evidence for local dispersal by insects and ... - Wiley Online Library

Environmental Microbiology (2010) 12(1), 63–73

doi:10.1111/j.1462-2920.2009.02035.x

A distinct population of Saccharomyces cerevisiae in New Zealand: evidence for local dispersal by insects and human-aided global dispersal in oak barrels emi_2035

Matthew R. Goddard,* Nicole Anfang, Rongying Tang, Richard C. Gardner and Casey Jun The School of Biological Sciences, University of Auckland, Auckland, New Zealand. Summary Humans have used S. cerevisiae to make alcoholic beverages for at least 5000 years and now this supermodel research organism is central to advances in our biological understanding. Current models for S. cerevisiae suggest that its population comprises distinct domesticated and natural groups as well as mosaic strains, but we generally know little of the forces which shape its population structure. In order to test the roles that ecology and geography play in shaping the S. cerevisiae species we examined nine variable microsatellite loci in 172 strains of S. cerevisiae isolated from two spontaneous grape juice ferments, soil, flowers, apiaries and bark in New Zealand. Bayesian analysis shows that the S. cerevisiae in NZ comprise a subdivided but interbreeding population that out-crosses ~20% of the time. Some strains contributing to spontaneous ferments cluster with NZ soil/bark isolates, but others cluster with isolates from French oak barrels. It seems some strains have been globally dispersed by humans in oak barrels while some are locally vectored by insects. These data suggest geography is more important than ecology in shaping S. cerevisiae’s population structure. Introduction Humans have unwittingly used Saccharomyces cerevisiae since the dawn of civilization: traces of fermented beverages have been found in 9000-year-old Chinese pots (McGovern et al., 2004) and S. cerevisiae DNA has been isolated from a 5000-year-old wine jar (Cavalieri et al., 2003). More recently, this human–microbe association has become increasingly sophisticated. S. cerevisiae Received 21 May, 2009; accepted 9 July, 2009. *For correspondence. E-mail [email protected]; Tel. (+64) 9 373 7599 ext. 89537; Fax (+64) 9 373 7946.

© 2009 Society for Applied Microbiology and Blackwell Publishing Ltd

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was one the first microbes to be visualized when the microscope was invented (Weeks and Alcamo, 2008), and now S. cerevisiae is a super-model research organism used generally to investigate the molecular biology, genetics and evolution of eukaryotes (Zeyl, 2000; Landry et al., 2006). Considering the significance of this singled celled fungus it is surprising how little we know of the forces which have shaped its genome and population structure (Aa et al., 2006; Landry et al., 2006; Goddard, 2008). A handful of studies have examined the population biology of S. cerevisiae (Aa et al., 2006; Ezov et al., 2006; Fay and Benavides, 2006; Ruderfer et al., 2006; Legras et al., 2007), and recently the global population structure of S. cerevisiae has been estimated by microarray and re-sequencing analyses of an overlapping set of 63 and 38 strains (Liti et al., 2009; Schacherer et al., 2009). These analyses suggest there are between three and five major global lineages of S. cerevisiae but that there are also mosaics strains which have ancestry in more than one of these genetically distinct lineages. Some lineages comprise isolates from human-associated wine and sake ferments: these are suggested to represent ‘domestication’ events which have then been globally dispersed via the human transport of vines (Mortimer and Polsinelli, 1999; Legras et al., 2007). However, the fact that divergent strains have been isolated from niches not associated with fermentation, such as oak trees, soil and insects, suggests that S. cerevisiae is not domesticated generally (Liti et al., 2009; Schacherer et al., 2009). Studies that analyse contemporaneous populations of S. cerevisiae are rare, and all have examined populations deriving from soil/plant niches (Sniegowski et al., 2002; Ezov et al., 2006; Sampaio and Goncalves, 2008). While the current data support a human-aided radiation model for S. cerevisiae associated with fermentation, we know little about the mechanisms of dispersal. Overall, geography is thought to play less of a role in shaping S. cerevisiae’s population structure than ecology, especially when compared with S. paradoxus (Koufopanou et al., 2006; Tsai et al., 2008; Liti et al., 2009); however, because there are no studies which have contemporaneously isolated and analysed strains from different niches, it is difficult to decipher the roles that ecology and geography play in

