewing yeast S. pastorianus such that only 6% of the cells survived, while the known probiotic S. boulardii and the wine strain S. cerevisiae showed 99% viability (Table 8). The survival rate of S. pastorianus in AGJ + AIF, as determined by PI staining, was lower by a statistically significant amount (p-value < 0.05).

4. Discussion

Growing awareness of the importance of health and wellbeing, as well as the negative associations of alcohol consumption, is leading consumers to alternative beers, including AFB.
While the interest in AFB is increasing globally, preserving the organoleptic properties during the use of physical and biological production methods remains the main challenge for the widespread acceptance of these beer types. Additionally, these processes may cause a reduction in health-promoting phenolic compounds [39]. Using a special yeast that can produce such beers without requiring additional processing steps can create unique flavor profiles while preventing the loss of volatile compounds during production.
This work is focused on exploring the potential of wine-originating S. cerevisiae CCM 9181 to produce AFB, with a further investigation of its probiotic properties. S. cerevisiae, with its GRAS/QPS (generally regarded as safe/qualified presumption of safety) status, also introduces a strategic advantage for the commercialization of such AFBs produced with this yeast.
The initial characterization of basic growth parameters showed that the highest μ of S. cerevisiae CCM 9181 is lower than that of top-fermenting yeasts, and closer to bottom-fermenting yeasts [40]. This study also examined the impact of iso-alpha-bitter acids on μ at concentrations ranging from 15 to 50 IBU. Even with the highest concentration of 50 IBU, exceeding the levels typically found in commercially available beers, the presence of iso-α-bitter acids did not affect μ. The presence of ethanol in the medium (0.5–5.0% (v/v)) indicated that the highest tested concentration of 5.0% (v/v) led to a 15% decrease in μ. However, the highest ethanol concentration produced by S. cerevisiae CCM 9181 during subsequent fermentation experiments remained below 0.5% (v/v). From the technological point of view, this is an advantage over brewer’s (S. pastorianus) and probiotic yeasts (S. boulardii) [21], which tend to overproduce ethanol in the case of insufficient process control.
A response surface methodology was used to examine the effect of temperature and pitching rate, as independent variables, on the formation of fermentation by-products to improve the flavor profile of AFB [41]. Formation of both ES and HA from S. cerevisiae CCM 9181 increased with higher temperatures in accordance with the previous studies [42,43,44]. Pitching rate, on the other hand, was observed to have a limited impact on the formation of ES [45], while increasing the formation of HA [46]. Overall, the formation of HA by S. cerevisiae CCM 9181 was higher than that by probiotic yeast [21] or brewer’s yeast in a limited batch [13] and under continuous fermentation [47]. Overproduction does not apply for the formation of ES by S. cerevisiae CCM 9181, which is comparable with the results of previous studies on AFB. However, since ES are synthesized by yeast from organic acids and alcohols (including HA) [48], the higher levels of HA might result in increased ES levels during prolonged fermentation.
Viability is an inherent property of probiotics, which are defined as “live microorganisms which, when administered in adequate amounts, confer a health benefit on the host” [49]. Both this definition and its modified version [50] emphasize the importance of maintaining the structural integrity of probiotic strains as they navigate the upper digestive tract [8]. To estimate this integrity after exposing the strains to simulated gastrointestinal conditions, besides traditional plate counting, flow cytometry was used to determine the exclusion of propidium iodide (PI) by an intact membrane [23]. The observations for S. cerevisiae CCM 9181 showed a discrepancy in viability quantification via plate counting versus flow cytometry methods, suggesting that the yeast stressed by AGJ and AIF could be in a viable (according to PI staining) but non-culturable state (according to the results of plate counting). This is related to the fact that a clear definition of microbial viability is lacking, especially when it comes to viable but not culturable (VBNC) microorganisms [24].
The VBNC state is described as dormant microorganisms with low metabolic activity and an inability to divide without additional recovery attempts [51]; this was mostly studied in bacteria. However, recent studies on yeast reported the presence of VBNC under various stress factors such as pesticides [52], high phenol concentrations [53], sulfites [54], and isomerized hop extract [55] in varying degrees, including up to a complete loss of the culturability of the yeast population. Further investigation is to be carried out to confirm the presence of the VBNC state in S. cerevisiae CCM 9181 exposed to simulated gastrointestinal conditions.
The potential probiotic properties of S. cerevisiae strain CCM 9181 will also be studied. The eventual confirmation of cell inactivation via passing it through a simulated gastrointestinal system does not mean that the cells cannot have a probiotic effect. Studies have revealed that dead/inactivated cells as well as their cell metabolites can have significant health benefits [25,26].
The industrial use of this strain will require large-scale brews. There are several method of use in the entire fermentation process, during secondary fermentation, or just bottle conditioning. The first use of the strain S. cerevisiae CCM 9181 in an industrial brewery has already taken place [56].

