Brettanomyces bruxellensis wine isolates show high geographical dispersal and long persistence in cellars.

Brettanomyces bruxellensis is the main wine spoiler yeast all over the world, yet the structure of the populations associated with winemaking remains elusive. In this work, we considered 1411 wine isolates from 21 countries that were genotyped using twelve microsatellite markers. We confirmed that B. bruxellensis isolates from wine environments show high genetic diversity, with 58 and 42% of putative triploid and diploid individuals respectively distributed in 5 main genetic groups. The distribution in the genetic groups varied greatly depending on the country and/or the wine-producing region. However, the two possible triploid wine groups showing sulfite resistance/tolerance were identified in almost all regions/countries. Genetically identical isolates were also identified. The analysis of these clone groups revealed that a given genotype could be isolated repeatedly in the same winery over decades, demonstrating unsuspected persistence ability. Besides cellar residency, a great geographic dispersal was also evidenced, with some genotypes isolated in wines from different continents. Finally, the study of old isolates and/or isolates from old vintages revealed that only the diploid groups were identified prior 1990 vintages. The putative triploid groups were identified in subsequent vintages, and their proportion has increased steadily these last decades, suggesting adaptation to winemaking practices such as sulfite use. A possible evolutionary scenario explaining these results is discussed.

Introduction

Brettanomyces bruxellensis is one of the most infamous wine spoiler yeast, able to contaminate up to 25% of red wines [1, 2]. Indeed, B. bruxellensis is known to produce specific compounds like volatile phenols, associated with unpleasant aromas, usually described as “horse sweat” or “leather” [3]. The contaminated wines have tainted organoleptic perception, decreased fruitiness [4, 5] and consequently are rejected by the consumers [6].

An important bibliography is dedicated to the B. bruxellensis species, with 100 to 200 papers published each year over the last decade (source: Google Scholar). Many papers investigate volatile phenol production [7-10], the biotic and abiotic factors impacting B. bruxellensis growth [11-15] and some peculiarities of the species like the ability to survive in the VNC (Viable Non Culturable) state [7, 16, 17] or the specific oxygen needs during fermentation [18]. Moreover, different detection and quantification methods for Brettanomyces, ranging from direct plating methods through molecular detection and flow cytometry analysis, were examined (see Tubia et al., 2018 for review [19]). The genetic diversity of the species has also been largely investigated, and a plethora of approaches were developed across the years, including RAPD (Random Amplified Polymorphic DNA) [20], AFLP (Amplified Fragment Length Polymorphism)[21], REA-PFGE (pulsed field electrophoresis) [22], Sau-PCR [23], PCR-DGGE [24], mtDNA restriction analysis, ISS-PCR (introns 5′ splice site sequence)[25, 26], etc. In the wine industry, most of these genetic analyses revealed high diversity within the species, at the vineyard, in the winery or at sample levels [8, 23, 27–29]. However, in most cases, only a small subset of isolates (a few dozens) were included, and these markers, although discriminant, were not appropriate for population genetic studies. Recently, a great advance was made with the genome sequencing of different B. bruxellensis strains [30-36], revealing the existence of diploid and allotriploid strains. This genetic oddity prompted the development of microsatellite markers that are codominant and thus can be used to assess the possible ploidy level of an individual (maximum 2 alleles per locus means possible diploid, maximum 3 alleles per locus possible triploid, etc.) [37-39]. Microsatellites are also particularly well-adapted for large-scale population studies [40, 41]. Twelve markers were applied to a unique collection of more than 1500 strains of B. bruxellensis from various countries and different fermentation niches (wine, beer, bioethanol, tequila, kombucha, cider) [41, 42]. The strains were clustered in 6 genetic groups, depending on both their putative ploidy level (diploid versus triploid) and their substrate of isolation [41]. Besides their genetic difference, these populations presented contrasted phenotypes: two different groups of triploid strains, mostly associated with wine substrate, showed tolerance or resistance to sulfur dioxide, the most common preservative used in winemaking [42-44]. A preliminary study on a small subset of 8 strains suggested variability in bioadhesion and colonization properties [45]. Altogether, these results indicate that the genetic diversity of B. bruxellensis is shaped by anthropic activities, including the winemaking process. Though, the precise impact of wine-related activities on B. bruxellensis populations remains to be precisely described. In this work, we focused on the 1411 isolates previously genotyped associated with wine niche (wine, grapes, cellar equipment, etc.). We searched for the geographical and temporal trends underlying wine B. bruxellensis diversity. Finally, a specific attention on ‘clones’ (i.e. isolates displaying identical genotypes) is proposed.

Material & methods

Yeast strains

We used 1411 isolates of B. bruxellensis associated with the wine production from 21 countries (S1 Table). Agar-YPD medium containing 10 g.L−1 yeast extract (Difco Laboratories, Detroit M1), 10 g.L−1 bactopeptone (Difco Laboratories, Detroit M1), 20 g.L−1 D-glucose (Sigma-Aldrich) and 20 g.L−1 agar (Sigma-Aldrich) was used for day-to-day growth. All isolates were kept at -80°C in glycerol:YPD (50:50) medium.

Microsatellite genotyping

Twelve microsatellites were used for B. bruxellensis genotyping as previously described [41]. Briefly, DNA was extracted by lysing fresh colonies in 30 μL of 20 mM NaOH (99°C, 10 minutes). Touchdown PCR were performed in a final volume of 15 μL containing 1 μL of DNA extract, 0.05 μM of forward primer, 0.5 μM of reverse primer and labelled primer, 1x Taq-&GO (MP Biomedicals, Illkirch, France). The sequences of the primers, PCR program and dilution conditions are detailed in Avramova et al. (2018). The size of PCR fragments were determined using an ABI3730 DNA analyser (Applied Biosystems) and GeneMarker Demo software V2.2.0 (SoftGenetics). More than 17 96-well microplates were needed to analyse the whole population. Thus, control strains (AWRI1499 and/or CBS 2499) were used to check for deviation between microplates and normalized the data. All genotyping analyses were performed in the same laboratory (UR Oenology) to minimize technical variation. Most ofthe microsatellite datasets (1488 isolates encompassing non-wine strains) were published by Avramova et al (2017), with strains addition (from Greek wines) by Dimopoulou et al (2019) and unpublished isolates from Catalonia wines [40, 41].

