Microsatellite marker-based assessment of the biodiversity of native bioethanol yeast strains

Authors

  • Ana Teresa B. F. Antonangelo,

    1. Laboratório de Pesquisas e Análises Genéticas (PANGENE), Depto de Parasitologia, IBB-UNESP, Botucatu, SP, Brazil
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  • Diego P. Alonso,

    1. Laboratório de Pesquisas e Análises Genéticas (PANGENE), Depto de Parasitologia, IBB-UNESP, Botucatu, SP, Brazil
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  • Paulo E. M. Ribolla,

    1. Laboratório de Pesquisas e Análises Genéticas (PANGENE), Depto de Parasitologia, IBB-UNESP, Botucatu, SP, Brazil
    2. Programa de Pós-graduação em Genética, IBB-UNESP, Botucatu, SP, Brazil
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  • Débora Colombi

    Corresponding author
    1. Programa de Pós-graduação em Genética, IBB-UNESP, Botucatu, SP, Brazil
    • Genotyping Biotecnologia, Botucatu, SP, Brazil
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Correspondence to: D. Colombi, Genotyping Biotecnologia, Prospecta Incubadora Tecnológica Fazenda Lageado, Botucatu, SP, Brazil.

E-mail: debora@genotyping.com.br

Abstract

Although many Brazilian sugar mills initiate the fermentation process by inoculating selected commercial Saccharomyces cerevisiae strains, the unsterile conditions of the industrial sugar cane ethanol fermentation process permit the constant entry of native yeast strains. Certain of those native strains are better adapted and tend to predominate over the initial strain, which may cause problems during fermentation. In the industrial fermentation process, yeast cells are often exposed to stressful environmental conditions, including prolonged cell recycling, ethanol toxicity and osmotic, oxidative or temperature stress. Little is known about these S. cerevisiae strains, although recent studies have demonstrated that heterogeneous genome architecture is exhibited by some selected well-adapted Brazilian indigenous yeast strains that display high performance in bioethanol fermentation. In this study, 11 microsatellite markers were used to assess the genetic diversity and population structure of the native autochthonous S. cerevisiae strains in various Brazilian sugar mills. The resulting multilocus data were used to build a similarity-based phenetic tree and to perform a Bayesian population structure analysis. The tree revealed the presence of great genetic diversity among the strains, which were arranged according to the place of origin and the collection year. The population structure analysis revealed genotypic differences among populations; in certain populations, these genotypic differences are combined to yield notably genotypically diverse individuals. The high yeast diversity observed among native S. cerevisiae strains provides new insights on the use of autochthonous high-fitness strains with industrial characteristics as starter cultures at bioethanol plants. Copyright © 2013 John Wiley & Sons, Ltd.

Introduction

In Brazilian industrial ethanol production processes, fermentation is conducted in very large tanks with high yeast cell densities. The fermentation must is composed of the yeast inoculum and either sugarcane juice, water-diluted molasses (a thick syrup that is a byproduct of sugar industry), or a mixture of both (Amorim et al., 2011). At the end of the fermentation cycle, which occurs over a period of 6-12 h, the yeast cells are returned to the fermentation tanks to begin a new cycle (Basso et al., 2008). Although this cell recycling offers particular advantages to Brazilian production processes by ensuring the best ethanol yield (Amorim et al. 2011), it also causes great stress on the yeast cells (Basso et al., 2008, 2011; Argueso et al., 2009).

The industrial process of bioethanol production is conducted under unsterile conditions that permit the influx of contaminating microorganisms, such as bacteria and indigenous yeast strains, the better adapted of which tend to predominate and usually outnumber the Saccharomyces cerevisiae population inoculated as the starter culture (Silva Filho et al., 2005b; Basso et al., 2008). These indigenous yeast strains can sometimes cause serious problems to the industrial process, including yield reduction, increased fermentation time and operational problems (Cabrini and Gallo, 1999). However, some highly productive native yeast strains that dominate the fermenter during the entire production season do permit efficient and stable fermentations and therefore could be suitable for initiating the industrial process in the subsequent harvest season (Stambuck et al., 2009). There has been a recent effort to identify long-lasting strains with high fermentation efficiency among indigenous strains, leading to the identification of the PE-2, BG-1, SA-1 and CAT-1 strains, which have been used as inocula in many Brazilian ethanol plants (Silva Filho et al., 2005a; Basso et al., 2008; Stambuck et al., 2009; Amorim et al., 2011; Andrietta et al., 2011).