64 M. R. Goddard et al. shaping S. cerevisiae’s population structure (Schacherer et al., 2009). In order to test directly the roles that geography and ecology play in shaping S. cerevisiae’s population structure, and the idea that S. cerevisiae may be globally dispersed via humans’ activities, we surveyed for the presence of S. cerevisiae on a remote, recently inhabited island: New Zealand (NZ). Humans have been present in NZ for only the last ~700 years (King, 2003), and the human introduction of vines for wine production only occurred in the last 100 years or so (Cooper, 2002). We address the question of whether there are any natural populations of S. cerevisiae in NZ. If so, how do they relate to strains isolated from a variety of different international locations and niches?

bial communities in other niches (Hughes et al., 2001) and fits a log normal distribution [P < 0.01 based on a goodness-of-fit to an empirical distribution function (Kolomogorov’s D); m = 0.73; s = 0.981]. While we may have adequately sampled the abundant genotypes it seems that the tail of rare genotypes is very long. The suite of methods within Estimate S (Colwell, 2005) was used to gauge the likely asymptote of the novel genotype accumulation curve (expected genotype richness) and suggests this ferment harboured as many as 150 different genotypes. The discovery of a diversity of S. cerevisiae in this ferment is in line with reports concerning diversity in a handful of spontaneous European ferments (Valero et al., 2007). However, this provides the first direct evidence for the presence of a diverse population of S. cerevisiae in NZ.

Results and discussion A NZ spontaneous ferment contains multiple genotypes of S. cerevisiae To survey for the presence of S. cerevisiae in NZ, we initially sampled a spontaneous (un-inoculated) Chardonnay ferment at the Kumeu River winery in West Auckland. We analysed the ribosomal spacer region of ~800 random isolates from this ferment. S. cerevisiae was present initially but at very low frequency (~1/1500th of the community); however, it increased in frequency until, by day 11 of the ferment, S. cerevisiae dominated the community due to its ecosystem engineering via fermentation (Goddard, 2008). To scrutinize more closely the S. cerevisiae population present we scored repeat length at nine variable microsatellite loci (Richards et al., 2009). We differentiated 88 different microsatellite profiles (genotypes) from 380 S. cerevisiae isolates taken throughout the ferment. The distribution of these genotypes echoes that of micro-

Approximately 20% of the matings in this S. cerevisiae population were between spores derived from independent genomes. Traditional methods of analysing diploid data from eukaryotes do not account for the independent clonal expansion of linked loci (genotypes); therefore, all population genetic tests were conducted on data where replicates of identical genotypes were removed. The Kumeu ferment S. cerevisiae population’s alleles show a deviation from Hardy– Weinberg (H-W) proportions through a significant deficit of heterozygotes (P < 0.0001, Table 1); in addition the nine loci are in significant linkage disequilibrium (P < 0.01). The deviation from the random intermixing of alleles is undoubtedly in part due to aspects of S. cerevisiae’s life history which strongly encourage inbreeding: within ascus mating and mating type switching (Knop, 2006). Since sustained inbreeding would rapidly remove heterozygotes

Table 1. Population information for the sub-populations of Saccharomyces cerevisiae analyzed. Isolation source

Number of genotypes (cumulative) Mean number of allelesb Mean FISc Out-crossing rate (t)d Cumulative number of inferred groupse No. of chimerasf

Kumeu ferment

Matua valley

International isolatesa

French barrel

Fossil Bay ferment

88 8.2 0.64 0.19 (0.15–0.24) 5.8 ⫾ 0.61 21/88

22 (110) 5.6 1.00 0 7.5 ⫾ 0.52 7/22

34 (144) 15.8 n/a n/a 12.8 ⫾ 1.71 19/34

40 (184) 4.6 0.67 0.29 (0.19–0.40) 12.1 ⫾ 1.45 6/40

22 (206) 6.7 0.58 0.17 (0.09–0.27) 11.6 ⫾ 1.28 11/22

a. The strains as described in Liti and colleagues (2009); haploid spores were sequenced making out-crossing rate inference meaningless for this group. b. Mean number of alleles per locus across all nine loci. c. The mean inbreeding coefficient across all nine loci (a value of 1 indicates a completely inbred population). d. The inferred proportion of matings between spores from independent genotypes at each meiotic generation with 2 log likelihood support limits see Johnson and colleagues (2004). e. The cumulative inferred number of subpopulations (E[K|X] and variance (Var[K|X]) from analyses with Structurama when each set of isolates is added. f. The proportion of genotypes in each set of isolates inferred to have 11% or greater of their ancestry in more than one subpopulation.