Data analysis

The microsatellite dataset was analyzed using R and various packages. Principal Component Analysis (PCA) was performed using ade4 package [46]. Not available (NA) data (around 6% missing data) were replaced by the closest neighbour data (only for PCA analysis). The connection network and minimum spanning tree was built using the chooseCN function from adegenet package [47, 48]. In order to determine whether the observed clustering was purely due to the presence of 2 or 3 alleles in putative diploids and triploids respectively, the following simulation was performed: for each strain and each locus showing 3 alleles, we randomly removed one of the three alleles and performed the PCA on this randomly 2N-constrained dataset.

Diversity indexes were calculated using the poppr package [49, 50], and 95% confidence intervals were calculated using 100 bootstrap replicates.

For the geographic distribution, maps were drawn using R maps package and pies using graphics package. Kilometric distances between clones were calculated from longitude and latitude coordinates using the sp package [51].

Results

B. bruxellensis wine isolates show high genetic diversity and distribution varying with the country and the vineyard region

1411 wine isolates from 21 countries were included in our analysis, resulting in 340 genotypes. The isolates’ set is represented as a minimum spanning tree (Fig 1). In a previous study that encompassed other substrates (beer, kombucha, etc), we defined 6 subpopulations that clustered depending on substrate origin and the possible ploidy level of the strains: strains having maximum 2 alleles per locus were considered as possible diploids, while those having maximum 3 alleles per locus were considered as putative triploids [41]. The six previously defined clusters were globally well conserved with this subset of wine isolates, although the position of a few isolates, located at the periphery of the clusters, seemed poorly resolved. Our wine isolates were distributed as follow (Table 1): 521 isolates belong to the so-called diploid wine group (Wine 2N, CBS 2499-like, darkcyan), 551 to a possibly triploid wine group (1st Wine 3N, AWRI1499-like, red), 229 to a possible triploid beer group (Beer 3N, AWRI1608-like, orange), 69 to the kombucha diploid group (Kombucha 2N, L14165-like, green), 40 to a second possible triploid wine group (2nd Wine 3N, L0308-like, turquoise) and 1 from a possible triploid tequila/bioethanol group (blue). To determine whether the observed clustering was due to the presence of additional alleles for the putative triploid strains compared to the diploid ones, a similar analysis was performed on a 2N-constrained dataset (maximum 2 alleles/loci, randomly picked). The resulting minimum spanning tree (S1 Fig) was very close to the one obtained with the complete dataset, indicating that the different populations clustered depending on the quality of their alleles besides their quantity.

Fig 1

Minimum spanning tree of wine Brettanomyces bruxellensis isolates based on genetic distances.

1411 strains were genotyped using 12 microsatellite markers. A PCA was performed using the R ade4 package. Only the two first axes (principal component, PC1 and PC2) were represented. The connection network and minimum spanning tree was built using the chooseCN function from R adegenet package. For genetically identical isolates (aka ‘clones’), the size of the points is log10 proportional to the number of isolates.

Table 1

Distribution of 1411 wine isolates of Brettanomyces bruxellensis and main diversity parameters.

Group name–color	Reference strain	Number of wine isolates	Number of genotypes (richness)	Shannon's diversity index	Shannon's Equitability index (Evenness)	Simpson's diversity index	Simpson's Equitability index
Wine 2N –darkcyan	CBS 2499	521	58	0.972 [0.789–1.455]	0.239 [0.221–0.372]	1.364 [1.301–1.804]	0.024 [0.024–0.039]
Wine/Kombucha 2N –lightgreen	L14165 (UCD 2399)	69	50	3.732 [3.13–3.732]	0.954 [0.911–0.967]	31.53 [16.184–31.53]	0.631 [0.495–0.796]
Wine/Beer 3N –orange	AWRI1608	229	88	2.92 [2.557–3.65]	0.652 [0.618–0.831]	4.373 [3.624–14.466]	0.05 [0.05–0.189]
1st Wine 3N –red	AWRI1499	551	118	1.83 [1.6–2.22]	0.384 [0.368–0.493]	1.884 [1.776–2.581]	0.016 [0.016–0.029]
Tequila/Bioethanol 3N –darkblue	CBS 5512	1	1	NR	NR	NR	NR
2nd Wine 3N –turquoise	L0308	40	26	2.856 [2.098–2.856]	0.877 [0.793–0.943]	9.756 [5.08–13.92]	0.375 [0.323–0.708]

For each diversity parameter, the 95% confidence interval is indicated in brackets. NR means Not Relevant.

Within these groups, contrasting genetic diversity was highlighted, with Shannon’s diversity index ranging from low (0.97) to high (3.73, see Table 1). The lowest diversity was estimated for the Wine 2N group, suggesting high clonal expansion within this group, whereas higher diversity was obtained for the Wine/Kombucha 2N group and 2nd Wine 3N and Wine/beer 3N groups. Wine/Kombucha 2N and 2nd Wine 3N groups showed an equitability index closed to 1, suggesting a more even distribution of the genotypes among the genetic groups compared to Wine 2N group. Simpson’s diversity and Equitability indexes showed the same trend. Overall, the percentage of the putative triploid wine isolates was 58%, indicating that the triploid state, far from being rare, has a large extend.

The genetic distribution of the wine isolates was then assessed per country, or per wine-producing region when sufficient isolates were available (Fig 2). In France, 5 regions were examined (Fig 2A): Bordeaux, Languedoc, Burgundy, Jura and Cotes-du-Rhone. In Bordeaux, 732 isolates were genotyped and were mainly distributed into two genetic groups: the Wine 2N group (darkcyan, sensitive to SO2, encompassing 345/732 of Bordeaux isolates), and the 1st Wine 3N (red, tolerant to SO2, 373/732). By contrast, in Burgundy, only a small percentage of the 157 isolates belonged to the Wine 2N group (16/157), while the most represented groups were the Beer 3N (orange, 95/157) and the 1st Wine 3N (red, 42/157). Cotes-du-Rhone also displayed a high proportion of isolates belonging to the Beer 3N group (orange, 26/36), beside to the Wine 2N (darkcyan, 6/36) and the 1st Wine 3N (red, 4/36). In Jura, two genetic groups dominated: the 1st Wine 3N (red, 8/16) and the Beer 3N (orange, 8/16). Finally, isolates from Languedoc mostly fell within the Wine 2N group (darkcyan 63/108), the remaining isolates belonging to the 1st Wine 3N group (red, 19/108), the 2nd Wine 3N group (turquoise, 15/108) and the Kombucha 2N group (green, 9/108). In Italy, the three regions tested (Calabria, Campania, Puglia) showed various genetic distributions, Puglia being mostly associated with the Wine 2N group, and Calabria/Campania with the 1st Wine 3N group (red). Denmark was associated with Wine 2N (darkcyan) and Beer 3N groups (orange), while Portugal showed an almost perfect equitable distribution into the five genetic groups. Isolates from Spain (mostly from Catalonia) showed the dominance of the orange group while Greece was mostly associated with the Kombucha 2N group (green) and then with the 1st Wine 3N group (red, Fig 2A). In non-European countries (Fig 2B), the genetic distribution of B. bruxellensis was also contrasted, with the diploid wine group (darkcyan) dominant in USA, Brazil and South Africa, and the 1st Wine 3N group (red) dominant in Australia.

