a high-throughput, short-amplicon sequencing approach to test the regional distribution of fungal and bacterial communities associated to vineyards in Napa and Sonoma valleys, which are located in the same latitude, covering from N 38◦ 6.80 to N 38◦ 50.400 approximately. The next generation sequencing approach allowed a deep examination of microbial communities (Bokulich et al., 2014) and detection of the differences between these close locations (Gilbert et al., 2014). Using a simpler approach to cover more distant locations (Hierro et al., 2006), we were able to establish that grape-surface microbial communities were different among Chilean regions. These differences in the microbial profiles may be related to climatic factors, as northern and southern regions of Chile present important discrepancies in the wheatear conditions.

Additionally, our results allowed us to identify co-variations in the loads of Metschnikowia/Hanseniaspora, Torulaspora/ Saccharomyces/Meyerozyma, and Rhodotorula/Debaryomyces that were observed along latitude and associated with relative humidity, rainfall and temperature, respectively. These observations are consistent with studies by Gayevskiy and Goddard (2012), reporting that the proportions of these nonconventional yeasts varied in each sampling zone. Several authors attribute these changes to the geographical location and climatic conditions of the vineyard (Parish and Carroll, 1985; Longo et al., 1991), and it has also been suggested that rainfall could be among the most important factors affecting the load of non-conventional yeasts (Rousseau and Doneche, 2001). Combina et al. (2005), reported that rain near harvest can induce changes in yeast populations, affecting Metschnikowia and Hanseniaspora. Similarly, Itata valley showed the highest rainfall during the harvest period, which coincided with a high load of Metschnikowia/Hanseniaspora. Recent studies by Brilli et al. (2014) showed the influence of relative humidity on non-conventional yeast populations, indicating that an increase in relative humidity might induce higher loads of non-conventional yeast during grape ripening. Similar studies by Van der Westhuizen et al. (2000a,b), confirmed that yeast loads observed in coastal areas were higher than in the inland area. Therefore, those studies support the idea that higher load of Metschnikowia/Hanseniaspora in Casablanca valley, located near to the coast, may be related to relative humidity, as this parameter is highest due to the pronounced maritime influence. Those reports showed that rainfall and relative humidity favored a prevalence of Hanseniaspora and Metschnikowia yeast on the grape–berries, which could explain the co-variation observed in the Chilean valleys. Contrasting results were obtained for Torulaspora/Saccharomyces/Meyerozyma, which seems to vary inversely with rainfall. However, these results have not been reported previously and demand more research efforts to define the negative influence of the rainfall on the load of those yeasts.

Based on the culture dependent approach, our results showed that Hanseniaspora, Metschnikowia, and Aureobasidium were the main genera present on grape–berries in all of the vineyards studied in Chile. These observations are consistent with the findings reviewed by Bisson and Joseph (2009) and Barata et al. (2012) establishing that those genera, along with Candida, were the main ones present on grape– berries examined in Spain, Canada, and Argentina. Molecular biology techniques provide a simple and rapid method to differentiate yeasts based on their genetic background (Granchi et al., 1998; Torija et al., 2001). The modern taxonomy of yeasts has been improved by molecular biology techniques providing reliable methods to differentiate yeasts based on their genetic background, mainly the phylogenetic analysis of conserved DNA and protein sequences. Repeats of the chromosomal rDNA sequences have been widely used for the identification and barcoding of yeast genera and

species. The D1/D2 rDNA sequences are frequently used in the phylogenetic analysis of yeast, where yeast isolates differing by more than 1% substitutions in the D1/D2 domain represent separate species (Kurtzman and Robnett, 1998). The comparison of D1/D2 domains in our Metschnikowia isolates from different Chilean valleys showed that the high genetic diversity was related to 26 polymorphic sites that generate 16 phylotypes. These results agreed with the findings of Sipiczki et al. (2013), which reported 18 and 25 substitutions in the D1/D2 domain in Metschnikowia species.

Non-conventional yeasts influenced the wine aroma: terpenes, thiols, esters, and higher alcohols are the most typical aromatic compounds that contribute to the enhancement of sweetfruity aromas in wines (Mason and Dufour, 2000; Clemente-Jimenez et al., 2004; Sumby et al., 2010; Viana et al., 2011; Gobbi et al., 2013; Jolly et al., 2014). Most of the evidence of the effect of non-conventional yeasts has been obtained from co-inoculation studies combining non-conventional yeast and Saccharomyces in different wines. Medina et al. (2012) indicated that the inoculation of Hanseniaspora isolates in Chardonnay produced a uniquely fruity character, such as banana, pear apple, citric fruits, grape fruit, and guava. Metschnikowia has been used in base wine for sparkling wine production, improving the aromatic profile by increasing smoky and flowery notes (González-Royo et al., 2015). In another example, it was reported that Debaryomyces increased the concentrations of citronellol, nerol, and geraniol, which resulted in floral and citrus-type aromas in wine (Garcia et al., 2002); however, the Debaryomyces isolate obtained in this study showed a different property, improving dried fruit aromas. These studies have demonstrated that non-conventional yeast can be selected based on their ability to produce aromatic secondary metabolites that contribute to improving the quality of wine, which is presently a very important area of applied interest in oenology.

In our study, we focused on the selection of different nonconventional yeasts as a basis for the selection of interesting strains to be used by the wine industry. In our hands, the most promising yeast strains corresponded to the Hanseniaspora, Metschnikowia, and Debaryomyces genera. Therefore, our isolates

#### REFERENCES

might influence the wine quality through the release of several aromatic compounds, such as esters, higher alcohols, acids, and monoterpenes. Thus, further research to analyze the potential of these strains is underway to select new starter presentations for the wine industry. Furthermore, these nonconventional yeasts reveal the potential of the yeast microbiome to contribute to the complexity and typicality of the wine and conferring the aromatic profiles of specific regions. This possibility is another aspect that is currently being developed in our laboratories.

### AUTHOR CONTRIBUTIONS

Conceived and designed the experiments: CJ, VL, AM, and JR. Performed the experiments: CJ and JR. Generated and analyzed the data: CJ, VL, AM, and JR. Wrote the paper: CJ, VL, AM, and JR.

#### ACKNOWLEDGMENTS

Fondef grant ID14I10010 and Programa de Atracción de Capital Humano Avanzado del Extranjero, MEC 80130024 (CONICYT). The authors also thank Rodrigo Loyola for gathering the weather information; Henri Nicod and Carolina Ilabaca for technical assistance.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00663

FIGURE S1 | Phylogenetic analysis of Chilean of Metschnikowia using D1/D2 domain. Two sequences from GenBank were included as reference (KM249369 and KM658981).

FIGURE S2 | Phylogenetic analysis of Chilean isolates of using D1/D2 domain for Hanseniaspora and Rhodotorula.

vintage, and climate. Proc. Natl. Acad. Sci. U.S.A. 111, 139–148. doi: 10.1073/pnas.1317377110

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Jara, Laurie, Mas and Romero. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Production of Volatile and Sulfur Compounds by 10 Saccharomyces cerevisiae Strains Inoculated in Trebbiano Must

Francesca Patrignani 1, 2, Fabio Chinnici 1 , Diana I. Serrazanetti 2 , Pamela Vernocchi 1, 3 , Maurice Ndagijimana4 , Claudio Riponi 1 and Rosalba Lanciotti 1, 2 \*

*1 Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy, 2 Interdepartmental Centres for Industrial Research, University of Bologna, Cesena, Italy, 3 Human Microbiome Unit, Genetic and Rare Diseases Area, Bambino Gesu Research Hospital IRCCS, Rome, Italy, 4 Department of Agricultural Food and Nutritional Science, Agriculture/Forestry Centre, University of Alberta, Edmonton, AB, Canada*

#### Edited by:

*Giuseppe Spano, University of Foggia, Italy*

#### Reviewed by:

*Giuseppe Spano, University of Foggia, Italy Francesco Grieco, Consiglio Nazionale delle Ricerche - Istituto di Scienze delle Produzioni Alimentari, Italy Angela Capece, University of Basilicata, Italy*

#### \*Correspondence:

*Rosalba Lanciotti<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology*

Received: *21 December 2015* Accepted: *15 February 2016* Published: *04 March 2016*

#### Citation:

*Patrignani F, Chinnici F, Serrazanetti DI, Vernocchi P, Ndagijimana M, Riponi C and Lanciotti R (2016) Production of Volatile and Sulfur Compounds by 10 Saccharomyces cerevisiae Strains Inoculated in Trebbiano Must. Front. Microbiol. 7:243. doi: 10.3389/fmicb.2016.00243* In wines, the presence of sulfur compounds is the resulting of several contributions among which yeast metabolism. The characterization of the starter *Saccharomyces cerevisiae* needs to be performed also taking into account this ability even if evaluated together with the overall metabolic profile. In this perspective, principal aim of this experimental research was the evaluation of the volatile profiles, throughout GC/MS technique coupled with solid phase micro extraction, of wines obtained throughout the fermentation of 10 strains of *S. cerevisiae*. In addition, the production of sulfur compounds was further evaluated by using a gas-chromatograph coupled with a Flame Photometric Detector. Specifically, the 10 strains were inoculated in Trebbiano musts and the fermentations were monitored for 19 days. In the produced wines, volatile and sulfur compounds as well as amino acid concentrations were investigated. Also the physico-chemical characteristics of the wines and their electronic nose profiles were evaluated.

Keywords: Saccharomyces cerevisiae, sulfur compounds, volatile compounds, Trebbiano wine, electronic nose

### INTRODUCTION

The wine flavor and aroma are the result of several interactions between a huge amount of chemical compounds and sensory receptors. The wine flavor can be the sum of varietal (deriving from the grapes), pre-fermentative (deriving from grape crushing and must conditioning), fermentative (generated during fermentations by yeasts and/or bacteria), and post-fermentative flavors (generated by the wood release or the chemical transformation during conservation; Swiegers et al., 2005).

However, volatiles from fermentation largely dominate wine flavor, since yeasts metabolize grape sugars and other components into ethanol, carbon dioxide, and hundreds of secondary end-products, contributing to the wine character (Fleet, 2003). The aroma compounds from yeast metabolisms are constituted by higher alcohols, esters, organic acids and aldehydes (Lambrechts and Pretorius, 2000; Vernocchi et al., 2011, 2015). The amount of these compounds constitutes the overall expression of the fermentative flavor and, if in excess, some of them (i.e., acetic acid, acetaldehyde) may also be regarded as undesirable (Liu and Pilone, 2000; Styger et al., 2011). Also sulfur compounds, which can be considered a "doubleedged sword," can contribute positively or negatively to wine aroma (Vichi and Cortes-Francisco, 2015). Positive examples are furfurylthiol (roast coffee' aroma) (Tominaga et al., 2000) and the "fruity" polyfunctional thiols 3-mercaptohexan-1-ol (3MH), 4-mercapto-4-methyl-pentan-2-one (4MMP), and 3 mercaptohexyl acetate (3MHA), that impart passion fruit, grapefruit, gooseberry, guava, and "box hedge" aromas (Swiegers et al., 2005; Swiegers and Pretorius, 2007). In particular, these thiols affect the distinctive sensory characteristics of wines made from the grape variety Sauvignon Blanc (Harsch and Gardner, 2013). On the contrary, the highly volatile sulfur compounds (HVSC) have a negative impact in wine because, with their low odor threshold (in the order of ppb), they imparts a powerful odor described as souplike, meaty, boiled potato, rotten egg-like off-flavor, and cooked cabbage aroma (Vermeulen and Gus, 2005; Davis and Qian, 2011; Franco-Luesma and Ferreira, 2014). Commonly found HVSCs include methanethiol, dimethyl sulphide (DMS), dimethyl disulphide (DMDS), dimethyl trisulphide (DMTS), 3-methylthio-1-propanal (methional), 3-methylthio-1-propanol (methionol), and S-methylthioesters of short-chain fatty acids (acetate, propanoate, and butanoate). Also the production of H2S represents in winemaking a global problem, resulting in a loss of wine quality and a rejection from the consumers. During alcoholic fermentation, Saccharomyces cerevisiae can be responsible for the production of several sulfur compounds via the sulfate reduction pathway (Swiegers and Pretorius, 2007), but the majority of H2S produced during winemaking occurs as a result of the biosynthesis of the sulfur containing amino acids, methionine, and cysteine, which occur in low concentrations in grape juice, through the sulfate reduction sequence (SRS). However, for sulfides as for all the other classes of volatile compounds, the yeast strain used for fermentation is the main factor influencing their production (Rainieri and Pretorius, 2000; Fleet, 2008). However, their perception in wine is related to the other volatile compounds, and it is also the result of the interaction with non-volatile molecules. Because sulfur compounds are present in wine at very low concentrations, they are usually determined by gas-chromatographic techniques and their detection represents a methodological challenge. Headspace techniques are generally preferred due to the high volatility of these compounds and their relatively low solubility in organic solvents. Consequently, simple static headspace or headspace solid phase microextraction are generally used for their extraction and the sulfur chemiluminiscence (SCD) and the flame photometric detectors (FPD) for their detection (Franco-Luesma and Ferreira, 2014).

Thus, the main goal of this research was characterize 10 strains of S. cerevisiae, endowed for good oenological properties, producers of H2S in strain dependent way, also for the production of HVSC, by using a suitable and reliable technique, since they are fundamental for the sensory wine features but deeply investigated. Because, as previously underlined, the wine volatile profiles are the outcome of the ratio and interaction of several molecules (volatile and not), also the production of volatile compounds and electronic nose profiles were investigated to evaluate the strain volatile fingerprinting and their effects on wine features. In order to verify their potential use for the production of Trebbiano wine, the strains were inoculated in Trebbiano must determining also the fermentation kinetics and the aminoacidic compositions.