© 2009 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 12, 63–73

S. cerevisiae’s population biology 65 the observation of heterozygous loci means, barring mutations, that some frequency of out-crossing (the union of spores derived from independent genomes) occurred in the history of this population (Johnson et al., 2004). Likelihood analysis suggests around 20% of matings in this population were between spores from independent asci (Table 1). This S. cerevisiae population is subdivided Do the strains contributing to this ferment derive from one population or more than one? Testing for evidence of population structure is a notoriously hard problem and one major drawback with the classical methods is that they rely on assigning individuals to subpopulations a priori (Huelsenbeck and Andolfatto, 2007). One alternative is to use the Bayesian methods developed by Falush and colleagues (2003) and extended by Huelsenbeck and Andolfatto (2007); these in essence maximize the likelihood of observing the data using a model that attempts to find the number of subpopulations or clusters (K), which minimize the deviation from H-W equilibrium within subpopulations. The strength of these approaches is that they require no a priori assumptions concerning groupings and one may use these analyses to infer whether structure exists, the likely number of subpopulations and individuals’ assignments to these. Analyses of the Kumeu River ferment population with these methods suggests that they do not derive from a single homogenous population but rather six subpopulations (Table 1). The strength of the methods implemented in Structurama is that the likely number of subpopulations may easily be inferred, but the drawback is that it does not use a model which allows one to infer the degree to which individuals have ancestry in more than one subpopulation. The admixture model used in Structure allows just this and so to gauge the extent to which certain strains likely represent hybrids between inferred clusters (chimeras), we conducted an analysis where the number of populations was set to that inferred using Structurama (K = 6). This analysis shows that 67 of the 88 strains belong to one of the six discrete clusters (i.e. 90% or more of their ancestry is inferred to be in one subpopulation only), but that the remaining 21 genotypes have at least 11% of their ancestry split between more than one cluster. We then pursued an alternative approach to examine population structure and converted the differences between these genotypes to a genetic distance matrix: we used a conservative distance measure that simply considered the degree to which two genotypes differ (it made no assumption about the mutational process of microsatellite repeat number; Peakall and Smouse, 2006). A network is a more accurate way to plot the relationships between eukaryotic genotypes since, unlike a binary tree, conflicting and reticulated rela-

tionships may be represented (Huson and Bryant, 2006). A star–burst network would indicate a homogeneous population, but some population structure is apparent if Fig. 1 is examined. The clusters inferred using the Bayesian approaches correlate well with groupings as suggested using the genetic distance method. Since there is evidence this S. cerevisiae population is inbred this will tend to amplify signal for population structure; however, as around 24% of the strains in this population represent chimeras this analysis provides evidence for gene flow between subpopulations and correlates with our above independent estimate that ~20% of matings between these strains are out-crossed. The population is not related to known commercial yeast strains Even though it is not routinely practiced at Kumeu River, the majority of NZ wineries add commercial wine strains (sourced from overseas) at extremely high numbers (~106 ml-1) to increase ferment reliability, and there are reports from Europe suggesting that commercial strains may ‘escape’ from wineries (Valero et al., 2005). Consequently, a simple explanation for the presence of this S. cerevisiae population is that they are commercial wine yeasts used by neighbouring wineries. However, none of the genotypes from Kumeu River remotely resemble any of the 78 commercial strains in our collection, which includes the strains commonly used in NZ (no one isolate shares more than 55% of its alleles with any commercial strain). Local natural isolates of S. cerevisiae are related to a subset of the fermentation strains What then is the origin(s) of this population? Since we failed to detect any S. cerevisiae in the winery before harvest (winery equipment and walls were sampled, data not shown), we hypothesized that the strains contributing to the ferment were brought into the winery with the grapes and represent members of populations inhabiting the local environment. In order to test this we sampled the soil, bark and flowers from Matua Valley vineyard which is surrounded by indigenous bush and only 6 km away from Kumeu River. These samples yielded 122 colonies identified to be S. cerevisiae, among which we discovered 22 different genotypes (2 from vine bark, 2 from buttercup flowers and 18 from soil). Some genotypes were isolated from more than one sample (e.g. the Soil1-1 genotype was recovered from five independent soil samples), including some from different niches (e.g. the Buttercup2 genotype was also isolated from bark and soil). It may be that many genotypes are present in all niches, and that our sampling process was not powerful


66 M. R. Goddard et al.

Fig. 1. A network showing the genetic distance between between 110 S. cerevisiae genotypes from a Kumeu River ferment (red) and Matua Valley vineyard soil, bark and flowers (blue). This group as a whole was inferred to fall into seven clusters and the proportion of each strain’s ancestry in each of these is shown. Those strains which are inferred to have 90% or greater ancestry in one of the seven clusters are circled on the network. The remaining strains represent hybrids (chimeras) with ancestry in more than one group. The apiary samples cluster within group 7 as indicated.