Fig 2

Genetic distribution of Brettanomyces bruxellensis wine isolates in different regions or countries.

Maps were drawn using maps packages and pies using graphics package.

When summing-up all these regional specific distributions, some trends emerged: the Wine 2N (darkcyan) and the 1st Wine 3N (red) groups were isolated in almost every region/country. The Beer 3N group (orange) was more dominant around a meridian crossing Denmark, the east of France and Italy (except for Spain), while the Kombucha 2N group (green) was mostly found around Mediterranean countries. Furthermore, isolates tolerant/resistant to sulfites (belonging to the 1st or 2nd Wine 3N groups), were found in almost all regions/countries.

The temporal distribution of B. bruxellensis wine isolates reveals important evolution over the last century

Most of the studied strains were isolated in the last decade from wines sampled within two years after grapes harvesting (vintage). However, 157 isolates were isolated prior to 2000 and/or were isolated from bottles containing old vintages, mostly from Bordeaux region. For example, three strains were isolated from 1909-wine, five isolates from 1911-wine, etc. Most of the wines with vintages older than 2000 were analyzed several years after bottling (S1 Table).

The genetic distribution of B. bruxellensis strains in wines older than one century, with 20-years intervals, is shown on Fig 3. Without exceptions, isolates from wines produced before-1990 (104 isolates) all belonged to diploid groups, mostly from the Wine 2N group (darkcyan). The Wine 2N group, represented 67% of the isolates from wines produced in 1981–2000, and only 32% of the isolates from wines produced in 2001–2020. For the 1st Wine 3N group (red), tolerant/resistant to sulfite, the older wine displaying such isolate dates back to 1990, and was isolated 15 years after wine elaboration. The proportion of “red” isolates increased from 23% for 1981–2000 period and to 43% for the wines produced during 2001–2020. Similarly, the Beer 3N group that was first isolated from a wine of 1995 vintage represented only 4% of the isolates from wines produced between 1981 and 2000, and 18% of the isolates from wines produced between 2001–2020. For the other genetic groups, the older isolates were found in wine as old as 1956 for Kombucha 2N (and represented around 4–5% of the population), 1994 for 2nd Wine 3N (1% and 3% found in wines produced in 1981–2000 and after 2001 respectively), and 2002 for Tequila/Bioethanol (less than 1%). Unless the late sampling of the wine (>15 years) biases the analyses, the temporal distribution of B. bruxellensis wine isolates shows a clear shift from domination by the 2N darkcyan genetic group in old vintages to 3N red genetic group prevalence among isolates from wines produced over the last decades.

Fig 3

Distribution of B. bruxellensis wine isolates from different genetic groups over vintages.

20 years-intervals were used. In order to calculate confidence intervals, 100 bootstraps were performed (re-sampling of the population). Error bars correspond to 95% confidence interval.

The same B. bruxellensis genotypes can be identified in wines produced in a given cellar over decades

We then focused on B. bruxellensis clones. In this paper ‘clones’ will be defined as genetically identical isolates for all 12 microsatellite markers tested. Over the 1411 isolates, 138 groups of clones were identified, encompassing 2 to 114 isolates. We searched whether some clones were identified repeatedly in the same winery over different vintages. Forty-two groups of clones contained isolates isolated several times in 11 wineries from France and Italy (Fig 4). For example, in winery A1, 9 clone groups were identified: 7 from the Wine 2N and 2 from the 1st Wine 3N (red). Clones from the group n°4 (Wine 2N) were isolated independently in wines of vintages 1909, 1948 and 1970, while clones from the group n°8 were isolated in wines produced in 1990, 2012, 2013 and 2014. Similarly, for winery B1, 15 clone groups were evidenced: clones from the group n°12 (Wine 2N) were isolated repeatedly in wines of vintages 1961, 1985, 1996 and 2014 wines while clones from the group n°22 (1st Wine 3N) were isolated in wines produced in 2003, 2010, 2012, 2013 and 2014. Thus, in several wineries, genetically identical strains were isolated from wines of different vintages, sometimes from different decades. The longer interval (86 years) was found for winery B1, with clones from the group n°3 isolated in wines produced in 1926 and 2012.

Fig 4

Identification of clone groups within the same winery over different vintages.

Genetically identical isolates were designed as clone group. 42 groups gathering clones isolated from the same winery over different vintages were identified, corresponding to 11 wineries from France and Italy.

Fig 4 also illustrates that, within a given sample, different B. bruxellensis can be isolated. In fact, if we considered the strains isolated from the same samples, our collection contained 57 wine samples for which at least 5 isolates were analysed (mostly from France or Italy). In 45 out of 57 samples, we found isolates from two different genetic groups, highlighting the high diversity of B. bruxellensis at sample level.

Wines from different countries and/or continents can be spoiled by the same B. bruxellensis clone

Since some clones were able to persist over several years in the cellar, we searched whether wine-producing regions were associated with specific clones. No ‘signature’ was identified, meaning that no specific genotypes were associated with the studied regions. Instead, we found that some clone groups were highly disseminated. For example, the clone group n°16 (Wine 2N, darkcyan) encompassed 96 isolates from Denmark, France, Portugal and USA (Fig 5A). Another example is clone group n°67 (6 isolates), isolated in wines from Italy, Portugal and South Africa. In the other genetic groups also, several examples of dissemination were found (Fig 5B): the clone group n°24 (1st Wine 3N, red) encompassed 29 isolates from France, Italy and USA, while clone group n°35 were found in France, Italy and South Africa.

Fig 5

Examples of spatial dispersion of wine clones of B. bruxellensis.

Over the 138 clone groups identified, 24 encompassed isolates from different countries. For clarity, only 7 of these groups (number 2, 16, 24, 35, 47, 67, 72) are represented here.