#### MATERIALS AND METHODS

#### Strains

Ten S. cerevisiae strains (L234, L288, L674, L951, M630, M692, U5298, 6944, 7541, 6644), able to produce in strain dependent way H2,S belonging to ASTRA srl, Faenza, Italy, were employed in the research (**Table 1**).

Before using, the frozen strains were sub-cultured three times in Sabouraud broth medium (Oxoid, Basingstoke, UK) at 28◦C for 48 h.

### Micro-Vinifications

Grape must of Trebbiano variety (vintage 2011) was used to test the effects of the different strains of S. cerevisiae on wine characteristics. Until the use, the must was kept frozen. The Trebbiano must features are reported in **Table 2**. Before inoculation, the must was flash pasteurized (70◦C for 20 s). The fermentations were carried out in 500-ml flasks filled with 400 ml of Trebbiano must. For each strain considered, three different micro-vinifications were performed. Each strain was inoculated at level of about 6 Log cfu ml−1 . The inoculations were performed using 48-h pre-cultures in the same must. The temperature was kept at 18◦C during alcoholic fermentation. The weight lost was used to follow the fermentation process. After the completion of alcoholic fermentation, the different wine samples were separated by filtration.

### Chemical Analyses

Residual sugars, SO2, ethanol, pH, and total acidity were performed according to the Official EU Methods (OJEU, 2010).

\**Very high producer;* \*\**Low producer;* \*\*\**High producer;* \*\*\*\**no production.*

TABLE 2 | Enological features of Trebbiano wines in relation to the strain used for fermentation.

\**not performed; For each column considered, values with the same superscript letter are not statistically different (P* > *0.05).*

### Determination of Volatile Compound Profiles

The volatile molecule profiles of Trebbiano wines were analyzed by solid-phase microextraction coupled with gas chromatography-mass spectrometry (SPME-GC-MS) according to the method of Vernocchi et al. (2015). A polyacrylate-coated fiber (85µm; Supelco, Bellefonte, PA) and a manual SPME holder (Supelco) were used after preconditioning, according to the manufacturer's guidelines. Before each head-space sampling, the fiber was exposed to the gas chromatograph inlet for 5 min for thermal desorption at 250◦C in a blank sample. Five milliliter of wine samples were placed in 10 ml glass vials, with 1 g NaCl and 10µL 4-methyl-2-pentanol (initial concentration of 10000 mg l−1 )(Sigma, Milan, Italy) as internal standard. The samples were then heated for 10 min at 45◦C. The SPME fiber was exposed to each sample for 40 min. Both the equilibration and absorption phases were carried out under stirring. The fiber was then inserted into the injection port of the gas chromatograph for a 5-min sample desorption. GC–MS analyses were performed on an Agilent 7890A (Agilent Technologies, Palo Alto, CA) coupled to an Agilent 5975C mass selective detector operating in electron ionization mode (ionization voltage 70 eV) and using a Chrompack CP-Wax 52 CB capillary column (50 m, 0.32 mm i.d.; Chrompack, Middelburg, Netherlands). Volatile compounds were separated using helium as carrier gas (1 ml min−1 ). The temperature program was 50◦C for 2 min, then programmed at 1.5◦C min−1 to 65◦C, and finally at 4.5◦C min−1 to 220◦C, which was maintained for 20 min. Injector, interface, and ion source temperatures were 250, 250, and 230◦C, respectively. Identification of the compounds detected in the wine samples was performed comparing mass spectra of compounds with those contained in an available database (NIST version 2005) and those of pure standards.

#### Determination of Sulfur Compounds

The extraction of sulfur compounds from wine was performed by using the method proposed by Moreira et al. (2002). Briefly, 50 ml of wine were extracted twice with 5 ml of dichloromethane after the addition of 4 grams of sodium sulfate and of 500µl of i.s. [ethyl (methylthio)acetate] at 500 µg l−1 to have a final concentration of 50µg l−1 . The two organic phases were mixed and the solution was concentrated to 1/10 under a nitrogen flow. Finally, 2µL of the extract was injected into the chromatograph.

For the analyses, a gas-chromatograph equipped with a Flame-Photometric-Detector (Clarus 500, Perkinelmer) fitted with a 30 m Elite-5 (Supelco, Bellefonte, PA, USA) (i.d. 0.53 mm) column was used. The identification was based on the comparison of the peak retention times with those of pure standards while the quantification was performed by using calibration curves, obtained with reagents Pure standards (>95%) of methanethiol and ethanethiol from Fluka (Steinheim, Germany), dimethylsufide from Merck (Darmstadt, Germany), sodium sulfide, ethylmethylsulfide, 1-propanethiol, thiophene, diethyldisulfide, dimethyldisulfide, diethylsulfide from Sigma-Aldrich (Steinheim, Germany).

### Determination of the Amino Acids Release in Wine

The analysis of amino acids in wine was performed according to the method proposed by Ndagijimana et al. (2010, unpublished data).

One ml of of NaOH 1% was added to 1 ml of standard solution or to 1 ml of freeze dried samples supernatants in a silanized micro reaction vessel and vortexed for 10 s. Twohundred microliter of the mixture were collected in a new micro reaction vessel, added with methanol and pyridine and vortexed for 10 s in presence of 10µL of decanoic acid (10.000 ppm—solution in ethanol 70%). The following ratios of aqueous phase/methanol/pyridine was used 6:2.1.

An increasing volume of ECF (18 ul) was then added to the mixture to evaluate the efficiency of the derivatizing agent and the mixture was vortexed for 20 s. The same procedure was repeated twice. In order to extract the derivatized analytes, 400 ul of chloroform were added and the mixture vortexed for 20 s. The control of the pH of the reaction medium was performed by means of addition of 400 ul of sodium bicarbonate 50 mM. In order to remove traces of water, anhydrous sodium sulfate was added then the organic phase was carefully collected in a glass silanized conical tube and subjected to GC/MS analysis. The derivatized extracts (both form culture and from standards) were analyzed with a Agilent 7890 gas chromatograph coupled with a 5973C mass spectrometer (Agilent Technologies, USA). One microliter of the extracts was injected into a SPB5 capillary column coated with 5% diphenyl cross-linked 95% dimethylpolysiloxane (60 m × 250µm i.d., 0.25-µm film thickness; Supelco, Palo Alto, USA) in the split mode (30:1). Preliminary experiments, described in the results, permitted to choose the subsequent conditions. The injection and interface temperatures were set to 250◦C and the ion source temperature was adjusted to 200◦C. Initial GC oven temperature was 80◦C; 2 min after injection, the GC oven temperature was raised to 140◦C with 10◦C min−1 , to 240◦C at a rate of 4◦C min−1 , to 280◦C with 10◦C min−1 again, and finally held at 280◦C for 3 min. Helium was used as the carrier gas with a flow rate of 1 mL min−1 . The analyses were performed with electron impact ionization (70 eV) in the full scan mode (m/z 30–550).

The identification of analytes was performed by comparison of their retention times and their mass spectra data with those of pure standards analyzed under the same conditions. Moreover, the retention index of the analytes of interest was calculated by means of results related to a mixture of n-alcanes (C10- C24) analyzed under the GC-MS conditions above described. The following equation was used for the calculation of retention index:

$$RI(\mathbf{x}) = 100 \times z + 100 \times \frac{\text{RT(x)} - \text{RT(z)}}{\text{RT} \,(z+1) - \text{RT(z)}}$$

where RI(x) is the retention index of the unknown analyte, z is the number of carbon atoms of the n-alkane eluting before the analyte unknown and (z + 1) is the number of carbon atoms of the n-alkane eluting after the peak of interest, RT(x) is the retention time of analyte unknown, RT(z) is the retention time of the n-alkane eluting before the analyte unknown and RT(z+1) is the retention time of of the n-alkane eluting after the peak of interest. All the GC–MS raw files were converted to netCDF format via Chemstation (Agilent Technologies, USA) and subsequently processed by the XCMS toolbox (http://metlin.scripps.edu/download/). XCMS software allows an automatic and simultaneous retention time alignment, matched filtration, peak detection, and peak matching. The resulting table containing information such as peak index (retention time-m/z pair) and normalized peak area was exported into R (www.r-project.org) for subsequent statistical analysis.

#### Determination of Electronic Nose Profiles

The electronic nose profiles of the different Trebbiano wines were recorded using a Pen2 Electronic Nose (Airsense Analytics GmbH, Schwerin, Germany) composed of an array of 10 temperature-moderated metal-oxide sensors (MOS), a sampling system, a data acquisition system, and a data processing system. Each sensor is sensible to different kind of volatile molecules For the analysis, 5 ml of wine sample was placed in 40 ml glass vials hermetically sealed and warmed at 28◦C for 1 h. After warming, injections were performed at 180◦C. For each sample, three repetitions were performed.

Ten different sensors were used: s1 (WMA-CCTO1), s2 (WMA-US5), s3 (WMA-CCTO2), s4 (WMA-US6), s5 (WMA-CCTO3), s6 (WMA-US1), s7 (WMA-CW1), s8 (WMA-US2), s9 (WMA-CW3), and s10 (WMA-U3). Each sensor is sensible to different kind of volatile molecules i.e., s1 for aromatic, s2 for generic compounds, s3 for aromatic, s4 for hydrogenated, s5 for aromatic-aliphatic, s6 for hydrocarbons, s7 for sulfur, s8 for alcohols, s9 for sulfur chlorides, s10 for hydrocarbons-aliphatic. During the analysis the response of the sensors were monitored at 1 s intervals for an overall time of 95 s at a flow rate of 400 mL/min. The sensor data were expressed as the ratio between signal sensor and minimum signal sensor recorded (data not showed). The signal evaluation was done following the method reported by Sado Kamden et al. (2007), in order to find out which are the most indicative signals for the evaluation of the differences among the samples.

#### Statistical Analysis

Microvinification were performed in triple. The data obtained are the mean of three independent repetitions. The electronic nose analyses, for each independent experiment, were repeated five times.

The oenological were analyzed by 1-way Anova using the statistical package Statistica for Window (Statsoft Inc. Tulsa, OK). The ability of each parameter to discriminate among the samples was investigated according to the post-hoc comparison of the Anova.

For volatile compounds and amino acids the variability coefficient was reported.

The raw data obtained for electronic nose were subjected to principal component analysis (PCA) by using Statistica (Package for Window).

#### RESULTS

#### Fermentation Kinetics and Wine Analytical Profile

In order to evaluate the effects of yeast strain on the physicochemical wine characteristics, Trebbiano musts were inoculated with the 10 strains at level of about 6 Log cfu ml−1 .

The fermentation kinetics were evaluated measuring the weight loss of musts during fermentation at 18◦C, as shown by **Figure 1**. Data obtained indicated that strains L674 (C), L951(D), M692(F), U5298 (G), 7541(I), and 6644 (L) had similar kinetics, characterized by a reduced amount of fermented sugars, in particular for strain D. On the other hand, strains L234 (A), L288 (B), M630 (E), and H (6944) fermented faster and with a deep sugars consumption. This behavior is confirmed by data of **Table 2**, where, for yeast A, B, E, and H, the highest alcohol contents are shown. As expected, the yeast strains have produced, in strain dependent way, succinic acid, which ranged from 0.19 (sample fermented with strain D) to 1.74 g l−1 (sample fermented with strain A). Total acidity, ranged between 5.10

and 12.0 g l−1 . Several differences, in strain dependent way, were reported also for the malic and lactic acid (**Table 2**). A significant decrease of malic acid was observed, comparing to the must, for all the inoculated samples. The lowest decrease in mailc acid concentration were observed in wines produced with the strains H (6944) and A (L234). The decrease of malic acid was not always accompanied by the increase of lactic acid. The pH values ranged between 3.05 and 3.27 according to the strain used.

#### Analysis of Volatile Compounds

The gas-chromatographic analyses permitted the identification of molecules belonging to different chemical classes such as aldehydes, lactones, higher alcohols, esters, short chain fatty acids, and terpenes (**Table 3**).

Regarding aldehydes, the strain F produced the highest amounts of acetaldehyde, while the strains A and H produced nonanal, having a great sensorial impact. For what concern ketons, quantitative and qualitative differences were observed among the samples, in relation to the strain used. For example, the wine produced with the strains C, E, and H were characterized by great amount of butyrolactone. The strain C, E, and G have produced in wines high amount of acetoin, absent in wines produced by strains B, I, and L. Only the strains B, C, and E produced low amount of 2,3-butanedione.

Great differences were detected among wines in produced alcohols. The strains C, G, and I produced in wines levels higher than 100 mg l−1 , associated to production of phenylethyl alcohol higher than 50 mg l−1 . Low amounts of isoamylic alcohols distinguished the sample fermented by strains A, B, D, F, and L. The wine samples H and I did not presented ethylphenol, a molecule of great impact at low concentration.

Regarding esters, high amounts were detected in all the samples, independently on the strain employed. The most presents were ethylacetate and ethylester of medium chain fatty acids such as hexanoic, octanoic, and decanoic acids. Ethylacetate was highly produced by strain D, F, and G. On the contrary, low productions were detected for strains A, B, C, E, H, I, and L. In general, the highest production of esters (excluding ethylacetate) were detected in wines obtained by strain A, H, and I.

Terpenic alcohols, molecules of great sensorial impact, were detected in wines obtained by fermentation of strain A, C, E, and H. These wines showed an accuulation of linalool, α-terpineol, and citronellol.