enough to detect them. However, since most samples yielded many isolates of the same genotype a more likely explanation is that some strains are being dispersed between areas/niches in this vineyard. The genetic diversity of this population is in line with the ferment population, but in contrast to the ferment population, all the genotypes from Matua Valley are homozygous (Table 1). The inference is this group has experienced no out-crossed matings, at least in the last meiotic generation. The ferment and soil/bark/flower strains are not significantly differentiated by an exact test

(P = 0.36) but an AMOVA shows some degree of difference between them (Fst = 0.16; P < 0.001). None of the Matua genotypes matched any commercial isolate in our database, but neither did they match any of the isolates found in the ferment. We used the Bayesian approaches to test the relationships between the ferment and soil/bark/flower isolates. Approximately seven clusters are inferred when these genotypes are included in an analyses (Table 1) and 81 of the 110 strains unambiguously fall into one of the seven clusters (i.e. 90% or more of their ancestry is inferred to be in one group only);


S. cerevisiae’s population biology 67 clearly the remaining 29 strains have at least 11% ancestry split between more than one cluster. The relationship between these strains, and the inferred clusters, is shown in Fig. 1. While no one cluster is inferred to comprise strains from both the ferment and soil/bark/flowers groups, these groups are interdigitated and some ferment and soil/bark/flower groups are more closely related to one another than to other groups comprising isolates from the same location (e.g. groups 2 and 7 appear more closely related to one another than 7 is to 6; see Fig. 1). In addition, there is evidence for gene-flow between isolates from these different niches, as demonstrated by the presence of strains that have ancestry in both ferment and soil/bark/flower groups (Fig. 1). These data suggest that some of the genotypes in the Kumeu River ferment cluster closely with a local population of S. cerevisiae that resides in soil, and on bark and flowers. Evidence for dispersal of S. cerevisiae via bees Our inference is that strains residing in soil, bark and flowers find themselves in local ferments. There is also some evidence for the dispersal of strains between soil, bark and flower niches. Given that yeast cells are not capable of independent dispersal, how might isolates from the local environment be dispersed among these niches and areas? One hypothesis suggests that insects, including bees, act as vectors (Mortimer and Polsinelli, 1999) and we have observed bees around local vineyards. We took 19 samples over 5 months from an apiary which situates hives near both Kumeu River and Matua Valley. After the SelMed selection step we identified two S. cerevisiae colonies from the 67 analysed. These two genotypes are almost identical and only differ by two base pairs at the YBR240C locus (which is a 2 bp repeat). Strikingly, these genotypes are highly related to genotypes isolated from flowers, bark and soil in Matua Valley. One is an exact match (honeycell1 = buttercup2 = bark1 = soil2); the other is unique among the NZ isolates see Fig. 1. Given the frequencies of the various alleles in the ferment and Matua Valley populations the probability of recovering these genotypes from the apiary by chance (that is they are not connected to the Matua valley population) is ~10-9. This suggests that at least bees may vector S. cerevisiae around West Auckland. NZ isolates are distinct from a sequenced collection of international strains While these analyses suggest that a diverse subdivided but interbreeding S. cerevisiae population resides in and moves around Auckland we have not proved whether these isolates represent a discrete population or not. In line with the human global dispersal hypothesis (Legras