In order to quantify the level of clonal dissemination, we computed the kilometric distance separating the different isolates belonging to a given clone group (Fig 6). 88% of clone pairs were localized in the same region, with kilometric distance inferior to 100km (‘local clone pairs’), of which 34% had distance inferior to 1km. 4% were separated by ~100-750km, usually associated with inter-country distances, less than 1% were distant of ~750-1000km (intra-continental distances), and 6% were separated by more than 1000km (inter-continental distances). It has to be noted that all isolates were considered here, including clonal isolates from the same wine samples that may drift the distribution toward zero kilometric distance. Thus, B. bruxellensis clones appear to mainly disseminate in short distances, as expected. However, a significant proportion of clones showed high geographic dispersal and these distances (hundred kilometres away) are incompatible with natural dispersion.

Fig 6

Kilometric distances between wine clones of B. bruxellensis.

For each clone pairs, the separating distance was calculated. Genetically identical isolates separated by less than 100km were considered as “local clone pairs”.

Discussion

In this work, we studied the genetic diversity and structure of a large collection (>1400) of wine isolates of B. bruxellensis, from 21 countries across 5 continents. Most of these wine isolates belong to five of the six genetic groups previously described at the species level [41], and confirmed the high genetic diversity of this yeast species [23, 27]. Interestingly, we showed that the distribution of B. bruxellensis wine isolates varied greatly from one country/region to another. At a large scale, our results confirm that the two possible triploid groups showing sulfite resistance/tolerance are widespread worldwide and are identified in 14 regions/countries out of 16, with the notable exceptions of Denmark and Brazil. However, in both cases, the sampling may be non-representative (only 11 isolates from Brazil, and 31 isolates from a unique winery in Denmark). Indeed, for some regions, hundreds of isolates were studied (e.g. Bordeaux region, >700 isolates), while smaller subsets were considered for others (16 isolates for Portugal or Australia, for example). Thus, it will be necessary to validate or invalidate these results with a larger number of isolates for all regions, but also for different vintages to analyze more precisely the distribution over time for each region. At the winery level also, the number of isolates per sample (usually from 10 to 30) was low, and we can’t rule out small sample size bias. Subsequent sampling of a large number of wineries, vintages and larger sample size will help refine these first results.

Still, our data reveal the unequal distribution of the different genetic groups at both the geographical and time level, suggesting that some environmental factors (climate, temperature, grape varieties etc.) leading to specific wine composition (pH, ethanol and polyphenols contents, etc.), and/or oenological practices (sulfur dioxide management, barrel ageing) could be shaping the diversity of these wine isolates. It will be interesting in a near future to identify those environmental/anthropic factors, and to examine the associated phenotypic characteristics.

B. bruxellensis wine isolates show high spatiotemporal dispersion

In this paper, genetically identical isolates for all 12 microsatellites were considered as “clones”. It is possible that the use of additional microsatellite markers would result in the identification of more intra-strains differences. Indeed, only full genome sequencing will assess formally whether these different isolates are actual clones. Nevertheless, the isolates hereby designed as clones, are, if not 100% identical, at least very close genetically. The analysis of these “clones” revealed unexpected patterns: first, it was observed a cellar persistence of clones over decades despite modern hygienic practices, improved cleaning/disinfection protocols and a large choice of products and treatments [52-54]. This long-term persistence of B. bruxellensis wine isolates in a given cellar is remarkable. In Saccharomyces cerevisiae, the persistence of cellar-resident populations was shown, but on smaller period of time (over 20 years maximum) [55]. This exceptional temporal durability remains to be explored, but could be related to the specific survival ability of the species, even in a VNC form and to its bioadhesion/biofilm forming capacity in the winery environment [45, 56]. Secondly, besides its cellar residency, some B. bruxellensis clones showed high geographical dispersal and were independently isolated from wines originated from different producing regions, countries and sometimes even from different continents. At a regional scale, the clonal dispersal could be promoted through yeast vectors like insects and birds for a distance inferior to 100km [57-59]. However, for a significant number of clone groups, the calculated kilometric distance is incompatible with the natural dispersion, indicating the involvement of human activities. Indeed, the exchange of contaminated equipment (barrels, bottling equipment, pumps, etc.), the international wine trade and human transport of goods (fruits, etc.) could probably explain such situation [60]. The possibility to isolate clones in wines from old vintages is another example of the specific ability of the species to survive in wines after bottle aging and possibly explain world dissemination of clones through wine exports. In addition, exchanges may also happen between different industrial processes, allowing also niches dispersal of the species. However, it was previously shown that the dispersal was higher for wine isolates than other processes, suggesting different dispersal patterns for the different fermentation processes. Altogether, these results are consistent with the exchange of contaminated wine-related material, followed by adaptation to local winemaking practices, as suggested before [41]. These results draw an atypical picture of B. bruxellensis opportunistic lifestyle, mostly sedentary with nomad propensities.

Allotriploidisation: a recent adaptation to winemaking practices?

One of the most interesting results of this work is the fact that isolates from old vintages mostly belong to a unique group, the so-called “wine diploid” (darkcyan), while, intriguingly, this group represents only ≈31% of nowadays isolates. The oldest isolates for the triploid genetic groups date back the 1981–2000 interval, which is particularly surprising for the 1st Wine 3N (red) group that encompasses ≈45% of recent isolates and in a less extend for the Wine/Beer 3N (orange) group showing ≈16% of recent isolates. It has to be noted that most of the ‘old’ isolates were actually isolated recently from old vintages (eg strain L0626 that was isolated in 2006 from a 1909 vintage). Thus, two main hypotheses can explain this result: either isolates from the Wine 2N group have higher survival or revival rates or the putative triploid groups emerged more recently, during the 1981–2000 period. It is not possible from our data to favor one or the other scenario, and the unequal sampling of the different periods (eg only 11 isolates for 1901–1920 versus 1152 isolates for 2001–2020) may bias our analysis. Subsequent strain isolations will help determine whether the different genetic groups display contrasted ability to survive in wines over decades, thus formally testing the first hypothesis. On the opposite, some elements could be consistent with the second hypothesis: first, wines produced these last decades are characterized by higher ethanol content as a consequence of climate change [61, 62]. Cibrario et al recently showed that some strains of the 1st Wine 3N (red) group were highly tolerant to high ethanol content [63]. It can be hypothesized that the progressive increase in wine alcohol level could have triggered the selection of fitter individuals regarding ethanol content. Second, the two Wine 3N groups (red and turquoise) show an outstanding phenotypic trait related to adaptation to modern winemaking practices, namely sulfite tolerance/resistance. While sulfur dioxide addition is used in winemaking at least since the 18th century, it became the preferred treatment for B. bruxellensis spoilage in the 90’s, when Chatonnet et al. demonstrated formally that the species was the main responsible for ethylphenol production in wine [3]. Subsequently, control strategies encouraging the use of recurrent sulfite treatments at high dosage have emerged [64]. One possible outcome of the adoption of these strategies by the wine industry might have been the selection of tolerant/resistant strains. For example, in Australia where the use of larger quantities of sulfite was promoted [60, 65], 92% of B. bruxellensis wine isolates were SO2-tolerant in 2012 while in Greece the isolates that belong to the tolerant/resistant group were exclusively isolated from sweet red wine where higher doses of SO2 are detected and permitted [66]. Winemaking environments may have supported the existence of specific selective pressure favouring the retaining of fitter allotriploid individuals and their progressive proliferation in the last decades. Indeed, competition experiments between tolerant and sensitive strains showed that the former outcompeted the latter in high SO2 concentrations [44]. Altogether, our results suggest that independent allotriploidisation events in B. bruxellensis may have allowed diversification and subsequent adaptation to winemaking practices. Since most of the old vintages studied here were from Bordeaux region, it will be necessary to analyze old vintages from other regions to confirm or dispel such trend.

