**1. Introduction**

At present, the increasing alcohol content in wines is closely related to climate change and consumer choice for full-bodied, rich, and ripe fruit flavor profiles, which often involve increased grape maturity [1–3]. In recent years, the worldwide trend towards more frequent warm periods during the grapevine growing season has increased sugar content in grapes and therefore the alcohol concentration in wines [4]. Thus, the average alcohol level has risen about 2% (*v*/*v*) over the past few decades in warm areas, and it is not uncommon to find wines with an alcohol content higher than 16% (*v*/*v*) [5]. Excessive alcohol concentration in wines can alter the sensory profile of wines, increasing bitterness, astringency, and hotness perception and masking some volatile compounds [6,7]. Additionally, wines with elevated alcohol content can lead to harmful health effects [8] and also increase costs in markets where taxes are linked to the ethanol level in many countries [9].

Among the various methodologies aimed at the reduction of alcohol content in wines, microbiological approaches may be promising to preserve organoleptic characteristics and quality in wines. In addition, they are profitable and easy to implement strategies that do not require the need for specialized equipment [10,11]. *Saccharomyces cerevisiae* is the principal microorganism selected for

winemaking. This species completes fermentation of sugars due to its ability to produce and tolerate high concentrations of alcohol [12,13]. Unlike *S. cerevisiae*, non-*Saccharomyces* yeasts are not generally able to complete the fermentation process; thus, mixed or sequential inoculations with *S. cerevisiae* are required for this purpose [14–17]. Research efforts have therefore focused on developing new *S. cerevisiae* strains that produce less ethanol in wine [18] and on using non-*Saccharomyces* yeasts that metabolize sugar without producing ethanol or that do so with less efficiency [19].

Several investigations have employed non-*Saccharomyces* co-cultures as a tool for reducing the ethanol concentration in wine [19–29]. Here, the early inoculation of non-*Saccharomyces* strain transforms sugar to produce biomass and by-products, decreasing ethanol formation before addition of *S. cerevisiae* [2,30]. This action plan is particularly adequate to winemaking in warm regions, as in the case of the Madrid winegrowing region (Spain) under study in the present work. The climate in the Denomination of Origin (D.O.) "Vinos de Madrid" presents temperatures ranging from −8 ◦C in winter to 41 ◦C in summer, and rainfall ranges between 461 and 658 mm [31]. Winemakers in this region are working hard in order to elaborate new styles of wine that are more competitive in the market [32]. The knowledge and selection of native yeasts is a very important achievement to confer typicity and originality to the wine [33,34], and its use is also considered a reactive adaptation practice to climate change [35].

In this work, 33 native non-*Saccharomyces* strains from 13 different wine yeas<sup>t</sup> species were tested with the aim of identifying yeasts that, in sequential fermentation with *S. cerevisiae*, could be used for reducing alcohol content in Malvar white wines, and additionally evaluating their positive impact on the quality of these wines. Moreover, no previous investigations have been carried out to select non-*Saccharomyces*/*S. cerevisiae* combinations with native yeasts from D.O. "Vinos de Madrid" (Madrid, Spain) directed towards ethanol reduction in wines.

#### **2. Materials and Methods**

#### *2.1. Yeast Strains: Purity and Identity Control*

A total of 33 non-*Saccharomyces* strains from the IMIDRA collection belonging to 10 different genera were used in this study (Table 1). All non-*Saccharomyces* strains were native from D.O. "Vinos de Madrid" vineyards and cellars [31,36]. The well-studied native strain, *S. cerevisiae* CLI 889, was employed as a control [31,34,37]. Cryogenically preserved (−80 ◦C) strains in 30% glycerol were subsequently seeded on YPD liquid medium (1% yeas<sup>t</sup> extract, 1% meat peptone, and 2% glucose (Conda Laboratories, Madrid, Spain), w/v) and incubated for 24−48 h at 28 ◦C. Later, all strains were maintained at 4 ◦C on YPD plates.

To confirm yeas<sup>t</sup> strain identifications, DNA extraction and rDNA 5.8S−ITS region PCR-RFLP analysis [38] were employed as described previously by Cordero-Bueso et al. [39]. Some of these strains were also sequenced [31,40], and the D1/D2 domain of the 26S rDNA gene was amplified using primers NL-1 and NL-4 [41].