et al., 2007) it could be that these isolates were introduced to NZ from other areas of the world by some means. In order to see if there is any evidence for this we included 34 of the strains analysed by Liti and colleagues (2009), which include genetically diverse isolates that were deliberately selected from diverse global locations and niches, for Bayesian analyses. Not surprisingly, the genetic diversity is very high in this international group and a jump to ~13 subpopulations is inferred when these strains are included (Table 1). Eighty-nine of the 144 strains are inferred to fall discretely into one of these 13 groups (i.e. 90% or more of their ancestry is inferred to be in one group only), with the remaining 55 strains representing various degrees of chimeras. Fifteen of the international isolates form five of these discrete groups, which correlate with groups inferred by Liti and colleagues (2009) (and see Richards et al., 2009). However, none of the international isolates fall into a group that contains NZ isolates, and all but three international isolates are inferred to share less than 3% of their ancestry with any NZ group. The closest three strains, L-1528, DBVPG1373 and BC187, are inferred to share no more than 5%, 8% and 9% of their ancestry, respectively, with a group containing NZ isolates. In order to ascertain whether the population structure we observed, and inference of a discrete NZ population, is likely due to chance, we used a nonparametric method and created a null distribution by permuting the data within loci 26 times (Mathematica code available upon request). We then used Structurama to infer the number of populations from each of these permuted data sets (the computational constrains of running the analyses confined us to examine 26 permuted data sets only). Only one population was inferred from all the 26 permutations and thus the observed population structure, and demarcation of NZ isolates, is significant at the P < 0.05 level using this conservative approach. A network shows NZ and international isolates to be generally separate and the international isolates to be at the end of long branches, indicating they are substantially genetically different (Fig. 2). Only BC187 (a Californian wine strain) and DVPG6765 (unknown origin) shows interdigitation with NZ strains which correlates with the inference of some shared ancestry with NZ isolates in the Bayesian analyses. While there is a suggestion that a small number of international isolates may share a tiny fraction of ancestry with a few NZ isolates, and may therefore indicate some international origin, on average the NZ isolates share less than 0.4% of their ancestry with any international strain and are thus distinct. Our analyses clearly indicate that generally these NZ strains are neither randomly distributed between, nor closely related to, any of the international isolates. We believe this provides evidence that the majority of genotypes isolated in NZ form a discrete group.


68 M. R. Goddard et al.

Fig. 2. A network showing the genetic distance between the Kumeu River, Matua Valley, Fossil Bay, Barrel and international isolates analysed by Liti and colleagues (2009). Groups which comprise only NZ and/or barrel isolates and share 90% or greater ancestry, as inferred by Bayesian methods, are indicated on the network. The group where the barrel isolates cluster is indicated with a cartoon.

Identification of a population of S. cerevisiae in French oak barrels imported to New Zealand Even though the isolates in NZ form a discrete group there is still evidence that these comprise a subdivided population and it may still be that one or more of these subgroups were unwittingly brought to NZ by humans. One possible route would have been along with grape vines when they were first introduced into NZ (Legras et al., 2007). Since vines have been imported and propagated in NZ for over 100 years (Cooper, 2002), it would be pointless to sample contemporary vines since these may equally well have been subsequently colonized by any

indigenous S. cerevisiae. However, there is another natural product associated with winemaking that is transported around the globe by humans, which provides a potential vector for yeasts: oak barrels. The fact that S. cerevisiae has been isolated from oak trees in Europe and North America (Sniegowski et al., 2002; Sampaio and Goncalves, 2008) means that the barrel-derived theory connects two niches, which S. cerevisiae is known to inhabit and makes this an intuitively attractive hypothesis. In order to test this idea directly, we sampled a new barrel imported into NZ from Chagny in the Burgundy region of France. We found 59 isolates that proved to be S. cerevisiae by molecular analyses: microsatellite analyses


S. cerevisiae’s population biology 69 discriminated 40 different genotypes. As far as we are aware this is the first direct evidence that S. cerevisiae is present in new oak barrels and therefore adds a potential agent of global dispersal associated with the wine industry. While the allelic diversity of the barrel-derived population is high (Table 1), again the population shows a significant deficit of heterozygotes (P < 0.001) and therefore strong evidence for inbreeding. The presence of heterozygous loci means the population is not entirely inbred and the out-crossing rate estimate for this population is around 30%. The barrel population comprises one subpopulation found in the ferment The presence of S. cerevisiae in barrels per se does not necessarily mean that these will become established in NZ, and so we tested for any evidence of a connection between these and the existing isolates. The first striking finding was an identical genotype in the barrel and ferment populations (T51 = B62). The probability of recovering this genotype by chance from both populations is ~10-13. This provides evidence for a connection between the populations present in the new barrel and ferments at Kumeu River. The ferment and barrel populations are not significantly differentiated by an exact test (P = 1.0; Excoffier et al., 2005), but there is clearly some degree of divergence between them as indicated by the high Gst’ value (0.76; Hedrick, 2005) and an AMOVA (Rst = 0.40; Fst = 0.24; P < 0.001). The number of inferred populations does not increase when the barrel isolates are included in a Bayesian analyses (Table 1), suggesting they cluster with one of the existing subpopulations. Indeed, all the barrel isolates (except B35) are inferred to strongly cluster with one of the ferment groups (the 18 strains that comprise group 1 in Fig. 1). We conducted the likelihood, Bayesian and frequency-based population assignment tests implemented in GeneClass2 (Piry et al., 2004) and these also show that it is more appropriate to cluster the barrel-derived population with these 18 ferment samples (see Fig. 2). It is clear that one of the six Kumeu River ferment clusters originally inferred constitutes strains that cluster strongly with this French barrelderived group. The inference that just one of the barrel isolates (B35) clusters with strains isolated from soil, bark and flowers is of note. It may be that this strain, which is divergent from the rest of the barrel isolates, truly represents a member of another distinct population, or it may be that this isolate was mislabelled or is a contaminant. Overall, these data provide support for the idea that humans may globally disperse S. cerevisiae and suggest a novel mechanism for that dispersal. It is worth noting that the most abundant genotype discovered in the ferment (T4, comprising 17% of the population) clusters