Details of the 1411 strains of Brettanomyces bruxellensis used in this study.

(CSV)

Click here for additional data file.

Minimum spanning tree of wine Brettanomyces bruxellensis isolates using a 2N-constrained dataset.

1411 strains were genotyped using 12 microsatellite markers. For each strain (and each locus) showing 3 alleles, one of the three alleles was randomly removed to produce a randomly 2N-constrained dataset. A PCA was then performed using the R ade4 package. Only the two first axes (principal component, PC1 and PC2) were represented. The connection network and minimum spanning tree was built using the chooseCN function from R adegenet package. For genetically identical isolates (aka ‘clones’), the size of the points is log10 proportional to the number of isolates.

(TIF)

Click here for additional data file.

9 Oct 2019

PONE-D-19-25158

Brettanomyces bruxellensis wine isolates show high geographical dispersal and long remanence in cellars

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript by Cibrario and collaborators reports a population analysis of Brettanomyces bruxellensis strains carried out by means of microsatellite analysis. Thanks to this analysis, the authors found a population structure shaped by geography and strain ploidy. I addition, analysis on 100 years old wines highlighted the recent insurgence of strains resistant to sufites, suggesting a role of antropogenic activities on the evolution of the studied microbial species.

my major concern is related to the novelty of the study. Apparently, all the data were published in previous works by the same authors of this study. It seems that the vast majority of strains were characterized through microsatellite and phenotypic analyses in the work by Avramova et al. (2018). In that study, the authors reported the structure of B. bruxellensis population is shaped by geography and substrate of isolation. In the current study, they report similar resultswith an additional new result: the observation of the long-term remanence of B. bruxellensis in wines. However, the authors refer to a ‘submitted’ study which, according to the title, seems to point out exactly this result: Lleixà J, Martínez-Safont M, Magani M, Masneuf-Pomarede I, Albertin W, Mas A, et al. Genetic and phenotypic diversity of Brettanomyces bruxellensis isolates from aging wines. Food Microbiol. Submitted.

Furthermore, if different studies were collated together, how did the authors merged the microsatellite data? Microsatellite profiling tends to be highly affected by laboratory-dependent biases. Were common strains included in every analysis and used as the reference to normalize the results? In general, further details should be provided in the materials and methods section. It also strikes me the fact that diploid and triploid profiles were analyzed together. The presence of three or two alleles in some loci (as reported in supplementary table 1) is surely the main reason the strains group according to the ploidy. Unless the data were standardized before the analysis.

The most interesting finding is probably the one on ‘old wine’ isolates, suggesting an impact of antripologic activities on the selection/evolution of B. bruxellensis. However, additional factors need to be considered:

1- Have the most recent strains been isolated from must or from wines? As far as I could understand from table S1, the number of isolates from recent wines out is higher than the number of strains isolated from old wines. If this is correct, author should consider that they may have sampled only part of the population present in the wine. If all the colonies formed from the analysis of old wines were analyzed, hence all the cultivable population was sampled, author should consider that the lack of isolation of sulfite-resistant strains in old wines could also be ascribed to the fact they may be more persistent that resistant strains. Hence, future analyses of the most recent wines would result in the isolation of sulfite-sensitive strains only as the resistant one could have died earlier.

2- How do the authors explain the fact that clones were isolated from wines sampled in different years but not over the intermediate years? For instance, the third clone from winery B1 was isolated in ~1930 and in ~2014, but not in wines sampled between these two dates. This could be ascribed to either a non-representative sampling of the population or by independent infections of the same clone from external sources. In the first case, the hypothesis that strains could survive in VNC form would still stand, but the observation of the insurgence of sulfite-resistant genotypes would be based on shaking foundations as the resistant strains may not have been sampled (see also my previous comment). In the latter case, both hypotheses would still be valid, but in a different environment (not the winery).

Concerning the study on ‘clones’, authors should discuss the possibility that extending the microsatellite analysis to more than 12 loci could result in the identification of more intra-strains differences.

It is interesting that In Denmark and in Brazil sulfite-resistant strains were not isolated. It would be interesting to assess whether these two regions have something in common that makes them different from the other regions.

Minor comments:

- please use ‘structure’ rather than ‘structuration’

L47: it should be ‘published each year over the last decade’

L53: methods/approaches/analyses should be used instead of ‘markers’

L62-63: it is not clear what the authors meant here. Why genetic oddity should prompt the development of microsatellite markers? Actually, the ‘genetic oddity’ reported by the authors (existence of diploid and allotriploid strains), may rather complicate microsatellite analysis.

L76: Please check the sentence. Assessing the diversity at the species level means to compare different species, whereas the study is based on a comparison among strains.

L111: it should be the lowest diversity.

L113: please correct, it should be ‘Wine/Kombucha 2N and Wine 3N turquoise groups’

L115: please correct with ‘the genetic groups compared to...’

L236-238: please rephrase the sentence, it is not clear.

L253: a verb is probably missing here, as the verb further does not fit with the rest of the sentence.

Figure 6: are the colors used as in previous figures? If yes, why only Wine 2N are indicated as ‘inter-continenr clone pairs’? Accroding to figure 5, also clone couples of the groups red Wine 3N and Wine/Beer 3N were found in different continents. If not, please use different colors (are colors really necessary, though?)

Reviewer #2: The study by Cibrario et al. examines the geographical and temporal trends underlying Brettanomyces bruxellensis diversity in winemaking environments using previously published microsatellite genotyping data of 1411 wine isolates from 21 countries (published by Avramova et al. (2018), Dimopoulou et al. (2019) and Lleixa et al., submitted).