Although recent studies have demonstrated that PE-2 and CAT-1 strains contain a highly heterogeneous genome (Argueso et al., 2009; Stambuck et al., 2009), further investigations are necessary to evaluate the genome complexity of other native strains. Proper strain identification of S. cerevisiae is a prerequisite to studying the diversity of this species and to monitoring population dynamics during the fermentation process (Ayoub et al., 2006). Many methods, such as chromosome karyotyping (Vezinhet et al., 1990; Kishimoto et al., 1994), mitochondrial DNA polymorphism (Querol et al., 1992; López et al., 2001; Santamaría et al., 2005), random amplified polymorphic DNA (RAPD) (Lavallée et al., 1994; Pérez et al., 2001), genomic and mitochondrial DNA restriction fragment length polymorphism (RFLP) (Querol et al., 1992), amplified fragment length polymorphism (AFLP) (de Barros Lopes et al., 1998), ITS region amplification (Cappello et al., 2004) and microsatellite markers (Gallego et al., 1998; Field and Wills, 1998; González-Techera et al., 2001; Hennequin et al., 2001; Howell et al., 2004; Legras et al., 2005; Masneuf-Pomarède et al., 2007), have been used for such purposes with varying success.

The PCR microsatellite method is capable of discriminating strains, even when closely related strains are compared (Ayoub et al., 2006; Jubany et al., 2008). Given its reliability for S. cerevisiae strain identification (González-Techera et al., 2001; Legras et al., 2005), the PCR microsatellite method has been widely and successfully used for assessing wine fermentation populations (González-Techera et al., 2001; Masneuf-Pomarède et al., 2007; Vaudano and Garcia-Moruno, 2008). In the present study, 11 microsatellite loci were evaluated to investigate the genetic diversity and population structure of native S. cerevisiae yeast strains that are present in industrial cachaça and bioethanol production processes in the liquor industry and various Brazilian sugar mills, respectively. The majority of the investigated industrial plants were located in São Paulo State.

Materials and methods

Yeast strains

The following commercial strains were used: bioethanol selected Saccharomyces cerevisiae strains BG-1, CAT-1, PE-2 and SA-1; the grape wine strain CK; the bread-making strain Itaiquara; and the beer strain SO4. Native strains isolated from many Brazilian ethanol plants, the laboratory strain W303 α/a and a S. cerevisiae strain isolated from a human were also used. Table 1 shows the complete list of strains used in this study and their respective origins.