5. Conclusions

The production and sale of alcohol-free beers is lucrative for breweries due to the lower production costs and usually more favorable taxation conditions. The consumption of alcohol-free beers is also in line with the effort to reduce alcohol consumption, which has a positive societal impact. Increasing the attractiveness and availability of this product for consumers is therefore in the interest of both producers and society. Positive health claims related to alcohol-free beers have not yet been fully exploited in terms of marketing. This work, aimed at demonstrating that yeast strains providing simultaneous technological advantages (limited ethanol but sufficient flavor formation) and probiotic effects could be an interesting part of an innovative product. The wine yeast S. cerevisiae CCM 9181 characterized in this work combines low alcohol formation (maltose negative), the ability to produce alcohol-free beer with the sensory properties of a bouquet of white wine and a significant survival rate under simulated gastrointestinal conditions.

Author Contributions

Conceptualization, E.İ., K.H. and T.B.; methodology, E.İ., Š.T., K.H. and I.K.; formal analysis, E.İ., Š.T. and K.H.; data curation, E.İ., Š.T. and I.K.; writing—original draft preparation, E.İ.; writing—review and editing, I.K. and T.B.; visualization, E.İ. and Š.T.; supervision, T.B. All authors have read and agreed to the published version of the manuscript.

Funding

The work was supported by Ministry of Agriculture of the Czech Republic (institutional support MZE-RO1923).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Fermentation 09 00805 g001
Figure 1. Response surface and experimental data of ester (ES) formation by S. cerevisiae CCM 9181 in response to two independent variables (T—temperature; P—pitching rate).
Figure 1. Response surface and experimental data of ester (ES) formation by S. cerevisiae CCM 9181 in response to two independent variables (T—temperature; P—pitching rate).
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Fermentation 09 00805 g002
Figure 2. Response surface and experimental data for the formation of higher alcohols (HA) by S. cerevisiae CCM 9181 in response to two independent variables (T—temperature; P—pitching rate).
Figure 2. Response surface and experimental data for the formation of higher alcohols (HA) by S. cerevisiae CCM 9181 in response to two independent variables (T—temperature; P—pitching rate).
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Table 1. Independent variables, corresponding to coded levels and actual values for fermentation trials.
Table 1. Independent variables, corresponding to coded levels and actual values for fermentation trials.
SymbolIndependent Variable (Units)Coded Level
−101
TTemperature (°C)51015
PPitching rate (×106 cells/mL)2610
Table 2. Central composite design matrix and response values for total higher alcohols, total esters, and ethanol formation by S. cerevisiae CCM 9181 during the fermentation of 6% (w/w) wort as a result of variation in process variables.
Table 2. Central composite design matrix and response values for total higher alcohols, total esters, and ethanol formation by S. cerevisiae CCM 9181 during the fermentation of 6% (w/w) wort as a result of variation in process variables.
FactorsResponses
TPHA (mg/L)ES (mg/L)Ethanol (% v/v)
+1−125.300.640.44
−1013.200.240.16
−1+113.800.250.17
0−124.010.430.38
0+124.300.360.41
+1029.500.590.46
+1+130.500.530.46
−1−109.700.240.09
0024.100.330.41
0024.300.360.42
0026.100.420.42
T—temperature, P—pitching rate, HA—higher alcohols, and ES—esters.
Table 3. Specific growth rate for S. cerevisiae CCM 9181 grown in YPD medium at different temperatures and concentrations of iso-α-bitter acids and ethanol.
Table 3. Specific growth rate for S. cerevisiae CCM 9181 grown in YPD medium at different temperatures and concentrations of iso-α-bitter acids and ethanol.
Temperature
(°C)		Iso-α-Bitter Acids (IBU)Ethanol
(% w/v)		µ
(h−1)
30000.38 ± 0.01
25000.41 ± 0.01
20000.34 ± 0.02
15000.18 ± 0.06
8000.08 ± 0.01
300-
201500.34 ± 0.01
203000.34 ± 0.02
205000.28 ± 0.03
2000.50.34 ± 0.01
2002.50.31 ± 0.02
2005.00.26 ± 0.01
μ—specific growth rate; IBU—international bitterness unit.
Table 4. ANOVA of the quadratic model of ester (ES) formation by S. cerevisiae CCM 9181 in response to changes in fermentation temperature and pitching rate.
Table 4. ANOVA of the quadratic model of ester (ES) formation by S. cerevisiae CCM 9181 in response to changes in fermentation temperature and pitching rate.
SourceSSQdfMSQF-Valuep-Value
Model0.1950.0439.680.0005
T0.1810.18185.68<0.0001
P4.80 × 10−314.80 × 10−35.060.0744
TP3.60 × 10−313.60 × 10−33.780.1095
T22.60 × 10−312.60 × 10−32.700.1614
P24.00 × 10−414.00 × 10−40.370.5680