This study shows that B. bruxellensis wine isolates are characterized by a high genetic diversity and the distribution of the different genetic groups varies at both the geographical and temporal level. The results also show a long-term remanence of B. bruxellensis wine isolates in cellars and a high geographical dispersal among countries and sometimes even continents. One of the most interesting result of this work is the fact that the proportion of diploids and triploids changes with time. Triploids which show a higher resistance to sulphites emerged more recently and their increase in frequency is concomitant with the increased uses of sulphite treatments in the 90’s. The results suggest that allotriploidisation is a recent adaptation event to winemaking practices. This study gives insights on how the genetic diversity of B. bruxellensis could be shaped by anthropic activities. It may also be interesting for wine industry by providing better knowledge of genetic characteristics of the main wine spoiler yeast for a better spoilage prevention and improvement of treatment methods in the winery.

The manuscript is in general well-written and clear. There are some concerns that could be considered.

Major concerns:

My overarching request is that the authors better discuss and analyze some aspects of the interesting data they have.

I find the text, in places, to be somewhat assertive concerning the identification of the ploidy of strains. The microsatellite method alone is not sufficient to confirm with certitude the ploidy level of a yeast strain as we cannot exclude the presence of aneuploidies. In general, whole genome sequencing and flow cytometry (FACS) are complementary methods to confirm more accurately the ploidy level. Thus, It would be more accurate to state that the mentioned ploidy in the text is “putative ploidy” if it has been identified by microsatellite method alone.

-Figure1 : This figure shows that there is three main groups of B. bruxellensis Wine 3N, Wine /Beer3N and Wine 2N, Wine 3N and Wine/Kombucha 2N that cluster together. There is some strains that are classified in a group but cluster with another one. For example, some strains from Wine 2N cluster with the Wine/Beer 3N. It would be nice to see discussion about that.

-Figure 2 and 3: I am wondering whether the genetic distribution of B. bruxellensis wine isolates in different regions or countries presented in figure2 represent all strains isolated at the same period of time or it contains all isolates from all studied periods? The data presented in the subsequent figure 3 show that there is a variation of the genetic groups distribution over the time. It would be nice to see a geographic distribution by period of time. The same thing for the temporal distribution in figure 3, Is it the temporal distribution of all isolates from different regions and countries? It would be very interesting and informative to see the distribution of isolates by region and over the time to see the variation of a combined spatio-temporal distribution. This will shed light on the difference in evolution of isolates distribution by region/country.

-The number of isolates is very different among the different periods in figure2. The last 20 years the number of isolates is hundred times higher than the beginning of the 20th century. This should be mentioned as a limitation as made for the different number of isolates from the different regions in the first paragraph of discussion.

Minor concerns:

-Table 1 and figure 1 : There is two distinct groups called “Wine 3N”,  for clarity it would be useful to better distinguish between these two distinct groups by name and not only colours and shapes.

-Figure 2 : for clarity it would be useful to add color legend in the figure and indicate more precisely in the map the region origin of Non-European countries because countries like USA and Australia (continent) encompass a very large geographic areas.

-Figure 3 : The legend is not complete: wine/Kombucha “2N” and Tequila/Ethanol “3N”.

-Figure 4: for clarity it would be useful to add colours and shapes legends of the different genetic groups and also to indicate the geographical origins of each winery in the figure legend.

-Materials & methods : Very brief section and for the first part “Yeast strains and microsatellite genotyping”, I’m wondering if there are new genotyping in this study or all data have been already genotyped and published previously by Avramova et al., 2018 and Dimopoulou 2019 and Lleixa et al., (submitted). It is not clear why there is the Agar-YPD medium composition in this section.

-Supplementary table: the genetic group is indicated by the colour and not the group name (Wine 2N, Wine 3N… ect), for clarity and consistency, It would be better to add the group names as in the main text.

**********

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Reviewer #1: Yes: Irene Stefanini

Reviewer #2: No

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18 Oct 2019

Dear Editor,

Please find a revised version of our manuscript entitled ‘Brettanomyces bruxellensis wine isolates show high geographical dispersal and long persistence in cellars ’. We have carefully corrected our paper according to the reviewer’s comments, as detailed below. We would like to thank the reviewers for their constructive and insightful comments that helped to improve our manuscript.

Awaiting for your editorial decision,

Sincerely,

The authors

2. During your revisions, please note that a simple title correction is required: the English word 'remanence' is inappropriate in this context. Please alter the title to "Brettanomyces bruxellensis wine isolates show high geographical dispersal and long persistence in cellars", or similar. Please ensure this is updated in the manuscript file and the online submission information. Please also change the use of the word 'remanence' throughout the manuscript

=> Remanence was replaced by persistence throughout the text.

5. Review Comments to the Author

Reviewer #1: The manuscript by Cibrario and collaborators reports a population analysis of Brettanomyces bruxellensis strains carried out by means of microsatellite analysis. Thanks to this analysis, the authors found a population structure shaped by geography and strain ploidy. I addition, analysis on 100 years old wines highlighted the recent insurgence of strains resistant to sufites, suggesting a role of antropogenic activities on the evolution of the studied microbial species.

my major concern is related to the novelty of the study. Apparently, all the data were published in previous works by the same authors of this study. It seems that the vast majority of strains were characterized through microsatellite and phenotypic analyses in the work by Avramova et al. (2018). In that study, the authors reported the structure of B. bruxellensis population is shaped by geography and substrate of isolation. In the current study, they report similar results with an additional new result: the observation of the long-term remanence of B. bruxellensis in wines. However, the authors refer to a ‘submitted’ study which, according to the title, seems to point out exactly this result: Lleixà J, Martínez-Safont M, Magani M, Masneuf-Pomarede I, Albertin W, Mas A, et al. Genetic and phenotypic diversity of Brettanomyces bruxellensis isolates from aging wines. Food Microbiol. Submitted.

=> The study written by Lleixà J, Martínez-Safont M, Magani M, Masneuf-Pomarede I, Albertin W, Mas A, et al., entitled “Genetic and phenotypic diversity of Brettanomyces bruxellensis isolates from aging wines” that was submitted to Food Microbiol reports the phenotypic characterization of 64 Spanish isolates, that were not included in the Avramova paper. These isolates were harvested from aging wines (8-14-months aging in barrels), but not ‘old’ wines (> 2000 vintage). In Lleixa paper, microsatellite analysis is simply used to check genetic clustering before phenotypic analysis, so there is no redundancy regarding the conclusion drawn between this paper and Lleixa’s. There is no redundancy with Avramova’s paper as well, since the main conclusions of this paper (wine isolates show high geographical dispersal and long persistence in cellars) were not described in Avramova’s paper. In short, we used genotyping data from previous papers, but we described new insights through a focus on wine isolates. Note that we deleted the reference to Lleixa’s paper, since it is still in review.