Table 1. Saccharomyces cerevisiae strains analysed by microsatellite markers with number, name of identification, class, season, geographic origin and collection. The last column refers to the designated populations for the study of their diversity and genetic structure
Strain number/nameClassOrigin (collection season)CollectionPopulations
(B) BG-1BioethanolCommercial selected strainSão Manoel Sugar Mill, São Manuel, SP 
(C) CAT-2
(S) SA-1
(P) PE-2
1. VF8 (6)NativeSão João Sugar Mill, Araras, SPProf. Sandra Regina Ceccato Antonini, UFSCar, Araras, SP 
2. M1. 1NativeMuller Industry, Pirassununga, SP (2011)Genotyping Biotechnology, Botucatu, SP 
3. M.9.1
4. M.14. 1
5. RP. 10.1NativeRio Pardo Sugar Mill, Avaré, SP (2010)Genotyping Biotechnology, Botucatu, SPPOP-1
6. RP. 10.2
7. RP. 10.3
8. RP. 10.4
9. RP. 10.6
10. RP. 10.8
11. RP. 10.12
12. RP. 10.13
13. RP. 10.14
14. SM. 9.1.AL1NativeSão Manoel sugar mill, São Manuel, SP (2009)Strains isolated during this studyPOP-3
15. SM. 9.1.AL2
16. SM. 9.1.AL3
17. SM. 9.1.BL4
18. SM.9.1.BL7
19. SM. 9.2.BL4
20. SM. 9.2.BR3(L)
21. SM. 9.2.BR5
22. SM.9.3.BL4
23. SM.9.3.BL5
24. SM.9.4.AL1
25. SM.9.4.BL2
26. SM.9.4.BL3
27. SM.9.4.BL4
28. SM.9.4.BL5
29. SM.9.4.LBA1
30. SM.9.4.BR1
31. SM.9.4.BR2
32. SM.8.2.C8NativeSão Manoel sugar mill, São Manuel, SP (2008)Strains isolated during this studyPOP-2
33. SM.8.2.C11
34. SM.8.2.C13
35. SM.8.2.L12
36. SM.8.3.mtBL1
37. SM.8.3.M4
38. SM.8.3.M5
39. SM.8.3.M6
40. SM.8.3.M9
41. SM.8.7.L7
42. SM.8.7.L8NativeSão Manoel sugar mill, São Manuel, SP (2008)Strains isolated during this studyPOP-2
43. SM.8.7.L9
44. SM.8.7.BR1
45. SM.8.7.ctBL1
46. SM.8.7.ctBR1
47. SM.8.8.BL1
48. SM.8.8.CVR1
49. SA.1.5.NativeSanta Adélia sugar mill, Jaboticabal, SP (2009)Strains isolated during this studyPOP-4
50. SA.9.2.BL3
51. SA.9.2.BR4
52. SA.9.3.BR2
53. SA.9.3.VR1
54. SA.9.4.VL4
55. SA.9.4.BR2
56. SA.10.1.VL1NativeSanta Adélia sugar mill, Jaboticabal, SP (2010)Strains isolated during this studyPOP-5
57. SA.10.1.VL8
58. SA.10.1.VR4
59. SA.10.1.CVL1
60. RP11.4.1NativeRio Pardo sugar mill, Avaré, SP (2011)Genotyping Biotechnology, Botucatu, SPPOP-6
61. RP11.4.5
62. RP11.4.11
63. RP11.4.14
64. P1NativeSugar mills located in north-east BrazilProf. Mario de Moraes Jr, Federal University of Pernambuco, Recife, PE. (Silva Filho et al., 2005a, 2005b)POP-7
65. P1a
66. P6
67. P25
68. JP1
69. CTC 001NativeN.S. Aparecida sugar mill, Itapira, SPSugarcane Technology Centre (Centro de Tecnologia Canavieira) CTC, Piracicaba, SP 
70. CTC 002
71. CTC 003NativeCoruripe sugar mill, Coruripe, AL
72. CTC 005
73. CTC 007NativeDa Serra sugar mill, Ibaté, SP
74. CTC 008
75. CTC 013NativeMaringá sugar mill, Araraquara, SP
76. CTC 016NativeEquipav sugar mill, Promissão, SP
79. W303LaboratoryRelated to the laboratory S288c strainProf. Mario Henrique Barros, University of São Paulo USP, São Paulo, SP 
83. ItaiquaraBread strainCommercial strainAcquired in local stores 
84. CKGrape wine strainCommercial strainProf. Maria Bordin Bonfim, Paraná State University, Curitiba, SP 
85. SO4Beer strainCommercial strainAcquired in local stores 
86. Sc human isolateNativeClinical exudate (skin) from Botucatu, SPProf. Eduardo Bagagli, IBB-Unesp, Botucatu, SP 