The tested strains resulted different also in the organic acid release. In particular, acetic, isobutyric, decanoic, 3 methylbutyric, octanoic, and 2,2, dimethyloctanoic acid productions were different in relation to the strain employed. The strongest producers of acetic acid were the strains C, D, E, and H.

#### Sulfur Compounds

The use of a photometric flame detector permitted to detect and quantify in wine samples methantiol (MT), dimethylsulfur (DMS), dimethyldisulfur (DMDS), dimethyltrisulfur (DMTS), 3-methyl-tio-propanol (MO), ethyl 3-methylpropanoate (EMTP), and 4-isopropyltiophenol (IPTF). The detected sulfur compounds, deriving from yeast metabolism, were found in all the samples. All the strains were able to produce high amounts of IPTF (from 45 to 233µg l−1 ; **Figure 2**). However, the strains C, G and L produced more than 200 ppb. The strains A, E, I, and G produced high levels of methionol while EMPT was produced at level of 11.82µg l−1 and 10.61µg l−1 in wines produced by strain A and I, respectively. The highest amounts of MT, DMDS,

#### TABLE 3 | Volatile molecules (expressed as mg l−1) identified by GC-MS/SPME in Trebbiano wines in relation to the strain used.

*\*Under the detection limit; The coefficient of variability, defined as the ratio of the standard deviation to the mean, ranged between 5 and 7%.*

and DMTS were detected in wines deriving from fermentation of the yeasts A and C.

### Amino Acid Release

Data obtained showed a low level of amino acid content in produced wines, while the must was characterized by high level of all the investigated amino acids (**Table 4**). Alanine, cystein, methionine (present at low level also in must), proline, leucine, isoleucine, valine, threonine were completely metabolized independent on the considered strain. On the contrary, in wine produced by strain A, with respect to the must, there was an increase of arginine and tryptophan. Arginine was found at low level in wine produced by strain D, E, G, and L.

### Electronic Nose

Because the sensorial profile of a wine is the resulting of volatile and not volatile molecule interaction, the wines were subjected to the electronic nose analysis. The data from electronic nose were obtained by using 10 different probes able to detect different classes of compounds, as reported in Materials and Methods, and give a wine sensory evaluation. The raw data obtained were analyzed by PCA able to discriminate the samples in three different macro-groups in relation to the affinity with the probes used (**Figure 3**). The first group included wine obtained by strains B, E, G, and H; the second group contained wines from strain D, I, and L, while the wines from strain A, F, and C were grouped together. In particular, the group 2 distinguished for the probes 2 and 7, detecting NO and sulfur compound, respectively. The cluster 3 was formed on the basis of probes 3 and 5, detecting NH3 and aromatic compounds and low-polarity aromatic compounds, respectively.

### DISCUSSION

The results of the present work showed that all the S. cerevisiae strains were able to drive the fermentation although with different kinetics. As expected, the strains have produced wines characterized by different amounts of succinic acid. On the other hand, the production of this acid, normally absent in the must, is related to yeast metabolism during alcoholic fermentation (Rainieri et al., 2003). Also the difference in total acidity, ranging from 5.1 to 12.65 g l−1 , can be associated to the strain ability to produce different amount of several acids (succinic, acetic, lactic, and malic acids) but also to the release of different amount of mannoproteins, during the fermentation. The significant decrease of malic acid detected in wine samples, compared to the initial must, can be attributed in the major part of sample to the ability of S. cerevisiae strains to degrade malic acid more than malo-lactic fermentation, (Styger et al., 2011). In fact it is well know that S. cerevisiae strains are able to degrade or produce malic acid in a strain dependent way. A wide literature have shown that these polymers, produced in strain-dependent way during the yeast growth, fermentation and autolysis, can affect also the tartaric acid concentration and its stability (Caridi, 2006; Palomero et al., 2007).

Until a few decades ago, wine yeasts were selected basically on their ability to quickly transform grape sugars into ethanol, on their resistance to sulfur dioxide and on the low acetic acid production. Actually, their role has been significantly expanded by the advent of modern oenological microbiology and their selection has therefore involved the development of techniques for detecting strains that might improve wines in terms of color, aroma, structure, technological, and also healthy properties. In the present work, in addition to test the yeast

TABLE 4 | Amino acid content (mg l−1) detected in Trebbiano wines in relation to the strain used.

\**Under the detection limit; The coefficient of variability, defined as the ratio of the standard deviation to the mean, ranged between 5 and 7%.*

fermentation power, also the strain ability to produce wine with characterizing flavor was investigated. In particular, the volatile sulfur compounds production, and in general the volatile molecule profiles produced by starter cultures have a main role in the strain selection and in the product characterization. Some researchers have suggested that these profiles can be regarded as footprints or "aromagrams" and can in the future be used for identification and quality control purposes (Styger et al., 2011). These aromagrams are not only composed of various chemical classes of compounds (alcohols, esters, aldehydes, ketones, acids, and sulfur- and nitrogen-containing compounds), but these compounds have a very wide concentration range in the wine varying between the gram to the nanogram per liter (Bonino et al., 2003). Moreover, it is their ratio which plays an important role in the final wine flavor and taste.

The GC-MS volatile molecules profiles obtained in this work resulted strain dependent and the results are in accordance with Vernocchi et al. (2015) who demonstrated that Trebbiano wines fermented with wild S. cerevisiae strains were characterized by proper unique aromatic profiles. Also Mauriello et al. (2009) found that a great variability in volatile molecules produced among the tested wild wine yeasts, emphasizing the potential role of this parameter as trait for starter culture selection. Moreover, Romano et al. (2015) found that volatiles detected by mass spectra techniques represent a strain fingerprinting. Also Tufariello et al. (2014) found that yeast species and, within each species, different strains exhibit wide differences in volatile compound profiles in the production of Negroamaro wines. In this research, for example, the strain F produced the highest amounts of acetaldehyde, while the strains A and H produced nonanal, having a great sensorial impact. The wine produced with the strains C, E, and H were characterized by great amount of butyrolactone. In the obtained wines, also terpenic compounds and esters were found. In general, esters are formed by yeasts during the alcoholic fermentation and they are responsible for the fruity odor, while terpenic and nor-isoprenoid compounds are the most important constituent of the varietal aroma of grapes and confer a flowery odor to the wine (Vararu et al., 2016). In wines obtained by the strains A, C, E, and H linalool, α-terpineol, and citronellol, able to impart citrus and peach flavor notes, were found. In general, these are released in wine also by the yeast ß-glucosidase activities (Pedersen et al., 2003; Fia et al., 2005). By now, numerous works have shown that yeasts involved in vinification processes possess β-glucosidase activity, and this is greater in non-Saccharomyces yeast strains than in S. cerevisiae ones (Fia et al., 2005). Also volatile esters constitute one of the most important classes of aroma compounds and are largely responsible for the fruity aromas associated with wine and other fermented beverages (Vararu et al., 2016). Their formation differs widely between yeast strains and other external factors such as fermentation temperature, nutrient availability, pH, unsaturated fatty acid/sterol levels, and oxygen levels all playing an important part in determining the end levels of esters in a wine (Lilly et al., 2000). Our data suggested that the highest production of esters (excluding ethylacetate) was detected in wines obtained by strains L284 (A), 6944 (H), and 7541 (I). For example this last strain produced high amount of ethyl hexanoate (whose odor descriptor corresponds to fruit, pineapple), ethyl octanoate (apricot). Also higher alcohols play a fundamental role since they have usually a strong pungent smell. Differently, 2-phenylethanol is an aroma carrier and its presence may contribute to the floral nuance of wines, especially for white wines. The aroma characterized by this compound changes with its oxidation from a rose to a hyacinth bouquet (Duarte et al., 2010). The strains I (7541), A (L284), D (L951), H (6944), L (6644) were able to produces in Trebbiano wines the highest amounts, contributing to positively affect the final aroma. Also sulfur-containing compounds play an important role in wine aroma. Sulfur compounds contribute mainly to unpleasant aromas in wines, although some of them have been reported to have a positive contribution to wine (4-mercapto-4-methyl-2-pentanone, 3-mercaptohexyl acetate,

3-mercapto-l-hexanol,4-mercapto-4-methyl-2-pentanol, and 3 mercapto-3-methyl-l-butanol). In this research, methionol was the heavy sulfur compound present in wines in the highest concentrations with IPTF. Similar results were obtained by Moreira et al. (2010) for monovarietal white wines. According to Falqué et al. (2002), methionol concentration was one of the variables responsible for the differentiation of wines from Loureiro, Dona Branca, and Trajadura cultivars from the Galicia region (Spain). Methionol is produced by yeast from methionine, via deamination, followed by decarboxylation (Ehrlich reaction); the aldehyde thus formed, 3-(methylthio)-1-propanal (methional), is then reduced to the alcohol (methionol) or oxidized to the acid (3-(methylthio)propionic acid). The reaction of methionol with acetic acid yields 3-(methylthio)propyl acetate (Rauhut, 1993). The content of methionol increased considerably in wines with reduction defects (Mestres et al., 2002), contributing odors of potato, cauliflower, and cooked vegetables/cabbage. In our research, the highest amounts of methionol were produced by strain A (110µg l−1 ), I (89µg l−1 ), and G (70µg l−1 ). However, the data of the present research showed that the impact of the sulfur compounds detected is not so strong because in relation and in equilibrium with other volatile and not volatile compounds. In fact, the PCA analysis, performed on the data from electronic nose, divided the wine samples only in three homogeneous clusters. On the other hand, this kind of analysis can account the sensory profiles of a wine and reflect the interaction between volatile and not volatile molecules.

### CONCLUSIONS

The present work showed that the omic technique adopted (GC/FPD and GC/MS-SPME) can be used as fingerprinting tools and, since they are successfully combinable with those produced by conventional analysis techniques, they can allow to discriminate among the tested strains, in order to select the best candidate in relation to the desiderated wine sensory features. In fact volatile compounds and HVSC, are fundamental for the characterization and definition of the wine sensory properties. The data obtained in this research outline the importance of strain aromagramma in the yeast strain selection for winemaking. In fact, the data contributed to the non-conventional characterization of the employed S. cerevisiae strains. In fact, although all the strains showed potential to ferment Trebbiano must, different profiles for volatile and sulfur compounds were identified and fundamental for strain discrimination. Although these preliminary data can useful for the selection of strains in Trebbiano winemaking, further studies regarding other technological features, such as the mannoprotein release and the production of molecule of health importance, such as ethylcarbammate, can be performed. Moreover, additional investigations regarding the genes involved in the sulfur production from the selected yeasts need to be investigated.

#### REFERENCES

### AUTHOR CONTRIBUTIONS

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

endowed with β-glucosidase activity for the production of Sangiovese wine. World J. Microbiol. Biotechnol. 27, 1423–1433. doi: 10.1007/s11274-010- 0594-1

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Patrignani, Chinnici, Serrazanetti, Vernocchi, Ndagijimana, Riponi and Lanciotti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Diversity of Saccharomyces cerevisiae Strains Isolated from Two Italian Wine-Producing Regions

Angela Capece1 , Lisa Granchi2 \*, Simona Guerrini2 , Silvia Mangani2 , Rossana Romaniello1 , Massimo Vincenzini2 and Patrizia Romano1

1 School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy, 2 Department of Management of Agricultural, Food and Forestry Systems, University of Florence, Florence, Italy

Numerous studies, based on different molecular techniques analyzing DNA polymorphism, have provided evidence that indigenous Saccharomyces cerevisiae populations display biogeographic patterns. Since the differentiated populations of S. cerevisiae seem to be responsible for the regional identity of wine, the aim of this work was to assess a possible relationship between the diversity and the geographical origin of indigenous S. cerevisiae isolates from two different Italian wine-producing regions (Tuscany and Basilicata). For this purpose, sixty-three isolates from Aglianico del Vulture grape must (main cultivar in the Basilicata region) and from Sangiovese grape must (main cultivar in the Tuscany region) were characterized genotypically, by mitochondrial DNA restriction analysis and MSP-PCR by using (GTG)5 primers, and phenotypically, by determining technological properties and metabolic compounds of oenological interest after alcoholic fermentation. All the S. cerevisiae isolates from each region were inoculated both in must obtained from Aglianico grape and in must obtained from Sangiovese grape to carry out fermentations at laboratory-scale. Numerical analysis of DNA patterns resulting from both molecular methods and principal component analysis of phenotypic data demonstrated a high diversity among the S. cerevisiae strains. Moreover, a correlation between genotypic and phenotypic groups and geographical origin of the strains was found, supporting the concept that there can be a microbial aspect to terroir. Therefore, exploring the diversity of indigenous S. cerevisiae strains can allow developing tailored strategies to select wine yeast strains better adapted to each viticultural area.

Keywords: Saccharomyces cerevisiae, wine, terroir, Aglianico del Vulture, Sangiovese, yeast diversity, genotyping, fermentation products

### INTRODUCTION

Traditionally, Saccharomyces cerevisiae is the predominant yeast species in spontaneous wine fermentations and thus it is the main responsible for the chemical and sensory properties of wines (Pretorius, 2000; Fleet, 2003; Romano et al., 2003; Cocolin et al., 2004; Camarasa et al., 2011).