strongly with the barrel-derived population. However, the second and third most abundant strains in the ferment (T8 and T13) fall away from the barrel-derived populations. S. cerevisiae isolates from other spontaneous ferments support the idea of a distinct NZ population Lastly, as an alternate means to test for the presence of a discrete NZ S. cerevisiae population, we analysed a second spontaneous ferment using Chardonnay grapes from Fossil Bay, a vineyard located on Waiheke, a 92 km2 island located 18 km offshore and 40 km as the crow flies from the Kumeu River/Matua Valley samples. This ferment was conducted in a barrel that had been reconditioned in NZ (i.e. 3–4 mm of the internal wood had been shaved off, and then the barrel was re-toasted and sulfur treated: this is a process likely to kill many microbes present). If there is a NZ population then the prediction is that any S. cerevisiae present in this second spontaneous ferment should cluster away from both the international strains and the French barrel-derived group. We monitored the population dynamics of this ferment and differentiated 22 different genotypes from 150 isolates of S. cerevisiae. The genetic structure of this population is similar in diversity to the Kumeu River ferment population, and has a homozygote excess (P < 0.001): the inferred rate of out-crossed matings is again around 20% (Table 1). None of the isolates from Fossil Bay matched any commercial isolate (though F3, F21 and F23 match ZymafloreF10 at 7 of 9 loci and are thus possibly escaped commercial strains) nor any other strain included in this study. No additional groups are inferred when the Fossil Bay isolates were included with all the other samples for Bayesian analyses, but a Fossil Bay isolate only cluster is now inferred, suggesting some fluidity of the inferred groupings. A total of 11 Fossil Bay isolates are inferred to fall into groups with the ⱖ 90% ancestry criteria, with the rest representing chimeric genotypes to some degree, which is again in line with our inference of out-crossed matings. However, none of the Fossil Bay isolates are remotely assigned to the barrel-derived cluster (all are inferred to have less than 1% ancestry in this group) or with any international isolate cluster (19 isolates share less than 2% ancestry with international clusters; the remaining three, F4, F13 and F14, share no more than 17%). Visualization with Splits-Tree correlates with the Bayesian inference and shows the Fossil Bay genotypes to be clustered strongly away from the French barrel-derived population and to be separate from the international isolates (see Fig. 2). This provides additional evidence that a discrete population of S. cerevisiae resides in NZ. Conclusion Of the 172 genotypes of S. cerevisiae contemporaneously isolated from ferments, soil, bark and flowers in NZ,


70 M. R. Goddard et al. none clustered strongly with any of the 34 sequenced strains isolated from a range of international locations. We believe this provides strong evidence for a discrete population of S. cerevisiae residing in NZ. Bayesian and network analyses show this NZ population not to be homogenous but structured into a number of clusters. Some isolates from spontaneous wine ferments cluster with strains deriving from vineyard bark, soil and flowers. These strains are therefore likely to be locally derived, and we provide evidence that on this small scale (~10 km) S. cerevisiae is dispersed by at least honey bees. Other ferment isolates cluster strongly with isolates deriving from a French oak barrel providing evidence to support the hypothesis that humans vector S. cerevisiae around the globe over distances of ~20 000 km (Legras et al., 2007). It is worth noting that none of the European isolates included in Liti and colleagues’ (2009) analyses cluster with the barrel-derived group, which persists as a strong independent cluster: this group possibly represents a distinct European S. cerevisiae population. It may be that natural populations of S. cerevisiae were present in NZ before humans arrived; alternatively it may be that in the past all isolates associated with fermentation were brought to NZ by humans. Either way, our data show no strong demarcation between NZ S. cerevisiae that inhabit contemporaneous soil/bark/flower and ferment niches. Therefore, our data do not support the hypothesis that there is a sharp demarcation between ‘domesticated’ and ‘natural’ isolates (Fay and Benavides, 2006; Liti et al., 2009; Schacherer et al., 2009), at least in NZ. Of course the caveat in this study is that the soil, bark and flower samples are derived from a vineyard. In contrast to the lack of correlation with ecological niche there seems a stronger genetic demarcation among the NZ strains in line with inference of geographic origin since the French barrel-derived cluster are most prominently grouped. In agreement with data from S. paradoxus (Johnson et al., 2004; Tsai et al., 2008; Liti et al., 2009), the structure of the S. cerevisiae we examined overall seems to be more strongly be influenced by geography rather than ecology – with evidence for global dispersal this is unsurprising given NZ’s remoteness. While the life cycle of S. cerevisiae appears geared for inbreeding, we estimate that approximately one-fifth of matings in the ferment and barrel populations were between spores from independent tetrads, and this estimate correlates with our inference of chimeric genotypes. Estimates for out-crossing rates for S. cerevisiae are sparse: one is based on the comparative genomics of just three strains and is around once every 50 000 divisions (Ruderfer et al., 2006). Our estimate of around 20% outcrossing in the ferment/barrel populations correlates with the only study to give an inbreeding coefficient for S. cerevisiae, and this was based on strains associated with