Yeast growth conditions and colony isolation

Samples of 50 ml crude sugar cane juice, must or wine were periodically collected from various ethanol plants (see Supporting information S1) in sterile flasks during the harvesting seasons in 2008, 2009, 2010 and 2011. Must samples were diluted to 1 × 10–6 and 1 × 10–7 and, in order to morphologically differentiate the colonies, 100 µl was plated onto WL Nutrient Medium (Acumedia, USA) containing nalidixic acid and ampicillin, both at 50 mg/l. After incubation for 72 h at 28 °C, 15 individual colonies were selected from the plates, evaluated for morphological characteristics such as border shape, colony surface aspect and dye assimilation, and selected for DNA extraction. A list describing the morphological characteristics of the isolated strains used in this study is included as Supporting information S2. All isolated strains were spread onto YPD agar media plates (1% w/v yeast extract, 2% w/v peptone, 2% w/v glucose, 2% w/v agar) and incubated for 16–48 h at 30 °C. The strains were stored in YPD broth containing 15% glycerol at –80 °C.

DNA preparation

DNA was isolated from yeast as follows: a yeast colony was transferred with a plastic tip directly from a YPD agar plate to a microtube containing 300 µl Chelex® Grade Molecular Biology Resin 5% (Bio-Rad Laboratories, USA), which had been prepared according to the manufacturer's directions. Samples were vortexed for 15 s, centrifuged at 4000 × g for 15 s and incubated for 20 min at 60 °C in a thermoblock Thermomixer Compact (Eppendorf, Germany). The samples were then vortexed for 15 s and centrifuged at 4000 × g for 1 min. Each supernatant was transferred to a new microtube, which was stored at –20 °C.

rDNA ITS PCR conditions

PCR was performed to amplify the rDNA internal transcribed spacer (ITS) region from each yeast colony. Each reaction had a final volume of 20 µl and was composed of 4 µl prepared DNA (described above), 10 µl GoTaq® Green Master Mix 2× (Promega, USA), 1 µm ITS1 (5′-TCCGTAGGTGAACCTGCGG-3′) or ITS5 (5′-GGAAGTAAAAGTCGTAACAAGG-3′) as the forward primer and 1 µm ITS4 (5′-TCCTCCGCTTATTGATATGC-3′) as the reverse primer (White et al., 1990), and a sufficient quantity (qs) of sterile deionized water. Amplification was performed in a TGradient Thermal Cycler (USA) as follows: 5 min at 94 °C; 34 cycles of 45 s at 94 °C, 30 s at 60 °C and 60 s at 72 °C; and a final step of 5 min at 72 °C. The amplified products were analysed by 1% w/v agarose gel electrophoresis in 1× TAE buffer stained with 0.1% v/v Gel Red (Biotium, CA, USA). Electrophoretic separation was performed at 6 V/cm for 60 min and the resulting DNA patterns were visualized under UV light. A 100 bp DNA Ladder (Ludwig Biotec, Brazil) was used as a molecular weight marker.

Microsatellite PCR conditions

The PCR reactions had a final volume of 20 µl and contained 4 µl of the prepared DNA, 10 µl GoTaq® Master Mix Colorless 2× (Promega, USA), 1 µm of each forward and reverse primer specific for each locus (supplied by Genotyping Biotechnology; see Supporting information S3), and deionized water qs. Amplification was performed as follows: 5 min at 94 °C; 14 cycles of 15 s at 94 °C, 30 s at 60 °C (decreasing 1 °C/cycle up to 47 °C) and 30 s at 72 °C; 25 cycles of 15 s at 94 °C, 30 s at 48 °C and 30 s at 72 °C; and a final step of 5 min at 72 °C. The amplified products were analysed by capillary electrophoresis as described below.

Capillary electrophoresis

Microsatellite PCR products were analysed on the QIAxcel system (Qiagen, Germany), using the QIAxcel DNA Screening Kit and QX Alignment Marker 15 bp/5000 bp. Separation was performed with a 6 kV voltage with a 20 s injection time and a 320 s separation time. The length of the product was determined by comparison with the QX DNA Size Marker 100 bp–3 kb. Data were analysed using QIAxcel Screengel software.