#### Edited by:

Sandra Torriani, Università degli Studi di Verona, Italy

#### Reviewed by:

Jyoti Prakash Tamang, Sikkim University, India Luca Cocolin, University of Turin, Italy

> \*Correspondence: Lisa Granchi<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology

Received: 29 February 2016 Accepted: 15 June 2016 Published: 30 June 2016

#### Citation:

Capece A, Granchi L, Guerrini S, Mangani S, Romaniello R, Vincenzini M and Romano P (2016) Diversity of Saccharomyces cerevisiae Strains Isolated from Two Italian Wine-Producing Regions. Front. Microbiol. 7:1018. doi: 10.3389/fmicb.2016.01018

In spite of the occurrence of a high number of different S. cerevisiae strains at the beginning of the fermentation, it was pointed out that, usually, only few strains (from one to three) dominate the process in the latter stages. Some S. cerevisiae strains were isolated over several years in the same cellar as predominant microbiota in wine fermentations (Sabate et al., 1998; Gutièrrez et al., 1999; Augruso et al., 2006) so that the existence of a "winery effect" was suggested (Vezinhet et al., 1992). Alternatively, specific S. cerevisiae strains were widespread in different cellars of the same wine-producing region (Versavaud et al., 1995; Blanco et al., 2006) and they were considered representative of an oenological area (Guillamón et al., 1996; Torija et al., 2001). More recently, biogeographical characterization of S. cerevisiae wine yeasts carried out at scales above 100 km, has revealed the presence of regional population with specific genotype but no differentiation within the region (Knight and Goddard, 2015). These findings suggest that specific native strains could be associated with a terroir, a term that classically includes only grape variety, climate and soil as fundamental factors determining the typical nature of wines (Van Leeuwen and Seguin, 2006) and that might be revised including also a "microbial aspect" (Bokulich et al., 2014; Taylor et al., 2014). Since it is well established that chemical and sensory properties of some wines reflect their geographic origin (Villanova and Sieiro, 2006; Callejon et al., 2010) it was interesting to determine whether regionally defined S. cerevisiae genotypes actually exhibit specific metabolic profiles (or phenotypes) able to modulate the wine quality, thus contributing to terroir-associated wine characteristics. Indeed, in a recent study Knight et al. (2015) demonstrated significant correlation between the region of isolation of S. cerevisiae and aroma profile in wines. The evidence that certain regions have "signature" S. cerevisiae populations that can produce significantly different chemical and sensory profiles of wine is of relevance to the wine industry because it may link territory, environment, and final products for wine valorisation (Torija et al., 2001; Romano et al., 2003; Aa et al., 2006; Camarasa et al., 2011; Pretorius et al., 2012; Tofalo et al., 2013). For this reason, the demand of indigenous S. cerevisiae, which could be representative of a specific oenological area, is increasing (Orlic et al., 2010 ´ ). In fact, each strain of S. cerevisiae is able to produce different types and quantities of secondary compounds, which are determinant on the desirable organoleptic characteristics of a wine (Pretorius, 2000; Romano et al., 2003; Barrajón et al., 2011; Scacco et al., 2012). Since to perform a better control of the alcoholic fermentation in the modern winemaking the use of yeast starter cultures is diffused, selecting the proper yeast strain can be critical for the development of the desired wine style. Moreover, by using these selected yeast starter cultures, that are better adapted to the environmental conditions, the must fermentation can occur in the correct way (Callejon et al., 2010). In this perspective, the goal of this study was to investigate a possible relationship between the diversity and the geographical origin of indigenous S. cerevisiae isolated from two different Italian wine-producing regions (Tuscany and Basilicata) considering two regional grape varieties usually used to produce Controlled Designation of Origin (DOC) wines. Such studies are of great interest in order to establish the existence of typical S. cerevisiae strains that would then be useful as inocula in the vinifications carried out in the specific oenological areas (Gutièrrez et al., 1999). The use of autochthonous yeast strains, besides assuring the maintenance of the typical sensory properties of the wines of any given region, can contribute to promote or retain the natural S. cerevisiae biodiversity.

### MATERIALS AND METHODS

#### Yeast Strains

Sixty-three Saccharomyces cerevisiae isolates were used. The yeasts were previously isolated from spontaneously fermented grape musts of two varieties: "Aglianico del Vulture," Basilicata region (coded with R1-R33) and "Sangiovese," Tuscany region (coded with R34-R63). The isolates were maintained on YPD medium [1% (w/v) yeast extract, 2% (w/v) peptone, 2% (w/v) glucose, 2% (w/v) agar].

### Genotypic Characterization of S. cerevisiae Isolates

Differentiation between the 63 indigenous S. cerevisiae isolates was performed by two molecular methods: microsatellite-primed PCR (MSP-PCR) by using the synthetic oligonucleotide (GTG)5 (Orlic et al., 2010 ´ ) and mitochondrial DNA restriction analysis (mtDNA-RFLP) by using the restriction endonucleases RsaI according to Granchi et al. (2003). Genomic DNA was extracted using a synthetic resin (Instagene Bio-Rad Matrix), following the protocol described in Capece et al. (2011). Amplification reactions were performed in a final volume of 50 µL containing 10 µL 5X Buffer (Promega), 4.0 µL of 25 mM MgCl2 (Promega), 1 µL of 10mM dNTP (Promega), 5 µL of 5 µM primer, 0.25 µL (5 U/µL) of Taq DNA polymerase (Promega) and 5 µL of the extracted DNA, by adding sterile water until final volume. The thermal cycler was programmed as follows: initial denaturation at 95◦C for 5 min, 35 cycles at 94◦C for 1 min for denaturing, 1 min at 52◦C, 2 min at 72◦C for extension and a final step at 72◦C for 5 min. PCR products were analyzed by electrophoresis in 1.2% (w/v) agarose gel. The obtained profiles were submitted to cluster analysis using "Complete Linkage" method with Pearson distance by FPQuest software v.4.5 (Bio-Rad).

DNA digestions were performed with the enzyme RsaI and restriction DNA fragments were separated on 0.8% (w/v) agarose gels containing ethidium bromide (1 µg mL−1 ) by electrophoresis in 1X·TBE buffer (90 mM Tris-borate, 2 mM, EDTA pH 8.0) at 4 V cm−1 for 6 h. The obtained patterns were submitted to pairwise comparison with the Dice coefficient (SD) (Sneat and Sokal, 1973) and cluster analysis with unweighted pair group method (UPGMA) by GelCompar 4.0 software (Applied Math, Kortrijk, Belgium).

### Technological Characterization of S. cerevisiae Isolates

The 63 isolates were submitted to screening for some phenotypic properties, such as sulfur dioxide, ethanol and copper resistance and fermentative performance. The SO2 and ethanol resistance

was evaluated on agarized grape must (pH 3.6), added with increasing doses of K2S2O5 (100–300 mg L−1 ) and ethanol (10– 18% vol/vol), respectively. Copper resistance was evaluated on agarized synthetic medium, containing 6.7 g L−1 YNB (Yeast Nitrogen Base without amino acids and sulfate), 20 g L−1 glucose, added with increasing doses of CuSO4 (50, 100, 200, 300, 400, and 500 µmolL−1 ). The strain resistance to the three compounds was evaluated on the basis of positive growth after incubation at 26◦C for 24 h, in comparison to the control (the medium without the compound). The degree of resistance of each strain was reported as minimal dose of compounds allowing the growth. All the tests were carried out in duplicate.

#### Laboratory-Scale Fermentations

The fermentative performance of the 63 S. cerevisiae isolates was tested in inoculated fermentations in two different grape musts, "Aglianico del Vulture" and "Sangiovese" possessing, respectively, the following physico-chemicals characteristics: pH: 3.7 and 3.2; sugars (g L−1 ): 227 and 214; yeast assimilable nitrogen (mgL−1 ): (130 ± 1.4) and (120 ± 2.5). The fermentations were performed according to Capece et al. (2012): 130-mL Erlenmeyer flasks were filled with 100 mL of the two grape musts and added with 50 mg L−1 of SO2. Each strain was inoculated in grape must at a concentration of 106 cells mL−1 , from a pre-culture grown for 48 h in the same must. The fermentation was performed at 26◦C and the fermentative course was monitored by measuring weight loss, determined by carbon dioxide evolution during the process. At the end of the process, indicated by constant weight of the samples, the wine samples were refrigerated at 4◦C to clarify the wine, racked and stored at −20◦C until required for analysis. All the experiments were performed in duplicate. Fermentation vigor was measured as weight loss after 2 days of incubation at 26◦C, whereas the fermentative power was defined as total weight loss, detected at the end of the process.

#### Chemical Analysis

In grape musts, α-amino acid and ammonium concentrations were determined by the NOPA procedure (Dukes and Butzke, 1998) and enzymatic assay according to the manufacturer's instructions (STEROGLASS s.r.l., Perugia), respectively. Glucose, fructose, ethanol, glycerol, 2,3-butanediol and acetic acid concentrations in experimental wines were determined by HPLC, according to Schneider et al. (1987) and Granchi et al. (1998), utilizing a MetaCarb H Plus Column (8 µm particle, 300 × 7.8 mm; Varian Inc.) and a Pro-star 210 chromatograph equipped with a Refractive Index Detector, in series (Varian Inc.). Higher alcohols (1-propanol, isobutanol, n-butanol, 2-methyl-1-butanol, 3-methyl-1-butanol), acetoin, diacetyl, acetaldehyde and ethyl acetate were analyzed by gas chromatography equipped with glass column (6.6% CW 20M BA 80/120 225, 2 m × 6 × 2 mm) as described by Romano et al. (1999).

#### Statistical Analysis

The raw data obtained by HPLC and GC analysis were subjected to Principal Component Analysis (PCA) and t-test by Statistica software (version 7, StatSoft, Tulsa, OK, USA).

### RESULTS

## Genotypic Characterization of S. cerevisiae Isolates

Genetic polymorphism in S. cerevisiae isolates from Aglianico del Vulture and Sangiovese grape musts was evaluated by MSP-PCR analysis with the (GTG)5 primer and mt-DNA-RFLP. MSP-PCR profiles contained a variable number of bands, some of which were common to numerous isolates. The dendrogram resulting from MSP-PCR analysis (**Figure 1**), by considering a similarity coefficient of about 65%, revealed the presence of two clusters (A and B). For the majority of isolates, the distribution was related to yeast origin; in fact, the cluster A grouped isolates from Sangiovese grape must (except R28 and R29 strains), whereas the cluster B grouped all the isolates from Aglianico del Vulture grape must, except the Bs sub-cluster, which contains 9 S. cerevisiae isolates from Sangiovese grape must.

The mitochondrial DNA-RFLP analysis revealed the presence of 24 different patterns, i.e., 24 strains, among the 63 isolates analyzed, confirming the high polymorphism found in S. cerevisiae populations. The resulting dendrogram from UPGMA analysis of the patterns obtained with RsaI, reported in **Figure 2**, indicated that S. cerevisiae isolates at 40% similarity grouped into four clusters, I, II, III, and IV. All the isolates from Aglianico del Vulture grape must, except for R6, were included in the clusters I, II, and III while all the isolates from Sangiovese grape must, except for R58, were comprised in the cluster IV. Therefore, the analysis pointed out a possible grouping of the assayed S. cerevisiae isolates according to their geographic origin.

S. cerevisiae isolates from Sangiovese.

### Technological Characterization of S. cerevisiae Isolates

As regards the evaluation of technological characters, the isolates exhibited a high tolerance to ethanol; almost all isolates tolerated 16% v/v of this compound (only few strains developed until 18% v/v of ethanol), whereas a certain variability was found for sulfur dioxide (**Figure 3A**) and copper (**Figure 3B**) resistance. Although the most of isolates exhibited a low tolerance to sulfur dioxide (100 mg L−1of SO2), all the yeasts developing to the highest tested doses of SO2 were isolated from "Sangiovese" (except one). As regards copper tolerance, the isolates were distributed in different classes of resistance. A high number of Sangiovese isolates tolerated 200 µM CuSO4, whereas the majority of "Aglianico" isolates developed between 200 and 400 µM CuSO4. However, also for copper tolerance, the yeasts growing at the highest copper doses (500 µM CuSO4) were mainly Sangiovese isolates.

### Inoculated Fermentation at Laboratory-Scale

The wild strains were tested in inoculated fermentations at laboratory scale. Two different red musts, "Aglianico" (the isolation grape must of the R1-R33 isolates) and "Sangiovese" (the isolation grape must of the R34-R63 isolates), were used to evaluate strain fermentative performance. The data related to fermentative vigor of Aglianico isolates (**Figure 4A**) indicate that these isolates have shown a different vigor in the two musts; in particular, the isolates exhibited a lower vigor in Sangiovese must (mean value 2.76 g CO2/100 mL) than in Aglianico (mean value 3.74 g CO2/100 mL). Furthermore, these isolates showed higher variability in Aglianico than in Sangiovese must and the highest fermentative vigor was found in Aglianico isolates fermenting the same isolation grape must (8.24 g CO2/100 mL, **Figure 4A**). Also Sangiovese isolates (**Figure 4B**) showed different fermentative vigor in the two grape musts. The results obtained for Sangiovese isolates were similar to data found in Aglianico yeasts, with highest vigor and variability in Aglianico fermentation, although the maximum fermentative vigor of Sangiovese isolates (5.48 g CO2/100 mL, **Figure 4B**) was lower than maximum value showed by Aglianico isolates.

The data related to fermentative power, showed in **Figures 4C,D**, confirmed the results obtained for fermentative vigor, with different fermentative behavior in the two musts. As already found for fermentative vigor, Aglianico isolates (**Figure 4C**) showed higher fermentative power than Sangiovese isolates (**Figure 4D**), and both isolates groups showed the best performance in Aglianico grape must, with the highest value of 17.23 g CO2/100mL for Aglianico isolates (**Figure 4C**) and 14.8 g CO2/100 mL for Sangiovese isolates (**Figure 4D**). Furthermore, the isolates exhibited higher variability for this parameter in Aglianico than in Sangiovese must (values ranging between 11.76–17.23 and 9.96–12.7 g CO2/100 mL, respectively). Finally, the best value was exhibited in Aglianico must by strains isolated from this variety.