winemaking in South America (FIS ~0.72; Cubillos et al., 2009; Table 1). Out-crossed sex for S. cerevisiae in fruit niches will enhance gene flow, which will tend to break down population structure. Our inference of out-crossed matings from observed levels of heterozygosity correlates with the inference of chimeras (hybrids) between subpopulations in the Bayesian analyses. All together, these data show that the S. cerevisiae population in NZ is subdivided but that there is significant gene flow between subpopulations. However, our inference of complete inbreeding in the NZ soil/bark/flower populations is more closely aligned with the estimates from a UK S. paradoxus population from oak bark, which are ~99% inbred (Johnson et al., 2004; Tsai et al., 2008). Since the ferment and soil/bark/flower populations are not inferred to be genetically distinct from one another, one explanation for the discrepancy between these observations proposes that S. cerevisiae (and S. paradoxus) is at low frequency and mostly in a sporulated state in these soil/bark/flower niches. These and other (Sniegowski et al., 2002; Johnson et al., 2004; Sampaio and Goncalves, 2008) data show an average of less than one genotype recovered from each bark and soil sample; in addition our unpublished laboratory observations indicate that natural isolates of S. cerevisiae and S. paradoxus sporulate even on rich media. It may be that S. cerevisiae exists primarily in such niches as spores, and rare asci residing in nutrient poor soil and bark are disrupted during the sampling process: rare spores on isolation media will germinate and likely haplo-self to yield homozygous genotypes and mean an inference of low out-crossing rates. Overall, these data have prompted us to suggest an alternate model for S. cerevisiae’s biology: on large scales S. cerevisiae may be dispersed by humans in oak barrels but on smaller scales spores/cells are dispersed from the diffuse reservoir surrounding ephemeral fruits (bark and soil) by insects to fruits as they come into season. It is worth noting that a recent study shows that Drosophila ingestion increases asci disruption and therefore opportunities for out-crossing (Reuter et al., 2007). It seems humans have expanded the opportunities for S. cerevisiae to infect the fruit niche with large-scale vine plantings, and may also have short-circuited this life cycle by bringing oak (barrels) and fruit juice together directly. It is undeniable that humans and S. cerevisiae have been closely associated with one another for well over 5000 years (Cavalieri et al., 2003; McGovern et al., 2004). While commercial isolates of S. cerevisiae have been available for baking, brewing and winemaking applications for the last 30 years or so, it may be that the domesticated concept of strains generally associated with fermentation is unwarranted. It seems that S. cerevisiae was specialized to the fruit niche long before humans existed (Goddard, 2008): the whole genome duplication