Diversity population analysis

Microsatellite PCR amplifications of 86 S. cerevisiae strains were used to create phenetic trees, using Population 1.2.30 software, the algorithm Minimum Genetic Distance (Dm) (Nei, 1987) for the distance method and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) as the clustering method. Eleven trees were constructed, using the strategy of removing one locus at a time and then, using PHYLIP 3.69 Phylogeny Inference Package, a consensus tree was also constructed.

Population structure analysis

To study the yeast population diversity and genetic structure present in the industrial fermentation process of various plants, the strains were clustered into seven populations according to the place of origin and collection season, as shown in Table 1.

Microsatellite data were analysed using Arleqin 3.1 (Excoffier et al., 2007). This software was used to compute FST values (Wright, 1951; Weir and Cockerham, 1984) and determine significance by permutating genotypes among populations (1000 permutations).

STRUCTURE 2.3.2.1 (Pritchard et al., 2000) was used to assign individuals from all populations to a predetermined number of clusters (K), based on multilocus microsatellite data. Cluster analysis was performed with previous information about geographic collection site (Locprior model) and with admixture option, i.e. the assumption of correlated allele frequencies among populations. For each run, a burn-in period of 50 000 steps was followed by 1 × 104 iterations. For each K of 1–14, five runs were performed. Estimated log probabilities [Ln P(D)] were averaged across runs and compared to determine the posterior probability of each K.

Results and discussion

To study the yeast population diversity present in alcohol and cachaça industrial production processes in various Brazilian industries, morphologically distinct colonies were isolated from wine, must, crude sugar cane juice and molasses. Isolated yeast colonies were screened between Saccharomyces and non-Saccharomyces species through rDNA ITS region amplification (data not shown). The PCR-generated fragment contained the rRNA 5.8 s gene and the internal transcribed spacers 1 and 2 (ITS1 and ITS2). The ITS regions and rRNA 5.8 s gene can be used to predict Saccharomyces species classification (Esteve-Zarzoso et al., 1999; Valente et al., 1996; Arlorio et al., 1999). Samples that did not present the expected 800 bp fragment size (about 13%) were excluded from the analysis. A total of 138 of 160 strains yielded an amplicon length compatible with that of S. cerevisiae . All samples were sequenced to confirm the data.

The Saccharomyces strains were subsequently evaluated with the most discriminating microsatellite markers, G1, G4 and G9, to select those that were different from the commercial ethanol strains and to avoid redundant patterns. A total of 77 strains displayed a unique pattern, and in those strains other microsatellite loci (G2, G3, G5, G6, G7, G8, G10 and G11) were then evaluated. Table 1 shows all strains evaluated by 11 microsatellite markers: G1, G2, G3, G4, G5, G6, G7, G8, G9, G10 and G11 (the banding pattern of these locus amplifications in the bioethanol commercial and some native strains is available as Supporting information S4a, b).

Each of these loci demonstrated a range of alleles varying between 8 and 16. The loci G2 and G4 were the most polymorphic, with 16 and 15 alleles, respectively. The G7 and G8 loci were the least polymorphic, with only eight alleles. The loci G9 and G10 both presented nine alleles, while G6 and G3 presented 10 and 12 alleles, respectively. The G1, G5 and G11 loci all presented 13 alleles. The phenotypes of these alleles in native strains were mostly heterozygous (see Supporting information S5), as observed by Richards et al. (2009) for wild, natural and commercial wine strains. Argueso et al. (2009) and Babrzadeh et al. (2012) demonstrated that the genomes from the diploid JAY270 (PE2) and CAT-1 strains, respectively, are highly heterozygous when compared with the reference S288c strain, which may be responsible for the fitness of these commercial strains (Argueso et al., 2009). The number of heterozygotic alleles found in these native strains was, in the majority, either greater than or equal to the number found for PE-2 and CAT-1 (see Supporting information S5).