The content of 14 yeast metabolic compounds (ethanol, glycerol, acetic acid, acetaldehyde, 1-propanol, 3-methylisobutanol, n-butanol, 2-methyl-1-butanol, 3-methyl-1-butanol, diacetyl, acetoin, meso and racemic 2,3-butanediol, ethyl acetate) was determined in the experimental wines obtained at the end of the alcoholic fermentations of Aglianico and Sangiovese grape musts.

Statistical analysis of metabolites produced (**Table 1**) demonstrated that, independently of the grape must variety fermented (Aglianico or Sangiovese), some compounds showed significant differences which may be related to the different origin of the yeast strains carrying out the fermentative process.

FIGURE 3 | Distribution of S. cerevisiae according to their resistance to sulfur dioxide (A) and copper (B).

In particular, S. cerevisiae isolates from Aglianico produced significantly higher amounts of acetic acid, acetaldehyde, acetoin, 1-butanol and 2,3-butanediols, while S. cerevisiae isolates from Sangiovese yielded higher concentrations of 2-methyl-1-butanol and 3-methyl-1-butanol (**Table 1**). The metabolic profiles obtained confirm the wide phenotypic variability within S. cerevisiae species, but, in any case, wine composition, independently of the grape variety, was markedly characterized by metabolites of the fermenting yeast strain.

TABLE 1 | Statistical analysis (t-test p < 0.05) of metabolites from fermentations of Aglianico del Vulture grape must (Ag fermented must) and Sangiovese grape must (Sg fermented must) carried out by S. cerevisiae isolates from Aglianico del Vulture (Ag) and Sangiovese (Sg), (Values as means ± SD) (different letters indicate significant differences among metabolites produced in the same must).

Principal component analysis (PCA) was applied to the matrix of multivariate data comprising concentrations of the metabolic compounds. Residual sugars resulted lower than 2 gL−1 in all experimental fermented wines, with the exception for five Sangiovese wines obtained with the strains R2, R4, R16, R22, and R23 originating from Aglianico del Vulture and two Aglianico wines produced by the strains R2 and R53 (originating from Aglianico and from Sangiovese must, respectively). Therefore, these seven wine samples were not included in the PCA analysis.

**Figures 5A,B** show PCA scores and loadings biplots, respectively, for all the experimental wines deriving from both grape musts fermentation by the 56 S. cerevisiae strains. Examination of the data by PCA showed that PC1 and PC2 accounted for 54% of variation in the dataset. Along the first component, independently of the fermented must, most of the wine samples grouped into two clusters according to the geographic origin of the fermenting yeast strains. In particular, 95% of wines produced by S. cerevisiae isolates from Sangiovese grouped in a cluster on the right of the plot, whereas 70% of wines obtained by S. cerevisiae isolates from Aglianico del Vulture were grouped into a more scattered cluster on the left of the plot. The first principal component correlated positively with 2-methyl-1-butanol, 3-methyl-1-butanol and glycerol and negatively with 2,3-butanediols.

In addition, in order to evaluate whether S. cerevisiae isolates could group according to their geographic origin, all assayed oenological properties, including technological characters and by-products of alcoholic fermentations of both grape musts, were combined and analyzed by PCA. The biplot of the parameters considered, pointed out that along the first component all the Sangiovese isolates, except one, were positioned in the left quadrants while 88% of Aglianico isolates grouped on the right quadrants (**Figures 6A,B**). Therefore, a good relationship between S. cerevisiae isolates and their geographical origin was confirmed.

#### DISCUSSION

The concept of terroir for wine is classically considered as the result from the interaction between specific Vitis vinifera varieties and the local soils, geography, climate and agricultural practices (Van Leeuwen and Seguin, 2006). Recently, there is limited but increasing evidence showing that the microorganisms that influence vine growth, fermentation and wine style (as S. cerevisiae does) also exhibit regional differentiation (Lopandic et al., 2007; Gayevskiy and Goddard, 2012; Bokulich et al., 2014; Taylor et al., 2014; Knight and Goddard, 2015), supporting the concept that there could be a microbial aspect to terroir. In the present study, 63 S. cerevisiae isolates from two different grape musts (Aglianico del Vulture and Sangiovese) were characterized in order to assess the influence of geographic origin of these yeasts on their genetic and phenotypic patrimony. The results obtained by molecular fingerprinting using MSP-PCR with (GTG)5 and RFLP-mtDNA methods confirmed applicability and sensitivity of these methodologies for identification of different S. cerevisiae strains (Schuller et al., 2007; Orlic et al., 2010 ´ ). Furthermore, these techniques were able to detect genetic differences between "Aglianico" and "Sangiovese" strains, resulting suitable methods to differentiate S. cerevisiae isolates based on their provenience as most of the isolates grouped according to their origin of isolation. The high genetic polymorphism found in the yeasts analyzed using the MSP-PCR and RFLP-mtDNA could be a result of a constant adaptation to the ecological conditions they are exposed to. Studies based on genetic and microbiological analyses suggest that in S. cerevisiae a significant part of the mechanisms affecting this genetic polymorphism occur during the vegetative phase of its growth cycle, where meiosis is a rare event (Puig et al., 2000; Perez-Ortin et al., 2002; Aa et al., 2006). That is to say, if yeasts reproduce clonally and they are constantly adapting to their particular environment, there must be a link between the genetic similarity of the strains

and their geographic origin. It is well known that geographic or ecological isolation is one of the mechanisms involved in the process of speciation (Dobzhansky, 1951) as it creates a barrier for the genetic flux, so that strains coming from the same microenvironment will be more similar to each other than those from other geographic origin (Martínez et al., 2007). Our results, although based on the analysis of a small number of isolates, confirm that the wine production areas represent a reservoir of natural yeasts with peculiar genotypic profile, selected by the natural environment and by the interactions between yeasts and its environment (Guillamón et al., 1996; Martínez et al., 2007).

Further step of yeast characterization was addressed to identify potential relationships between strain origin and fermentation phenotype. Indeed, the yeast strain diversity might significantly affect the fermentation performance (Schuller et al., 2012; Tofalo et al., 2014). The data related to fermentative performance of the two groups of S. cerevisiae isolates, tested in the two isolation grape musts, seem to suggest that this parameter is influenced by both fermentation medium and source of yeast isolation. In fact, the isolates showed different fermentative performance in the two musts, with best results in Aglianico grape must, and Aglianico isolates exhibited higher fermentative performances than Sangiovese isolates (**Figures 4A–D**).

Frontiers in Microbiology | www.frontiersin.org June 2016 | Volume 7 | Article 1018 |

As regards the fermentation substrate, the different yeast behavior could be correlated to the different composition of grape must. It has been underlined that wine fermentation conditions represent a combination of various stresses (osmotic, ethanol, acidic, nutrient limitation) that accentuate the metabolic differences between strains. Our results showed a certain influence of isolation origin (the grapes variety, in our case) on strain performance during the fermentation and might support the hypothesis that the autochthonous yeast strains are better adapted to the ecological and technological features of their own winegrowing area. These relationships between the origin and the phenotypes of some yeast strains could be due to physiological and metabolic adaptations in response to specific environmental conditions (Camarasa et al., 2011). Probably, "in the isolation grape must the strains are able to express their own better characteristics because they are better adapted to metabolize the precursors present in this grape must" (Capece et al., 2012). Indeed, in Sangiovese must five S. cerevisiae isolates from Aglianico were unable to complete the alcoholic fermentation. Furthermore, our data indicate significant correlations between the geographic relatedness of S. cerevisiae isolates and their effect on content of some compounds in the resulting wines in agreement with the results obtained by Knight et al. (2015). The PCA of experimental wines obtained by inoculating the S. cerevisiae isolates in Aglianico and Sangiovese grape musts (**Figure 5**) revealed that the samples were mainly grouped according to the geographic origin of the yeast strains. To our knowledge, few researches reporting the correlation between strain origin and fermentation phenotype are available until now. A study, aimed to analyze the variability of 36 S. cerevisiae strains, isolated from different grape varieties and from two very distant Italian zones (Mauriello et al., 2009), demonstrated that production of volatile aromatic compounds (VOC) allowed to differentiate the yeasts in function of isolation area. Indeed, S. cerevisiae isolated from Southern Italy grapes were able to produce more volatile compounds than those from Northern Italy. In a study performed on regionally genetically differentiated population of S. cerevisiae in New Zealand, Knight et al. (2015) demonstrated that these populations differentially affected wine phenotype. By evaluating the correlation between S. cerevisiae genetic distance and volatile chemical profile of wines, obtained by inoculating these strains, the authors found that these factors are correlated, confirming "the significant relationship existing between the genetic relatedness of natural S. cerevisiae subpopulations and their effect on resulting wine phenotypes" (Knight et al., 2015). However, these authors found that the chemicals responsible for the differences between regions are not consistently from any particular class. On the contrary, our results show that the production level of some compounds is correlated with yeast origin, independently from fermentation

#### REFERENCES

Aa, E., Townsend, J. P., Adams, R. I., Nielsen, K. M., and Taylor, J. W. (2006). Population structure and gene evolution in Saccharomyces cerevisiae. FEMS Yeast Res. 6, 702–715. doi: 10.1111/j.1567-1364.2006. 00059.x

substrate. In particular, in both grape musts tested, S. cerevisiae from Aglianico produced significantly higher amounts of acetic acid, acetoin, acetaldehyde, n-butanol and 2,3-butanediols, while experimental wines produced by inoculating S. cerevisiae isolates from Sangiovese contained higher concentrations of 2-methyl-1 butanol and 3-methyl-1-butanol (**Table 1**). These results might be correlated to genotypic characteristics of yeasts. In fact, it is reported that the types and concentrations of metabolites produced by S. cerevisiae are significantly influenced by yeast genotype (Camarasa et al., 2011; Pretorius et al., 2012; Richter et al., 2013), while not exclusively genetically determined.

#### CONCLUDING REMARKS

These findings support the need to unveil the indigenous S. cerevisiae population of specific areas and explore its natural biodiversity in order to produce valuable wines styles. The natural biodiversity of grape berries, grape juice, and winery environment, well correlated to each specific terroir, show a unique composition and represent great resources to winemaking. In fact, this work demonstrated that indigenous microorganisms are better adapted to the "chemical environment" of the grape must coming from a specific wineproducing area. The use of these strains as specific starter cultures can give distinct regional characteristics to wines. This suggests that safeguarding and exploiting natural biodiversity can allow the development of modern winemaking practices and the diversification of wine production, with tangible economic imperatives.

#### AUTHOR CONTRIBUTIONS

AC contributed to the design of the work, to the molecular characterization of yeasts, to the interpretation of data for the work, to draft the work and revising it; LG contributed to the design of the work, to the interpretation of data for the work, to draft the work and revising it; SG contributed to the molecular characterization of yeasts, to statistical analysis of data and to the interpretation of data for the work; SM contributed to chemical analysis of must and experimental wines, to statistical elaboration of data, RR contributed to the molecular characterization of yeasts, to the management of experimental fermentation, to the statistical elaboration of data; MV contributed to the design of the work, to the draft of the work and revising it, PR contributed to the design of the work, to the draft of the work and revising it, and ensured that that questions related to the accuracy or integrity of any part of the work were appropriately investigated and resolved.

Augruso, S., Granchi, L., and Vincenzini, M. (2006). Biodiversità intraspecifica di Saccharomyces cerevisiae e ambiente vitivinicolo. VQ 7, 38–45.

Agnolucci, M., Scarano, S., Santoro, S., Sassano, C., Toffanin, A., and Nuti, M. (2007). Genetic and phenotypic diversity of autochthonous Saccharomyces spp. strains associated to natural fermentation of 'Malvasia delle Lipari'. Lett. Appl. Microbiol. 45, 657–662. doi: 10.1111/j.1472-765X.2007.02244.x

yeast by molecular methods. Front. Microbiol. 4:166. doi: 10.3389/fmicb.2013. 00166

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Capece, Granchi, Guerrini, Mangani, Romaniello, Vincenzini and Romano. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Flor Yeast: New Perspectives Beyond Wine Aging

Jean-Luc Legras1 , Jaime Moreno-Garcia2 , Severino Zara3 , Giacomo Zara3 , Teresa Garcia-Martinez2 , Juan C. Mauricio2 , Ilaria Mannazzu3 , Anna L. Coi3 , Marc Bou Zeidan4 , Sylvie Dequin1 , Juan Moreno5 and Marilena Budroni3 \*

1 SPO, Institut National de la Recherche Agronomique – SupAgro, Université de Montpellier, Montpellier, France, 2 Department of Microbiology, Agrifood Campus of International Excellence ceiA3, University of Cordoba, Cordoba, Spain, 3 Department of Agricultural Sciences, University of Sassari, Sassari, Italy, 4 Department of Agri-Food Sciences, Holy Spirit University of Kaslik, Jounieh, Lebanon, 5 Department of Agricultural Chemistry, Agrifood Campus of International Excellence ceiA3, University of Cordoba, Cordoba, Spain

#### Edited by:

Giuseppe Spano, University of Foggia, Italy

#### Reviewed by:

Maurizio Ciani, Università Politecnica delle Marche, Italy Francesco Grieco, National Research Council, Italy Isabel Pardo, University of Valencia, Spain

> \*Correspondence: Marilena Budroni<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology

Received: 12 February 2016 Accepted: 29 March 2016 Published: 14 April 2016

#### Citation:

Legras J-L, Moreno-Garcia J, Zara S, Zara G, Garcia-Martinez T, Mauricio JC, Mannazzu I, Coi AL, Bou Zeidan M, Dequin S, Moreno J and Budroni M (2016) Flor Yeast: New Perspectives Beyond Wine Aging. Front. Microbiol. 7:503. doi: 10.3389/fmicb.2016.00503

The most important dogma in white-wine production is the preservation of the wine aroma and the limitation of the oxidative action of oxygen. In contrast, the aging of Sherry and Sherry-like wines is an aerobic process that depends on the oxidative activity of flor strains of Saccharomyces cerevisiae. Under depletion of nitrogen and fermentable carbon sources, these yeast produce aggregates of floating cells and form an air–liquid biofilm on the wine surface, which is also known as velum or flor. This behavior is due to genetic and metabolic peculiarities that differentiate flor yeast from other wine yeast. This review will focus first on the most updated data obtained through the analysis of flor yeast with -omic tools. Comparative genomics, proteomics, and metabolomics of flor and wine yeast strains are shedding new light on several features of these special yeast, and in particular, they have revealed the extent of proteome remodeling imposed by the biofilm life-style. Finally, new insights in terms of promotion and inhibition of biofilm formation through small molecules, amino acids, and di/tripeptides, and novel possibilities for the exploitation of biofilm immobilization within a fungal hyphae framework, will be discussed.