S. cerevisiae’s population biology 71 event that largely provided an opportunity for yeasts to preferably ferment sugars occurred approximately 100 MYA (Merico et al., 2007). It has been suggested that the use of sulfur in winemaking, a practice that dates back at least to the Romans (Johnson, 1998), has increased the incidence of sulfur resistance among S. cerevisiae and therefore denotes they are domesticated (Aa et al., 2006). However, tests for neutrality on genes involved in sulfite tolerance do not indicate they have been subject to selection: Aa and colleagues (2006) explain this observation by proposing repeated migration of natural S. cerevisiae strains into the vineyard. This conforms precisely to our alternate hypothesis. It seems that humans have not truly domesticated yeasts, but that we simply harness the fortuitous side-effects of S. cerevisiae’s adaptation to invade high sugar niches and have unwittingly created novel lineages in doing so. Experimental procedures Microbiological methods We sampled four barrels containing Chardonnay juice at the Kumeu River Winery in Auckland every two days during the 2005 ferment (the details are described in Goddard, 2008). The grape juice for the second spontaneous ferment was derived from the University of Auckland’s research vineyard (Fossil Bay) on Waiheke Island and was fermented at the University’s Wine Science department (located on a separate campus). Approximately 5 g of Matua Valley vineyard soil, vine bark (Vitis vinifera var Sauvignon blanc) and buttercup (Ranunculus sp.) samples, as well as honeycomb from the BeesOnline apiary (Waimauku, Auckland), was taken with a sterile spatula and placed into a sterile container and transported to the laboratory on ice. We also sampled a new barrel sourced from the same cooper as the other barrels used at Kumeu River (Seguin Moreau, France). We sampled this outside of the ferment season: immediately upon opening for the first time 5 l of sterile water was poured in, agitated for 10 min, and then poured back into the original sterile container. SelMed media (1% yeast extract, 2% peptone, 10% glucose and ethanol to a final concentration of 5% added after autoclaving) was added to the barrel, Matua and apiary samples and these were incubated at 28°C for 10 days. A sample of this culture was transferred to a second SelMed flask and, after a second 5-day incubation step, serial dilutions plated. This selection procedure is able to recover S. cerevisiae efficiently from mixed laboratory communities even when at an initial frequency of only one in 10 million (Serjeant et al., 2008). Juice samples, and populations derived from the SelMed procedure, were plated onto YPD (1% yeast extract, 2% peptone, 10% glucose) and allowed to form colonies. Around 100 candidate colonies were selected from each sample and subjected to molecular analyses.

Molecular methods In order to identify isolates to species level, the Internal Transcribed spacer region (ITS) of all candidate colonies was

amplified and analysed by RFLP and direct sequencing as described in Goddard (2008). For those isolates that proved to be S. cerevisiae we scored repeat length at nine variable microsatellite loci as described in Richards and colleagues (2009); note, the data described here do not include analyses of the YOR267C locus. These nine loci are unlinked and strain differentiation using these loci significantly correlates with the relationships ascertained by whole genome sequencing (Richards et al., 2009). The allelic diversity among these loci provides a high degree of discriminatory power among S. cerevisiae isolates, but is less robust at deciphering deeper relationships. Sizes were binned to the nearest whole number for the microsatellite allele length data, and in general the microsatellite repeat number was consistent with predictions from repeat sizes, but representatives for loci of spurious size classes were sequenced, and their sizes confirmed.

Data analyses The microsatellite data were initially analyzed using GenAIEx (Peakall and Smouse, 2006) to elucidate matching genotypes, generate distance matrices and for export into formats appropriate for other software. Population genetic analyses were conducted with Arlequin (Excoffier et al., 2005) (with data coded as MICROSAT) with both Fst and Rst like analyses for AMOVA. Population structure tests were conducted in GeneClass2 (Piry et al., 2004), Structure (Falush et al., 2003) and Structurama (Huelsenbeck and Andolfatto, 2007). One million MCMC cycles (burnin = 50 000) were used to estimate posterior probabilities for population number and strain assignments. For Structurama the prior number of populations was drawn from a Dirichlet probability distribution, and the inferred number of populations for each data partition was then used to set K in Structure where the admixed with correlated allele frequency model was used and the results were visualized using Distruct 1.1 (Rosenberg, 2004). Distance matrices were constructed using GeneAIex using the codom-genotypic option, and SplitsTree (Huson and Bryant, 2006) was used to generate networks from these distances. For the out-crossing rate estimates (t in Table 1), we followed Johnson and colleagues (2004) and used a model that accounts for the fact that the yeast mating system loses one-third of heterozygotes each generation when mating within the ascus and where diploids are formed from either random or intra-ascus matings (Mathematica code available on request).

Acknowledgements We thank Michael Brajkovich for access to the Kumeu River estate and winery and suggesting that we sample barrels; Matua Valley vineyard and BeesOnline for access to their properties for sampling purposes. We also thank Bakir Al-Sinawi, Keith Richards, Jeremy Gray and Randy Weaver for technical assistance, and David Bryant for access to developmental versions of SplitsTree. This work was supported by research grants to M.G. by the University of Auckland and to M.G. and R.G. by NZ Winegrowers and the New Zealand Foundation for Research, Science and Technology (contact UOAX0404).


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