Furthermore, if different studies were collated together, how did the authors merged the microsatellite data? Microsatellite profiling tends to be highly affected by laboratory-dependent biases. Were common strains included in every analysis and used as the reference to normalize the results? In general, further details should be provided in the materials and methods section.

=> The reviewer is right; merging microsatellite data can indeed be a problem. All genotyping analyses were performed by only one lab (UR Oeno), using the same experimental conditions. But even within a given laboratory, over time, microsatellite profiling can change, although marginally (ie it is frequent to observe 1pb difference between different genotyping batches). This is why we included in our genotyping batch 1-2 reference strains for normalization. These elements were missing in the material and method section, now improved and clarified (lines 92-102 in the 'Revised Manuscript with Track Changes’).

It also strikes me the fact that diploid and triploid profiles were analyzed together. The presence of three or two alleles in some loci (as reported in supplementary table 1) is surely the main reason the strains group according to the ploidy. Unless the data were standardized before the analysis.

=> One difficulty when dealing with populations showing different ploidy level is to use appropriate analyses that will not bias the results. In a previous paper (Avramova et al, 2018), we used raw genotyping data (unstandardized regarding ploidy) and various approaches (Bruvo’s genetic distance (specifically designed to support mixed ploidy populations) and NJ clustering; UPGMA clustering, multidimensional scaling, PCA, etc. In all these cases, the clusters were globally conserved whatever the approach. In addition, a “core genotype analysis” was performed, in which alleles identified as triploid-specific were excluded in order to study specifically the “core diploid” genotypes. All analyses gave similar results and clustering, showing, using different tools/approaches, that the presence of 2 or 3 alleles wasn’t the main reason for the observed clustering. To demonstrate that point formally here, we performed the following simulation: for each strain and each locus showing 3 alleles, we randomly removed one of the three alleles and perform the same PCA analysis. The result is shown in a new figure (S1 Fig), which is very close to the PCA obtained with the complete dataset. The “Mat & Met” and “Results” sections are modified to describe the new S1 Fig (lines 109-113; 136-141 in the 'Revised Manuscript with Track Changes’).

The most interesting finding is probably the one on ‘old wine’ isolates, suggesting an impact of antripologic activities on the selection/evolution of B. bruxellensis. However, additional factors need to be considered:

1- Have the most recent strains been isolated from must or from wines?

=> Most isolates (old or recent) were isolated from wine, scarcely any from must, lees, grape or winery environment. We added a new “Detail” column for S1 Table with these data.

As far as I could understand from table S1, the number of isolates from recent wines out is higher than the number of strains isolated from old wines. If this is correct, author should consider that they may have sampled only part of the population present in the wine. If all the colonies formed from the analysis of old wines were analyzed, hence all the cultivable population was sampled, author should consider that the lack of isolation of sulfite-resistant strains in old wines could also be ascribed to the fact they may be more persistent that resistant strains. Hence, future analyses of the most recent wines would result in the isolation of sulfite-sensitive strains only as the resistant one could have died earlier.

=> Indeed, we can’t rule out the possibility that 2N strains are more persistent than 3N strains. This point is discussed lines 341-343 in the 'Revised Manuscript with Track Changes’.

2- How do the authors explain the fact that clones were isolated from wines sampled in different years but not over the intermediate years? For instance, the third clone from winery B1 was isolated in ~1930 and in ~2014, but not in wines sampled between these two dates. This could be ascribed to either a non-representative sampling of the population or by independent infections of the same clone from external sources. In the first case, the hypothesis that strains could survive in VNC form would still stand, but the observation of the insurgence of sulfite-resistant genotypes would be based on shaking foundations as the resistant strains may not have been sampled (see also my previous comment). In the latter case, both hypotheses would still be valid, but in a different environment (not the winery).

=> For winery B1, 15 vintages between 1911 and 2014 were sampled, and a large diversity was evidenced (15 clone groups). Since less than 20 isolates were studied for most old samples, it may explain why the 3rd clone of B1 was found only in ~1930 and in ~2014. Thus, even if our total number of Brett isolates (>1400) is important, per sample we may have small sample size bias. This point is now discussed (lines 292-296 in the 'Revised Manuscript with Track Changes’).

Concerning the study on ‘clones’, authors should discuss the possibility that extending the microsatellite analysis to more than 12 loci could result in the identification of more intra-strains differences.

=> Reviewer 1 is right again. This fact is now discussed (lines 304-308 in the 'Revised Manuscript with Track Changes’).

It is interesting that In Denmark and in Brazil sulfite-resistant strains were not isolated. It would be interesting to assess whether these two regions have something in common that makes them different from the other regions.

=> A small number of isolates were studied for Denmark and Brazil, prompting the need for larger samples. This point is now discussed (lines 288-289 in the 'Revised Manuscript with Track Changes’).

Minor comments:

- please use ‘structure’ rather than ‘structuration’

L47: it should be ‘published each year over the last decade’

L53: methods/approaches/analyses should be used instead of ‘markers’

L62-63: it is not clear what the authors meant here. Why genetic oddity should prompt the development of microsatellite markers? Actually, the ‘genetic oddity’ reported by the authors (existence of diploid and allotriploid strains), may rather complicate microsatellite analysis.

L76: Please check the sentence. Assessing the diversity at the species level means to compare different species, whereas the study is based on a comparison among strains.

L111: it should be the lowest diversity.

L113: please correct, it should be ‘Wine/Kombucha 2N and Wine 3N turquoise groups’

L115: please correct with ‘the genetic groups compared to...’

L236-238: please rephrase the sentence, it is not clear.

L253: a verb is probably missing here, as the verb further does not fit with the rest of the sentence.

=> We corrected the manuscript accordingly

Figure 6: are the colors used as in previous figures? If yes, why only Wine 2N are indicated as ‘inter-continenr clone pairs’? Accroding to figure 5, also clone couples of the groups red Wine 3N and Wine/Beer 3N were found in different continents. If not, please use different colors (are colors really necessary, though?)

=> Thanks for pointing this. Colors in figure 6 were indeed not related to the genetic groups, and a new figure 6 without colors is proposed.