**Table 1.** Yeast strains used in this study.


**Table 1.** *Cont.*

1 a, spontaneous fermentation; b, must; c, grape; 2 publications in which strains have been investigated.

## *2.2. Laboratory-Scale Fermentations*

Bunches from healthy grapes of white Malvar (*Vitis vinifera* L. cv.) variety were collected from a vineyard in the Madrid winegrowing region of Spain (40◦31 N, 3◦17 W and 610 m altitude). The must was clarified by pectolytic enzymes (Enozym Altair, Agrovin, Spain) (0.01 g/L) at 4 ◦C and stored frozen until use. The main characteristics of Malvar must were pH 3.3; 23.3 ◦Brix, equivalent to about 230 g/<sup>L</sup> of reducing sugars; probable alcohol content, 13.5% (*v*/*v*); and yeas<sup>t</sup> assimilable nitrogen (YAN), 170 mg/L.

The grape must was inoculated with a final concentration of 10<sup>6</sup> cells/mL from 48 h pre-cultures of each yeas<sup>t</sup> strain (33 non-*Saccharomyces* and 1 *S. cerevisiae* as control strain). The fermentations were carried out in quadruplicate in 50 mL Falcon tubes containing 30 mL of sterile Malvar must. The trials were divided into two sections: Section I (pure culture), where strain growth was performed in aerobic conditions at 20 ◦C with continuous orbital shaking (130 rpm). The fermentation kinetic was controlled daily by weight loss. At 96 h, one duplicate of each trial was used to the study of dry weight, residual sugars (glucose + fructose), and volatile acidity (as g/<sup>L</sup> of acetic acid); and Section II (sequential culture), the other duplicate from Section I, was inoculated with 10<sup>6</sup> cells/mL *S. cerevisiae* CLI 889. In this case, Falcon tubes hermetically sealed and fitted with air locks ensured anaerobic conditions. The fermentation process was conducted at 20 ◦C with shaking at 130 rpm and was monitored daily until constant weight. Then, wine analyses were carried out.

Dry cell weight measurements were performed on samples from sections I and II. The wine samples were centrifuged (10,000 rpm, 5 min) and the pellets were washed with deionized water twice. Finally, dry weight was determined by filtering through a 0.45 μm pore size membrane filter (Millipore). Filters were heat-dried at 105 ◦C until constant weight was obtained.

#### *2.3. Analitycal Determination of Wines*

The concentration of glucose, fructose, glycerol, ethanol, and organic acids (malic, lactic, and acetic acids) was determined using a Waters 600E HPLC system (Waters, Milford, MA) at the end of fermentation. The HPLC was equipped with a Waters 2414 refractive index (RI) and Waters 2996 photodiode array detector (PDA) on a Rezex RHM−Monosaccharide H+ (8%) column (300 × 7.8 mm, Phenomenex, Torrance, CA, USA). The column was maintained at 65 ◦C, and 5 mM H2SO4 was used as mobile phase at a flow rate of 0.6 mL/min. In wine samples at 96 h, only residual sugars (glucose + fructose) and volatile acidity (as g/<sup>L</sup> of acetic acid) were measured with a multi analyzer LISA 200 (TDI, Barcelona, Spain), using enzymatic kits (TDI, Barcelona, Spain).

Quantification of major volatile compounds of wines was achieved using the gas chromatography coupled to flame ionization detector (GC−FID) technique. The GC system employed was an Agilent 6850 with a FID detector equipped with a column DB-Wax (60 m × 0.32 mm × 0.5 μm film thickness) from J&W Scientific (Folsom, CA, USA). The extraction and analysis methodologies of volatile analytes were performed following the procedure described by Ortega et al. [44]. Identification and quantification of the 32 individual major volatiles was performed using commercial pure standards. Calibration curves were drawn for each standard at 6 different concentration levels. Each standard was prepared in a synthetic wine solution (5 g/<sup>L</sup> of tartaric acid, dissolved in 13% of ethanol solution (*v*/*v*), at pH 3.4 adjusted with NaOH). The obtained coefficients of regression (*R<sup>2</sup>*) were > 0.990 [32,45].

#### *2.4. Statistical Treatment of Data*

The data were analyzed with SPSS Statistics 25 software (SPSS Inc., Chicago, IL, USA). Analysis of variance was carried out by ANOVA Tukey's test to examine significant differences between samples. Thus, a principal component analysis (PCA) was used to study the contribution of oenological and aromatic variables to the differences between Malvar wines.