Keywords: flor yeast, wine, biofilm, -omic tools, immobilization, biofilm management, biocapsules

## INTRODUCTION

Saccharomyces cerevisiae flor yeast are responsible for the biological aging of Sherry and Sherrylike wines. The main feature of these yeast is that at the end of alcoholic fermentation, when they are under nitrogen and sugar depletion, they shift from fermentative to oxidative metabolism (i.e., the diauxic shift) and rise to the wine surface to form multicellular aggregates. This aggregation leads to the build-up of a biofilm, or velum or flor (Esteve-Zarzoso et al., 2001; Aranda et al., 2002; Alexander, 2013).

Biofilm formation is strongly dependent on the nutritional status of the wine. It is well known that biofilm starts when the concentration of any fermentable carbon source is imperceptible or null (Martínez et al., 1997a). In addition, the presence of other carbon sources, such as glycerol and ethyl acetate, can induce biofilm formation (Zara et al., 2010). Thus, biofilm formation is not limited to aerobic growth on ethanol, but occurs also on other reduced non-fermentable carbon sources that provide sufficient energy input. Moreover, biofilm formation is affected by the availability of nitrogen. It has been shown that in wine lacking nitrogen sources, the flor yeast do not form a

biofilm, and that the addition of amino acids to the medium does not induce biofilm formation (Mauricio et al., 2001; Berlanga et al., 2006). Zara et al. (2011) reported that biofilm formation is favored by addition of 37.5 mM ammonium sulfate, while when these concentrations exceed 150 mM, biofilm formation is prevented.

During biofilm growth, the lack of fermentable carbon sources and the availability of oxygen induce cells to maintain aerobic metabolism, which results in important changes to the wine sensorial and aromatic properties, and to its chemical composition. These changes include a reduction of the volatile acidity due to the metabolism of acetic acid, and production of acetaldehyde at the expense of ethanol. Moreover, acetaldehyde by-products provide the distinctive flavor of Sherry and Sherrylike wines, such as 1,1-diethoxyethane and sotolon (Dubois et al., 1976; Guichard et al., 1992; Moreno et al., 2005; Zea et al., 2015).

Oxidative metabolism is essential to allow flor strains to remain at the wine surface; indeed, Jiménez and Benítez (1988) demonstrated that flor petite mutants cannot form biofilm and are more sensitive to ethanol. Furthermore, sensitivity to ethanol is inversely correlated with rate of biofilm formation, where the less resistant strains produce the biofilm more rapidly (Martínez et al., 1997b).

The ability of S. cerevisiae to adapt to environmental and nutritional changes depends on the activation of metabolic pathways that induce the expression of specific genes. For biofilm formation, expression of the FLO11 gene has been shown to be the key event. Indeed, the increased expression of FLO11 during the diauxic shift results in higher cell-surface hydrophobicity. This encourages the formation of multicellular aggregates that entrap CO2 bubbles deriving from the fermentation of the residual sugar, thus providing the buoyancy to the aggregates, and therefore promoting biofilm formation (Zara et al., 2005) (**Figure 1**). Activation of FLO11 depends on three specific pathways: the cAMP-protein kinase A (PKA) pathway; the mitogen-activated protein kinase (MAPK) pathway; and the TOR pathway (Braus et al., 2003; Vinod et al., 2008). It has been shown that in biofilm-inducing media, biofilm formation and FLO11 transcription can be significantly reduced by the addition of rapamycin, which is a well-known inhibitor of the TOR pathway, and the deletion of RAS2, which regulates the PKA and MAPK pathways (Zara et al., 2011). Finally, the expansion of minisatellites within the central domain of FLO11 contributes to increased protein glycosylation and hydrophobicity of the Flo11 glycoprotein (Flo11p) of flor yeast (Reynolds and Fink, 2001; Zara et al., 2005; Fidalgo et al., 2006).

As well as the role of FLO11 in the rising of cells and in their hydrophobicity, biofilm formation appears to be dependent on increased cell buoyancy. This is influenced by their lipid content and composition, as flor strains have greater chain lengths and unsaturation levels of their fatty-acid residues than those shown by non-biofilm-forming strains of S. cerevisiae (Farris et al., 1993; Zara et al., 2009). Addition of cerulenin, which is an antibiotic that inhibits de-novo fatty-acid biosynthesis, results in a dramatic reduction in FLO11 transcription levels and biofilm weight of flor yeast grown in biofilm-inducing media (Zara et al., 2012). Inositol availability also affects biofilm formation, possibly due to its key role in the assembly of the glycosylphosphatidylinositol anchor of Flo11p, and in the regulation of lipid biosynthetic genes, such as ACC1 (Zara et al., 2012).

Due to their metabolic and genetic peculiarities, flor strains can overcome stress caused by high ethanol and acetaldehyde contents in Sherry and Sherry-like wines (Budroni et al., 2005). It has been hypothesized that this adaptive ability is related to DNA mutations caused by acetaldehyde, such as double-strand breaks (Ristow et al., 1995). These mutations are considered to be responsible for mitochondrial DNA polymorphism (Castrejon et al., 2002) and for gross chromosomal rearrangements in flor yeast (Infante et al., 2003). The complexity and specificity of the flor yeast genome make these strains an interesting model for studies into speciation of S. cerevisiae and into adaptive evolution based on mutations in the FLO11 gene (Fidalgo et al., 2006).

Considering that comparative genomics, proteomics and metabolomics of flor and wine yeast strains are shedding new light on several features of these special yeast, in this review we will discuss the most recent data obtained through the analysis of flor yeast with -omic tools. Moreover, we will report on new insights in terms of promotion and inhibition of biofilm formation through small molecules, amino acids and di/tripeptides, and on novel possibilities for the exploitation of yeast immobilization within a fungal hyphae framework.

#### GENETIC DIVERSITY INDICATES THAT MOST FLOR YEAST SHARE THE SAME ORIGIN

Biological aging is performed traditionally in several countries in Europe, including Hungary (Tokaj-Hegyalja) to produce Szamorodni, Italy (Sardinia) to produce Vernaccia di Oristano, Spain (Jerez area) to produce Xeres, and France (Jura) to produce Vin Jaune. Flor yeast isolated from the biofilms of these different wines have long been considered as specific varieties of S. cerevisiae given their unique behavior, although until recently we had no knowledge whether the strains in these different countries are related or not.

The first attempt to differentiate flor strains based on their ability to metabolize sugars (i.e., galactose, dextrose, lactose, maltose, melibiose, raffinose, sucrose) classified flor yeast into four varieties: Saccharomyces cerevisiae var. beticus, Saccharomyces cerevisiae var. cheresiensis, Saccharomyces cerevisiae var. montuliensis and Saccharomyces cerevisiae var. rouxii (Martínez et al., 1997b). Strains of these four varieties were also detected among Jura flor strains (Charpentier et al., 2009). More recent molecular studies have revealed that despite the high diversity detected for mitochondrial restriction fragment length polymorphism profiles, Spanish Sherry wine yeast share a specific 24-bp deletion in ITS1, which suggests a single family for Spanish Sherry yeast (Esteve-Zarzoso et al., 2001), while another allele of the ITS1 region has been detected among French flor strains (Charpentier et al., 2009). Given the different geographic origins and the genetic specificities of flor yeast, the question of the origin of flor yeast can be investigated further.

The genetic analysis of flor strains with microsatellite typing revealed that, surprisingly, most flor strains of Spain, Italy, France and Hungary belong to the same genetic group of S. cerevisiae (Legras et al., 2014), with sub-clustering that corresponds to the strains from each of these countries (**Figure 2**). Of note, this sub-clustering might be related to differences in the ability to produce a biofilm. Some strains in the main group of Jura flor strains differ in terms of the length of the FLO11 gene and the presence of a 111-bp deletion in ICR1, the long, non-coding RNA that regulates the expression of FLO11. Jura flor strains with this deletion produce thicker biofilms, whereas Jura strains with a longer FLO11 allele and a wild-type version of ICR1 produce thinner biofilms (Legras et al., 2014). Interestingly, two isolates from Hungary have a heterozygote version of the promoter: one wild-type and one that has the deletion. The presence of a single cluster of flor strains from different countries attests that they share a unique origin and indicates that flor yeast have migrated within Europe, as has been shown for wine yeast all over the world (Legras et al., 2007). In agreement with this

the organoleptic, aromatic and chemical composition of the wine.

hypothesis, some isolates related to flor strains have also been isolated in Lebanon. This recent characterisation of flor strains from different countries into a single group demonstrates the ecological success of these flor strains, which occupy the specific niche of the wine surface. This suggests that there are genomic specificities associated to the adaptation to the wine biological aging environment, such as has been seen for FLO11, and will be very likely for other genes.

### ADAPTATION OF FLOR YEAST AND COPY-NUMBER VARIATIONS

Comparative genome hybridization provided the first insight into the adaptation of wine (Dunn et al., 2005) and flor (Infante et al., 2003; Legras et al., 2014) yeast to their environment. Aneuploidies are frequently involved in adaptation to changing environments, as has been observed in adaptive evolution experiments (Dunham et al., 2002; Gresham et al., 2008).

Sequences contained inside gross chromosomal rearrangements can be amplified, which leads to greater expression of some genes, and the first comparison of two flor strains was believed to indicate flor-strain peculiarities (Infante et al., 2003). However, the comparative genome hybridization profiles of six flor strains from Spain, Hungary, France and Italy, compared to those of wine strains and using S288C as a reference, did not reveal such complex aneuploidy profiles (Legras et al., 2014). This global comparison revealed a drop in the hybridisation signal in the sub-telomeric regions, which suggested missing or divergent genes in these regions. However, when looking for amplified genes, only three genes were detected: FRE2, MCH2, and YKL222C (Legras et al., 2014). MCH2 is annotated as a putative monocarboxylic-acid transporter, although its involvement in monocarboxylic acid transport has not been shown experimentally (Makuc et al., 2001). MCH2 is important for yeast survival during the second phase of alcoholic fermentation (i.e., alcohol accumulation) (Novo et al., 2013), and has been shown to be induced under vanillin stress and to confer vanillin resistance (Park et al., 2015). These results show that copy-number variations solely cannot explain the adaptation of flor yeast to their environment, as has been

proposed previously (Infante et al., 2003). However, MCH2 and YKL222C are promising targets, the roles of which need to be evaluated. Further studies, such as population genomics, have to be performed to unravel the genetics basis of flor-yeast adaptation.

### SPECIFICITIES OF FLOR YEAST: FURTHER INSIGHTS FROM PROTEOMICS AND METABOLOMICS

In recent years, proteomics and metabolomics have been applied to the study of flor yeast metabolism and their responses to environmental conditions. Moreno-García et al. (2014) performed a proteome analysis during biofilm formation that focussed on elucidation of the role of the mitochondria, which are the essential organelle for oxidative metabolism, for elaboration of several stress responses, and for the formation of biofilms (van Loon et al., 1986; Costa et al., 1993, 1997; Piper, 1999; Reinders et al., 2006; Ma and Liu, 2010; Fierro-Risco et al., 2013; Vandenbosch et al., 2013). From this proteome analysis, a number of mitochondrion-localized proteins that might be responsible for flor yeast behavior were highlighted. These included proteins involved in carbohydrate oxidative metabolism, biofilm formation, apoptosis, and responses to stresses typical of biological aging; e.g., ethanol, acetaldehyde, and reactive oxygen species (Fierro-Risco et al., 2013). Also, proteins associated with non-fermentable carbon uptake, glyoxylate and the TCA cycle, cellular respiration, and inositol metabolism are more expressed in yeast growing under biofilms than under fermentative conditions (Moreno-García et al., 2015b). Ino1p, which participates in inositol biosynthesis, was five-fold more expressed under biofilm conditions (Moreno-García et al., 2015b). Accordingly, Zara et al. (2012) reported that under biofilm-forming conditions, flor yeast show greater expression of genes involved in inositol biosynthesis.