Reviewer #2: The study by Cibrario et al. examines the geographical and temporal trends underlying Brettanomyces bruxellensis diversity in winemaking environments using previously published microsatellite genotyping data of 1411 wine isolates from 21 countries (published by Avramova et al. (2018), Dimopoulou et al. (2019) and Lleixa et al., submitted).

This study shows that B. bruxellensis wine isolates are characterized by a high genetic diversity and the distribution of the different genetic groups varies at both the geographical and temporal level. The results also show a long-term remanence of B. bruxellensis wine isolates in cellars and a high geographical dispersal among countries and sometimes even continents. One of the most interesting result of this work is the fact that the proportion of diploids and triploids changes with time. Triploids which show a higher resistance to sulphites emerged more recently and their increase in frequency is concomitant with the increased uses of sulphite treatments in the 90’s. The results suggest that allotriploidisation is a recent adaptation event to winemaking practices. This study gives insights on how the genetic diversity of B. bruxellensis could be shaped by anthropic activities. It may also be interesting for wine industry by providing better knowledge of genetic characteristics of the main wine spoiler yeast for a better spoilage prevention and improvement of treatment methods in the winery.

The manuscript is in general well-written and clear. There are some concerns that could be considered.

Major concerns:

My overarching request is that the authors better discuss and analyze some aspects of the interesting data they have.

I find the text, in places, to be somewhat assertive concerning the identification of the ploidy of strains. The microsatellite method alone is not sufficient to confirm with certitude the ploidy level of a yeast strain as we cannot exclude the presence of aneuploidies. In general, whole genome sequencing and flow cytometry (FACS) are complementary methods to confirm more accurately the ploidy level. Thus, It would be more accurate to state that the mentioned ploidy in the text is “putative ploidy” if it has been identified by microsatellite method alone.

=> We modified our text to be more prudent regarding the possible ploidy level of Brett strains (lines 28, 36, 71 and afterward in the 'Revised Manuscript with Track Changes’). However, note that, to date, our assessment of ploidy level is congruent with the one obtained using full genome sequencing.

-Figure1 : This figure shows that there is three main groups of B. bruxellensis Wine 3N, Wine /Beer3N and Wine 2N, Wine 3N and Wine/Kombucha 2N that cluster together. There is some strains that are classified in a group but cluster with another one. For example, some strains from Wine 2N cluster with the Wine/Beer 3N. It would be nice to see discussion about that.

=> Again a pertinent comment. We kept the initial distribution into clusters performed by Avramova et al. (2018). Non-wine strains from the initial subset were removed, while some others were added, mostly wine strains from Greece (Dimopoulou et al, 2019) and Spain (Lleixa et al, submitted). The clusters were globally well conserved, except for a few strains (<15) whose position varied a bit, usually “peripheric” strains. This issue is now pointed out (lines 128-130 in the 'Revised Manuscript with Track Changes’).

-Figure 2 and 3: I am wondering whether the genetic distribution of B. bruxellensis wine isolates in different regions or countries presented in figure2 represent all strains isolated at the same period of time or it contains all isolates from all studied periods? The data presented in the subsequent figure 3 show that there is a variation of the genetic groups distribution over the time. It would be nice to see a geographic distribution by period of time. The same thing for the temporal distribution in figure 3, Is it the temporal distribution of all isolates from different regions and countries? It would be very interesting and informative to see the distribution of isolates by region and over the time to see the variation of a combined spatio-temporal distribution. This will shed light on the difference in evolution of isolates distribution by region/country.

=> Fig 2 and 3 indeed presents all wine strains (for which geographic origins and/or vintages were known). While our dataset contains an important number of wine strains, the distribution is not homogeneous over time and region, so that spatio-temporal variation can’t be assessed with this dataset. The need for more isolates from different regions and/or vintages is now discussed (lines 292-296 in the 'Revised Manuscript with Track Changes’).

-The number of isolates is very different among the different periods in figure2. The last 20 years the number of isolates is hundred times higher than the beginning of the 20th century. This should be mentioned as a limitation as made for the different number of isolates from the different regions in the first paragraph of discussion.

=> The unequal sampling of isolates over time (and over region) is now discussed (lines 344-345 in the 'Revised Manuscript with Track Changes’)

Minor concerns:

-Table 1 and figure 1 : There is two distinct groups called “Wine 3N”, for clarity it would be useful to better distinguish between these two distinct groups by name and not only colours and shapes.

=> The two Wine 3N were called 1st Wine 3N and 2nd Wine 3N respectively, in the manuscript, tables and figures.

-Figure 2 : for clarity it would be useful to add color legend in the figure and indicate more precisely in the map the region origin of Non-European countries because countries like USA and Australia (continent) encompass a very large geographic areas.

=> Unfortunately, for many strains from collection, we have no mention of the precise area of isolation (only the country). We added the legend in the Figure 2 as requested.

-Figure 3 : The legend is not complete: wine/Kombucha “2N” and Tequila/Ethanol “3N”.

=> This display issue was corrected.

-Figure 4: for clarity it would be useful to add colours and shapes legends of the different genetic groups and also to indicate the geographical origins of each winery in the figure legend.

=> The legend was added

-Materials & methods : Very brief section and for the first part “Yeast strains and microsatellite genotyping”, I’m wondering if there are new genotyping in this study or all data have been already genotyped and published previously by Avramova et al., 2018 and Dimopoulou 2019 and Lleixa et al., (submitted). It is not clear why there is the Agar-YPD medium composition in this section.

=> This part was rewritten for clarity

-Supplementary table: the genetic group is indicated by the colour and not the group name (Wine 2N, Wine 3N… ect), for clarity and consistency, It would be better to add the group names as in the main text.

=> The table was corrected accordingly

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

14 Nov 2019

Brettanomyces bruxellensis wine isolates show high geographical dispersal and long persistence in cellars

PONE-D-19-25158R1

Dear Dr. Albertin,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: please be careful with the special character, all the Greek characters (e.g. mu for micro) have disappeared after the conversion to pdf.

Reviewer #2: The authors have thoroughly revised the manuscript and addressed each of my comments in their response letter.

I am satisfied with the majority of revisions they have made in response to my initial comments. I have only a follow-up comment that pertain to the revision. In figure 3, if I understood well and according to the supplementary table all old isolates sampled before 2000 are from Bordeau. Also, 586 of isolates sampled after 2000 are from Bordeau Thus for consistency, It would be more accurate to keep only samples from Bordeau for the temporal distribution at all time points in the figure.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Irene Stefanini

Reviewer #2: No

19 Nov 2019

PONE-D-19-25158R1

Brettanomyces bruxellensis wine isolates show high geographical dispersal and long persistence in cellars

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