LoF6.00 × 10−432.00 × 10−4
PE4.20 × 10−322.10 × 10−3
R20.9754
Adj.R20.9508
SSQ—sum of squares, df—degree of freedom, MS—mean square, LoF—lack of fit, PE—pure error, T—temperature, and P—pitching rate.
Table 5. ANOVA of the quadratic model of higher alcohol (HA) formation by S. cerevisiae CCM 9181 in response to changes in fermentation temperature and pitching rate.
Table 5. ANOVA of the quadratic model of higher alcohol (HA) formation by S. cerevisiae CCM 9181 in response to changes in fermentation temperature and pitching rate.
SourceSSQdfMSQF-Valuep-Value
Model461.26592.2550.010.0003
T393.661393.66213.40<0.0001
P15.33115.338.310.0345
TP0.3010.300.160.7023
T239.11139.1121.200.0058
P23.2013.201.730.2449
LoF6.8032.27
PE2.4321.21
R20.9804
Adj.R20.9608
SSQ—sum of squares, df—degree of freedom, MS—mean square, LoF—lack of fit, PE—pure error, T—temperature, P—pitching rate.
Table 6. Results of analysis of higher alcohols, esters, aldehydes, vicinal diketones and sulfur compounds in alcohol-free beer fermented with S. cerevisiae CCM 9181 at 15 °C and 2 × 106 cells/mL.
Table 6. Results of analysis of higher alcohols, esters, aldehydes, vicinal diketones and sulfur compounds in alcohol-free beer fermented with S. cerevisiae CCM 9181 at 15 °C and 2 × 106 cells/mL.
CompoundsAnalyteConcentration (mg/L)
Higher alcoholsisobutanol1.80
n-propanol4.00
2-phenylethanol1.20
2- and 3-methylbutanol18.30
Estersethyl acetate0.48
isoamyl acetate0.14
2-phenylethyl acetate0.02
Aldehydesacetaldehyde1.40
benzaldehyde1.5 × 10−3
Vicinal diketonesdiacetyl0.167
Sulphur substancespentanedione0.012
methional4.96 × 10−3
Table 7. Yeast counts and survival of yeast after exposure to the artificial gastric juice, and artificial gastric juice with artificial intestinal fluid. Means with at least one letter that is the same are not significantly different (p > 0.05). A comparison of statistical significance is presented separately for each column.
Table 7. Yeast counts and survival of yeast after exposure to the artificial gastric juice, and artificial gastric juice with artificial intestinal fluid. Means with at least one letter that is the same are not significantly different (p > 0.05). A comparison of statistical significance is presented separately for each column.
AGJ (Cells/mL)Survival % in AGJAGJ + AIF (Cells/mL)Survival % in AGJ + AIF
Strain0 h2.5 h5 h
S. boulardii4.6 × 1084.6 × 108100.0 a ± 2.11.9 × 1074.1 a ± 0.3
S. pastorianus8.5 × 1086.0 × 10863.6 b ± 3.48.9 × 1061.1 b± 0.2
S. cerevisiae1.6 × 1095.4 × 10837.4 c ± 2.16.4 × 1074.0 a ± 0.01
AGJ—Artificial gastric juice, AIF—Artificial intestinal fluid.
Table 8. Survival of yeast after exposure to the artificial gastric juice, and artificial gastric juice with artificial intestinal fluid, as determined by staining with propidium iodide and flow cytometry. Means with at least one letter the same are not significantly different (p > 0.05). Comparison of statistical significance is presented separately for each column.
Table 8. Survival of yeast after exposure to the artificial gastric juice, and artificial gastric juice with artificial intestinal fluid, as determined by staining with propidium iodide and flow cytometry. Means with at least one letter the same are not significantly different (p > 0.05). Comparison of statistical significance is presented separately for each column.
StrainSurvival %
AGJ (2.5 h)AGJ + AIF (5 h)
S. boulardii99.8 a ± 0.0099.2 a ± 0.26
S. pastorianus97.4 b ± 0.675.7 b ± 3.35
S. cerevisiae99.7 a ± 0.0699.0 a ± 0.15
AGJ—artificial gastric juice; AIF—artificial intestinal fluid.
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İlpars, E.; Titlová, Š.; Hanzalíková, K.; Křížová, I.; Brányik, T. Alcohol-Free Beer Produced Using Maltose-Negative Wine Yeast Saccharomyces cerevisiae with Probiotic Potential. Fermentation 2023, 9, 805. https://doi.org/10.3390/fermentation9090805

AMA Style

İlpars E, Titlová Š, Hanzalíková K, Křížová I, Brányik T. Alcohol-Free Beer Produced Using Maltose-Negative Wine Yeast Saccharomyces cerevisiae with Probiotic Potential. Fermentation. 2023; 9(9):805. https://doi.org/10.3390/fermentation9090805

Chicago/Turabian Style

İlpars, Emre, Štěpánka Titlová, Katarína Hanzalíková, Ivana Křížová, and Tomáš Brányik. 2023. "Alcohol-Free Beer Produced Using Maltose-Negative Wine Yeast Saccharomyces cerevisiae with Probiotic Potential" Fermentation 9, no. 9: 805. https://doi.org/10.3390/fermentation9090805

APA Style

İlpars, E., Titlová, Š., Hanzalíková, K., Křížová, I., & Brányik, T. (2023). Alcohol-Free Beer Produced Using Maltose-Negative Wine Yeast Saccharomyces cerevisiae with Probiotic Potential. Fermentation, 9(9), 805. https://doi.org/10.3390/fermentation9090805

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