The presence of proteins involved in cell-wall biosynthesis and protein glycosylation, which are important for cell-cell adhesion and hence for biofilm formation, has also been reported (Moreno-García et al., 2015b). Through the combination of proteomics and innovative metabolomics techniques that were aimed at quantifying minor volatile compounds under exhaustively controlled biofilm conditions, 33 proteins were shown to be directly involved in the metabolism of glycerol, ethanol and 17 aroma compounds (Moreno-García et al., 2015a). Although proteome analyses for oenological purposes have expanded substantially in recent years, particularly in terms of fermentative yeast (Zuzuarregui et al., 2006; Salvado et al., 2008; Rossignol et al., 2009), the relationships between changes in the yeast proteome and exometabolome and the influence of such changes on the organoleptic properties of wine still remained to be explored. The application of comparative -omic disciplines to flor yeast has provided novel knowledge on several features of these yeast, and has revealed the extent of the proteome remodeling that is imposed by the biofilm life-style. Under fermentative conditions, flor and wine yeast have comparable metabolism, although some differences have been revealed. For instance, unlike other fermentative strains, flor yeast increases the concentrations of some higher alcohols with their respective acetic acid esters and ethyl esters of C6 and C8 acids (Moreno et al., 1991). Furthermore, during the fermentation process and biofilm formation, flor strains yield higher levels of lactones than other non-flor strains (Zea et al., 1995). The intracellular accumulation and consequent excretion of terpenic compounds during fermentation, as well as during biofilm formation, was also shown by Zea et al. (1995).

Yeast growth under biofilm-forming conditions and wine biological aging are accompanied by the production of specific wine aromas. Systematic studies have shown that acetaldehyde is the most important metabolite in terms of the different levels between biologically aged and unaged wines, and have also highlighted the decrease in volatile acidity and glycerol content in aged wines (Mauricio et al., 1997, 2001; Cortés et al., 1998, 1999; Berlanga et al., 2004; Muñoz et al., 2005, 2007 and Moreno-García et al., 2013). Among the 35 aroma compounds quantified by Muñoz et al. (2005, 2007), acetaldehyde, 1,1-diethoxyethane, 2,3-butanediol (levo + meso forms), isoamyl alcohols, ethyl and isoamyl acetates, butanoic acid, 2,3-methylbutanoic acids, and 4-butyrolactone, were defined as the most active odorant compounds. Each of these showed odor activity values (OAVs) >0.8 in the biologically aged wines. Only 1-butanol, 2-butanol, isobutyl acetate, furanmethanol, and neral were present at levels 10-fold below their odor perception thresholds. The remaining compounds showed OAVs between 0.1 and 0.8. Compounds with OAVs >1 are considered as important contributors to the aroma of beverages, although there are exceptions when odorants with high OAVs are suppressed and compounds with lower OAVs are revealed as important contributors (Grosch, 2001). All of the 35 compounds studied here showed significant differences after biological aging, in relation to the initial control non-aerated wine (Cortés et al., 1998, 1999; Zea et al., 2001).

These data were confirmed and enriched by Muñoz et al. (2005, 2007) when they studied the effects of periodic aeration on metabolites such as acetaldehyde and its derivatives, and higher alcohols, their acetic-acid esters, and 3-(methylthio)-1 propanol, all of which increased in content as a consequence of the flor yeast growing under biofilm forming conditions. In contrast, the acids of 4, 5, and 6 carbon atoms showed lower concentrations in aged wines, and levels close to zero were obtained for 2-butanol, pantolactone, Z-whisky lactone, 4-ethylguaiacol, furanmethanol, 3-ethoxy-1-propanol and neral, after the same time of aging under biofilm forming conditions. Concentration changes obtained for other important aroma compounds, such as Z-whisky lactone and 4-ethylguaiacol, can only be explained because of the aging process carried out in contact with oak barrels.

The link between the intracellular proteins and metabolites excreted by yeast that are strongly related to sensorial properties constitutes a new and interesting advance in biological information systems. The knowledge generated can be considered as useful information for innovation in fermentative, winemaking and biotechnological-based industries in the near future.

### FLOR YEAST AS A BIOLOGICAL MODEL FOR THE STUDY OF SMALL MOLECULES THAT INHIBIT OR PROMOTE BIOFILM FORMATION

Microbial biofilms are tenacious structures that can be difficult to eradicate and to treat with the current arsenal of antifungal agents. This is mainly due to a lack of guidelines for biofilm management, and to difficulties in their diagnosis and identification. In contrast, many microbial biofilms are beneficial for a plethora of biotechnological processes, like cleaning up hazardous waste sites, filtering biofuels and wastewaters, and forming bio-barriers to protect soil and groundwater from contamination (Ashraf et al., 2014). Similarly for many food processes, such as maturation of cheese (Licitra et al., 2007) and biological aging of Sherry wines (Zara et al., 2005).

Problems related to biofilm eradication motivate current efforts to find compounds that can alter cell-surface hydrophobicity, typically through interactions with cellwall components, and mainly the cell-wall mannoproteins, thus counteracting biofilm formation. Antimicrobial peptides are lead compounds in this approach. Many antimicrobial peptides have been shown to modulate adhesion and biofilm formation of some yeast and fungi due to hydrophobic and electrostatic interactions. For example, histidine-rich glycoproteins greatly inhibit biofilm formation by Candida albicans by binding and rupturing cell-wall components (Rydengard et al., 2008). In contrast, the antimicrobial peptides histatin-5 and LL-37 are antagonized by the cell-wall mucin Msb2 of C. albicans, which enhances resistance toward such compounds (Szafranski-Schneider et al., 2012).

In addition to antimicrobial peptides, other small molecules are currently being assessed for anti-biofilm activity. Zhao and Liu (2010) have shown that N-acetyl cysteine has antibacterial properties toward Pseudomonas aeruginosa and might mediate detachment of P. aeruginosa biofilms. A recent study reported that when mixed with other amino acids and nisin, L-cysteine prevents biofilm formation by Streptococcus mutans (Tong et al., 2014). Other studies on the effects of amino acids are controversial. Sanchez et al. (2013) reported that D-amino acids inhibit biofilm formation in P. aeruginosa, while Sarkar and Pires (2015) showed that they have no effect on Bacillus subtilis, Staphylococcus aureus, or Staphylococcus epidermidis. Moreover, a report of promising anti-biofilm activity of D-amino acids on B. subtilis strains (Kolodkin-Gal et al., 2010) was recently retracted (Hofer, 2014).

Nitrogen is a fundamental nutrient in living cells, and its metabolism is involved in major developmental decisions in S. cerevisiae (Forsberg and Ljungdahl, 2001). According to Homann et al. (2005), clinical and vineyard isolates of S. cerevisiae can grow on a wide range of nitrogen sources, with respect to laboratory strains. Through phenotype microarray analysis, Bou Zeidan et al. (2014) showed that flor yeast can metabolize a wide range of nitrogen sources, including different dipeptides. The presence of FOT genes that code for oligopeptide transporters and were acquired by horizontal transfer from Torulaspora microellipsoides in wine strains, confers the ability to better use the nitrogen resource of grape must, which results in a competitive advantage (Damon et al., 2011; Marsit and Dequin, 2015; Marsit et al., 2016). As FOT genes have been shown for several flor strains (Marsit and Dequin, 2015), their presence might favor the adaptation of these strains to the nitrogen-limited environment during flor aging.

Remarkably, Bou Zeidan et al. (2014) observed that flor strains cannot metabolize dipeptides containing L-histidine, and showed a novel role of L-histidine in the dramatic reduction of biofilm formation and adhesion to polystyrene. Dose-response analysis in nutrient-rich medium showed that L-histidine reduces growth rates, delays the lag-phase, and finally inhibits the growth of the strains tested. Other studies have reported that L-carnosine, which is an L-histidine-containing dipeptide with potential antineoplastic effects (Letzien et al., 2014), can slow down cell growth rates and can kill yeast cells in fermentative metabolism (Cartwright et al., 2012). Interestingly, according to Letzien et al. (2014), L-histidine mimics the effects of L-carnosine, although it shows a stronger effect. Contrary to what was observed in glucose-rich medium, in ethanol medium, the presence of 10 mM L-histidine was sufficient to completely inhibit biofilm formation and adhesion to polystyrene, although these major inhibitory effects were not accompanied by any reduction in cell viability. Moreover, they did not correlate with the transcription level of FLO11, which was stable in the absence or presence of L-histidine. L-histidine is a cationic amino acid, with a unique imidazole ring as a side chain that shows high affinity for cationic metals, aromatic amino acids, and many other compounds (Shimba et al., 2003; Liao et al., 2013). By promoting non-specific physical interactions with embedded cell-wall components in general, and with the highly O-mannosylated cell-wall mannoprotein Flo11p in particular, these features might induce the loss of cell adhesion and the failure of air–liquid biofilm formation (**Figures 3A,B**).

Bou Zeidan et al. (2013) showed that a small peptide, PAF26, can promote biofilm formation. PAF26 is a short cationic and tryptophan-rich peptide with cell-penetrating and antifungal activities. It interacts with flor wine yeast without substantial cell death, and also promotes biofilm formation, thus indicating that the peptide interactions and cell death are not necessarily linked. The increased formation of biofilm in the presence of PAF26, and the absence of biofilm formation in the PAF26 treated 1flo11 mutant, indicate that PAF26 requires the presence of Flo11p (**Figure 3C**). Flo11p is the main molecular target for PAF26 in ethanol-rich medium, but not in glucose-rich medium, possibly because with glucose-rich medium, the FLO11 gene is induced solely during the stationary phase, when the cell concentration is high, and after PAF26 has completed its actions (Swinnen et al., 2006). Bou Zeidan and co-workers also observed that the enhancement of biofilm by PAF26 is independent of FLO11 gene regulation, but requires expression of a functional FLO11 gene. Therefore, the effects of PAF26 on biofilm is related to the enhancing of cell-to-cell aggregation by PAF26 under specific biofilm-forming conditions. Similar data were obtained in C. albicans, where the peptide LL-37 results in cell aggregation and prevention of cell adhesion (Ibeas et al., 2000).

components in general, and with the highly O-mannosylated cell-wall mannoprotein Flo11p in particular. This would lead to the failure of air–liquid biofilm formation and cell adhesion. (C) Biofilm promotion. PAF26 is a highly hydrophobic and cationic peptide. Due to its properties, electrostatic and hydrophobic interactions can be established between PAF26 and Flo11p. Following this hypothesis, PAF26 would act by facilitating and bridging the Flo11p-mediated interactions between cells, and thus increasing biofilm formation. Red arrows indicate cell to cell repulsion; green arrows indicate cell to cell attraction.

### BIOTECHNOLOGICAL APPLICATIONS OF FLOR YEAST

The potential applications of flor yeast in wine and other industries might be widened by their immobilization in rigid pla -tforms. Yeast immobilization provides a wide range of advantages compared to the use of free yeast; e.g., yield improvements, feasibility of continuous fermentation processing, and yeast reuse (Kourkoutasa et al., 2004).

Novel possibilities for the exploitation of flor yeast in other fermentative processes based on spontaneous immobilization within a fungal hyphae framework (Penicillium chrysogenum) have been recently attempted (Peinado et al., 2006). The higher immobilization efficiency of flor yeast versus nonflor yeast on filamentous fungi has been well demonstrated. Co-immobilization was carried out in a medium containing gluconic acid (as the carbon source for P. chrysogenum, and not for flor yeast) in the absence of physico-chemical

external support or chemical binders. The immobilization bodies thus obtained (i.e., yeast biocapsules) are hollow, smooth, elastic, strong, creamy-colored spheres of variable sizes, depending on the particular shaking rate and time in the co-immobilization medium (García-Martínez et al., 2011) (**Figure 4**). The biocapsule wall consists of yeast cells bound to fungal hyphae that are trapped. When biocapsules are placed in a medium containing fermentable sugars, the yeast cells colonize and invade all of the hyphae, thereby causing the fungus to die and thence to remain as a mere inert support for the yeast, which facilitates the subsequent reuse of the biocapsules.

Yeast-cell immobilization on P. chrysogenum and the suitability of the immobilized biocatalysts for sweet wine production was confirmed by the satisfactory operational stability during repeated batch fermentations of must of dried grapes (García-Martínez et al., 2015). The wines obtained by the fermentation of raisin musts contained greater amounts of volatile compounds. Successive reuse of the immobilized flor yeast revealed a gradual adaptation to the fermentation conditions and an increasingly uniform behavior, in terms of the fermentation kinetics and production of metabolites. Immobilized yeast cells produced higher concentrations of carbonyl compounds, esters and polyols than free yeast cells, and the opposite was true for higher alcohols. The nitrogen compounds (e.g., free amino acids, total aminic nitrogen, ammonium ions, urea) depended on the state of the cells (i.e., free or immobilized), and also on the number of times the yeast had been used.

Flor yeast immobilization might provide some advantages toward obtaining the desired ethanol levels by the easier removal of the yeast cells from the medium, or by reductions in the production costs in the inoculum preparation. Recently, different fungus–yeast combinations have also been attempted by using the Zygomycetes (i.e., Rhizopus sp.) (Nyman et al., 2013) as well as using non-flor forming yeast strains for different biotechnological purposes, such as for sparkling wine and sweet wine production (López de Lerma et al., 2012; García-Martínez et al., 2013; Puig-Pujol et al., 2013). The operational stability of the immobilization system proposed might enable its use at a commercial scale for the production of sweet wine (García-Martínez et al., 2015).

FIGURE 4 | Biocapsules of flor yeast. (A) Biocapsules of variable sizes obtained using an orbital shaker at 250, 200, and 150 rpm (left to right) for 7 days. (B) Biocapsules removed with a sterile strainer. (C) Biocapsule image under an optical microscope at 40× magnification. (D) Scanning electron micrograph showing immobilized yeast cells entrapped in the hyphae of the filamentous fungus.

#### CONCLUSION

fmicb-07-00503 April 12, 2016 Time: 16:3 # 9

Based on a survey of the most recent literature, flor yeast have emerged as a promising biological model for the study of yeast speciation and phylogenesis, of alternative life-styles in the microbial world, of management of microbial biofilms, and of biofilm industrial applications. The use of microsatellite genotyping has revealed that flor yeast are a group of S. cerevisiae strains close to wine strains, and given the contrasting life-styles of these two groups, this makes for an interesting model for the study of yeast adaptation to anthropic niches. Comparative genome hybridization only revealed two genes amplified in the genome of flor strains, which implies that other sources of allelic variations, such as single nucleotide polymorphisms, might explain the specific properties of flor strains and should be explored through population genomics strategies.

The exploitation of other comparative -omic tools has provided novel knowledge on several features of flor yeast, and has revealed that proteome remodeling under biofilmforming conditions might also be related to the production of aroma-properties-related metabolites. Transcriptomic analysis associated to genetic quantitative analysis might deepen this knowledge, and also help to decipher the complex regulatory networks associated with flor aging. The use of flor yeast as a biological model for the study of the management of biofilms is very promising considering that the control of biofilm formation through the use of small molecules is of great interest not only in the biomedical field, but also for practical applications

#### REFERENCES

in industrial settings. For example, by using plastic coatings that release small inhibitory molecules, it might be possible to prevent biofilm formation. On the contrary, the use of small molecules that promote biofilm formation can be beneficial to enhance the biological maturation and aging of different foods and beverages. The use of bio-immobilization systems will certainly widen the spectrum of possible applications of flor yeast, which will open new perspectives for fermentation processes, with substantial technical and economic advantages over traditional fermentation methods based on free yeast cells (García-Martínez et al., 2012). Future insights into the role of the FLO11 gene in flor yeast will also help to improve cell-immobilization technologies (Nedovic et al., 2015).

#### AUTHOR CONTRIBUTIONS

JMG, TG-M, JCM, JM wrote "Specificities of flor yeast: further insights from proteomic and metabolomics" and "Biotechnological applications of flor yeast"; J-LL, SD wrote "Genetic diversity indicates that most flor yeast share the same origin" and "Adaptation of flor yeast and copy-number variations"; SZ, GZ, IM, ALC, MBZ, MB wrote "Introduction", "Flor yeast as a biological model for the study of small molecules that inhibit or promote biofilm formation" and "Conclusion". MB coordinated the work and all authors critically revised the manuscript before submission.

of the flor yeast mitochondria in the velum formation. Int. J. Food Microbiol. 172, 21–29. doi: 10.1016/j.ijfoodmicro.2013.11.030

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Legras, Moreno-Garcia, Zara, Zara, Garcia-Martinez, Mauricio, Mannazzu, Coi, Bou Zeidan, Dequin, Moreno and Budroni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Yeast Interactions in Inoculated Wine Fermentation

Maurizio Ciani1 , Angela Capece2 \*, Francesca Comitini1 , Laura Canonico1 , Gabriella Siesto2 and Patrizia Romano2

1 Dipartimento di Scienze della Vita e dell'Ambiente, Università Politecnica delle Marche, Ancona, Italy, 2 Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali, Università degli Studi della Basilicata, Potenza, Italy

The use of selected starter culture is widely diffused in winemaking. In pure fermentation, the ability of inoculated Saccharomyces cerevisiae to suppress the wild microflora is one of the most important feature determining the starter ability to dominate the process. Since the wine is the result of the interaction of several yeast species and strains, many studies are available on the effect of mixed cultures on the final wine quality. In mixed fermentation the interactions between the different yeasts composing the starter culture can led the stability of the final product and the analytical and aromatic profile. In the present review, we will discuss the recent developments regarding yeast interactions in pure and in mixed fermentation, focusing on the influence of interactions on growth and dominance in the process.

Keywords: Saccharomyces cerevisiae, non-Saccharomyces, yeast–yeast interactions, starter dominance,

#### Edited by:

Giuseppe Spano, University of Foggia, Italy

#### Reviewed by:

Kiiyukia Matthews Ciira, Mount Kenya University, Kenya Roberto Foschino, Università degli Studi di Milano, Italy

> \*Correspondence: Angela Capece<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology

Received: 29 February 2016 Accepted: 04 April 2016 Published: 22 April 2016

#### Citation:

Ciani M, Capece A, Comitini F, Canonico L, Siesto G and Romano P (2016) Yeast Interactions in Inoculated Wine Fermentation. Front. Microbiol. 7:555. doi: 10.3389/fmicb.2016.00555

During the winemaking process, various microorganisms coexist and interact influencing the

inoculated wine fermentation

INTRODUCTION

dominance, the persistence of fermenting yeasts and the analytical profiles of wine. Although the predominance of Saccharomyces cerevisiae on other genera is widely reported (Bisson, 1999; Bauer and Pretorius, 2000), few studies on the competition between species of the same genera (Arroyo-López et al., 2011) and between strains of the same species (Barrajón et al., 2009; Capece et al., 2013; Perrone et al., 2013) are present in literature. On the other hand, as consequence of the reevaluation of the role of non-Saccharomyces yeasts, there is an increasing interest on the use of different species in mixed inoculated fermentation where the yeast interactions play a fundamental role. In this review, we will refer on the recent development regarding the dominance and yeast interactions in inoculated fermentations.

### S. cerevisiae/S. cerevisiae INTERACTIONS

The use of S. cerevisiae as starter culture is the most widespread practice in winemaking. However, the inoculation of musts using selected Saccharomyces strains does not ensure their dominance at the end of fermentation (Capece et al., 2010). In fact, although possessing high competition, commercial strains do not completely inhibit wild strains until several days after the process has started. The starter culture should compete with not only non-Saccharomyces yeasts, but also with indigenous S. cerevisiae strains, which theoretically adapt better to must conditions (Barrajón et al., 2011; Capece et al., 2011). The knowledge of the mechanism(s) responsible for interaction among Saccharomyces strains could be of particular importance in understanding the

observed persistence of these indigenous S. cerevisiae strains and the metabolic influence among S. cerevisiae strains composing mixed starter cultures. It has been hypothesized that S. cerevisiae strains can metabolically interact each other, by modifying fermentation products when grown in mixed culture. A compound, produced by a strain, could be taken up and used by other yeasts present. In this way, yeast interaction and sharing of metabolites could occur. Cheraiti et al. (2005) have demonstrated that redox interactions can occur between yeasts in co-culture, in particular acetaldehyde produced by one yeast was metabolized by the other. This observation provides an explanation as to why modulation of wine flavor in mixed culture cannot be replicated by blending wines together, as the modification arises from complex interactions, largely unknown until now, between strains included in mixed starters (Howell et al., 2006; King et al., 2008; Capece et al., 2013).

The competition degree of each strain is influenced by a number of abiotic factors (pH, temperature, ethanol, osmotic pressure, nitrogen, molecular sulfur dioxide, etc.) and biotic factors (microorganisms, killer factors, grape variety, etc.), which determine the capacity of one strain to out-compete another (**Figure 1**).

#### Abiotic Factors

Some winemaking practices, such as the amount of inoculum, rehydration conditions, or certain physical–chemical characteristics of the must, such as temperature, nutrients (nitrogen, vitamins; Rodriguez-Porrata et al., 2008), led to nonoptimal physiological conditions of the starter for competing with the wild biota, causing its growth inhibition by other strains better adapted to a specific oenological environment. Barrajón et al. (2010) evaluated the influence of oenological practices, strain vitality, stress tolerance, and nitrogen requirements on the starters implantation during industrial fermentations. The implantation of commercial strains was generally better in white musts than in red ones, probably in consequence of maceration practice, that might determine an increase of indigenous yeasts in must competing with the starter at the beginning of the fermentation. Different results were obtained: some commercial yeasts competed with one or several dominant wild strains, in other musts the inoculated yeast was completely displaced by only one wild strain at mid-fermentation, for some fermentations a wide variety of wild yeasts was found, none of them dominating the process. Vigentini et al. (2014) have investigated the evolution of the yeast populations during controlled fermentation of Chardonnay musts in two Italian wineries that used the same commercial strain. In the first winery, where the oenologist carefully managed only one starter culture and did not make any spontaneous fermentation, the commercial strain always mastered the process; conversely, in the second winery, where the oenologist performed also spontaneous fermentation, the starter culture did not even take over the dominance and a continuous succession of indigenous strains overcame without one prevailed on the others. Recently, some authors (Duarte et al., 2013) have hypothesized that some oenological additives, such as tannins and fermentation activators, can affect the starter implantation. García-Ríos et al. (2014) carried out a preliminary approach in order to study the fitness advantages of four commercial wine yeast strains (PDM, ARM, RVA, and TTA) against some important oenological parameters, such as nitrogen concentration of grape must, fermentation temperature profile, and ethanol tolerance, which can exert strong stresses on the inoculated strain and determine its competitive advantage. A mathematical approach was used to model the hypothetical time needed for the control strain (PDM) to out-compete the other three strains in a theoretical mixed population. The theoretical values obtained were subsequently verified by competitive mixed fermentations in both synthetic and natural musts, which showed a good fit between the theoretical and experimental data. Specifically, the increase in nitrogen concentration and temperature values improved the fitness advantage of the PDM strain, whereas the presence of ethanol significantly reduced its competitiveness. However, the RVA strain proved to be the most competitive yeast for the three oenological parameters assayed.

Very little is known as fermentation temperature affects the dynamics of the Saccharomyces strain population. Torija et al. (2003) studied the influence of fermentation temperature (from 15 to 35◦C) on a mixed population of S. cerevisiae strains, by evaluating the competition during alcoholic fermentation, at different temperatures, as a tool for testing the natural endurance of indigenous strains. They demonstrated that the temperature of fermentation could clearly affect the development of the different Saccharomyces strains: some strains were predominant at low temperatures, whereas others predominated at high ones. The usual growth curve was observed at 25 and 30◦C, whereas at 35◦C a high yeast mortality was found, which may have induced stuck fermentations with high residual sugar. In fact, these results agree with previous studies, reporting a decrease of yeast viability as the temperature increases (Casey et al., 1984), probably as a consequence of a greater accumulation of intracellular ethanol at higher temperatures, that determine cell toxicity and alter the structure of the membrane, decreasing its functionality (Lucero et al., 2000). On the contrary, at low temperatures there was no decline phase, but the stationary phase lasted until the end of fermentation. The percentage of the different Saccharomyces strains changed considerably during fermentation, probably in consequence of their sensitivity to ethanol toxicity. However, it is reported that the ethanol tolerance of some yeast species depends on the temperature (Gao and Fleet, 1988), and this could be the case also for some Saccharomyces strains. This may explain why the presence of some strains decreases at higher temperatures, but they are able to finish the fermentation at lower temperatures (Torija et al., 2003).

#### Biotic Factors

Ineffective starter implantation was also observed in some fermentation processes despite the use of correct winemaking practices. This means that other factors, i.e., biotic factors, like competition between microorganisms for space and nutrients, or production of toxic compounds (killer factors, medium-chain fatty acids, etc.), can affect starter dominance.

Among the biotic factors underlying the interactions between the different Saccharomyces strains during alcoholic

fermentation, the killer factor is the most studied. Both neutral and sensitive strains do not produce toxins, but the neutrals are resistant to their action. The use of selected S. cerevisiae strains with the killer factor may be effective in suppressing undesirable wild yeast strains or in avoiding stuck fermentations caused by indigenous killer yeasts. The magnitude of killer effect in wine fermentation depends on: the initial ratio of killer to sensitive strains, the presence of protein adsorbing substances, the environmental conditions and the growth phase of the sensitive cells, the presence of protective neutral yeasts, the susceptibility of sensitive strains to the killer toxins of different yeast strains, the inoculum size and nitrogen availability (Pérez et al., 2001). The killer phenotype seems to be linked to the execution of apoptosis, a form of active cell death, widely used by multicellular organisms, e.g., during development or as a mechanism to remove damaged and/or potentially cancerous cells. Apoptotic machinery has been also reported for S. cerevisiae. The finding of cell death with apoptosis-like features in yeast (Madeo et al., 1997) was unexpected, as a unicellular organism seems to have no advantages in committing suicide. As the exposure to killer toxins produced and secreted by concurring killer strains is another natural cell death situation for yeast, some authors (Reiter et al., 2005) investigated if killer toxins are able to induce the apoptotic process and if apoptosis is responsible for cell death in the presence of moderate or low toxin concentrations, closely reflecting the situation in the natural yeast habitat. The results showed that killer toxin action can trigger two modes of cell death. Under high toxin concentrations induction of apoptosis plays a minor role, whereas under moderate or low toxin doses, resembling the natural environment of toxin-secreting killer yeasts, induction of apoptosis might play an important role in efficient toxinmediated cell killing. In this situation, it might be of general importance for a toxin-secreting yeast to induce apoptosis in competing yeast cells, in particular at toxin concentrations that are per se too low to kill via the toxin's primary mode of action.

Another biotic factor involved in the interaction among different yeasts is due to a cell-to-cell contact mechanism. Perrone et al. (2013) investigated S. cerevisiae intraspecies competition during wine fermentations, in which the cells of the different strains were mixed or kept separated. In cofermentation, only the dominant strain was detected, whereas in bio-reactor, in which the cells from the two different strains were kept separate by a membrane and the strains did not sense each other, dominance did not take place. These authors postulated that growth arrest was due to cell-to-cell contact or microenvironment contact; in these conditions, cells compete for space when in high densities and in cell-to-cell contact.

### NON-Saccharomyces/Saccharomyces INTERACTIONS