These microsatellite loci were capable of differentiating between the autochthonous yeast strains and the inoculated population and, furthermore, could discriminate the commercial strains from each other. All markers used could also differentiate native strains 2, 3 and 4 (Table 1) isolated from cachaça must, although Oliveira et al. (2008) reported that some of the microsatellite markers failed to discriminate selected cachaça strains.

Analysis of yeast population diversity

The data from the amplification of the 11 loci from 86 strains were first used to build a UPGMA phenetic tree. Next, in order to test the robustness of the clusters, a resampling strategy was employed by removing one locus at a time. Finally, a consensus tree was generated, using PHYLIP 3.69 Phylogeny Inference Package (Figure 1). The commercial ethanol strains BG-1 and SA-1 were isolated in two independent branches. All the other strains were in the same major group, including the commercial ethanol strains CAT-1 and PE-2.

Figure 1.

Consensus tree plot of phenetic similarity of 86 S. cerevisiae strains analysed by 11 microsatellite markers. The 86 yeast strains analysed included seven commercial Saccharomyces cerevisiae strains: four selected ethanol (BG-1, CAT-1, PE-2 and SA-1); one bread-making (83); one wine (84); and one beer (85). A laboratory W303 (79) and a clinically isolated strains (86) were also analysed. The remaining strains were 77 autochthonous strains isolated from the following sources: São João sugar mill, Araras (1); Muller Industry (2–4); Rio Pardo sugar mill in 2010 (5–13) and 2011 (61–64); São Manuel sugar mill in 2009 (14–31) and 2008 (32–48); Santa Adélia sugar mill in 2009 (49–56) and 2010 (57–60); Pernambuco sugar mills (65–69); and five plants collected by CTC (70–77). The consensus tree was built using the Phylip 3.69 Phylogenetic Package

Interestingly, a slight tendency of arrangement in accordance with the place and season in which the native strains were collected was observed. For example, this could be seen in some strains isolated in São Manoel sugar mill in 2008 (37, 36, 39, 46, 47 and 44); in 2009 (17, 20, 19, 21, 27, 15, 16 and 23, 26, 25); and some isolated in Rio Pardo sugar mill in 2010 (8, 7, 11, 10, 9) (Figure 1).

The proximity of the strains collected in one place can be attributed to the existence of a local flora. Ecological studies on the distribution of yeasts have demonstrated that some strains of S. cerevisiae can persist for years in the same area (Sabate et al., 1998) and in the same winery (Blanco et al., 2006).

Yeast population structure

Microsatellite data of 52 native strains arranged in four populations designated by Pop-1, Pop-2, Pop-3 and Pop-4 (Table 1) were used to calculate the allele fixation index (FST) of the populations. Some populations (Pop-5, Pop-6 and Pop-7) were excluded from the analysis because of their small number of individuals. The FST measures the amount of genetic variance that can be explained by population structure. The FST average ranged from +0.13121 (São Manoel sugar mill 2009, compared to Rio Pardo sugar mill population 2010) to –0.00330 (São Manoel sugar mill 2008, compared to Rio Pardo sugar mill population 2010; Table 2). These results revealed a genetic differentiation of approximately 13% between the native population isolated from the São Manoel sugar mill in 2009 and the one isolated from the Rio Pardo sugar mill in 2010. The low FST value among the native populations isolated in São Manoel sugar mill in 2009 and Santa Adélia sugar mill in 2009 indicates that these populations were not significantly differentiated, which suggests that sufficient gene-flow between these two distant sites (~95.31 miles apart; see Supporting information S1) maintains the genetic homogeneity of the two populations.

Table 2. Matrix of genetic differentiation (FST pairwise) among four S. cerevisiae populations calculated using the F statistic method by Arleqin software v. 3.1.1
 Pop-1Pop-2Pop-3
 Rio Pardo sugar mill (2010)São Manoel sugar mill (2008)São Manoel sugar mill (2009)
  • * FST values are the significant values of FST pairwise between populations (p ≤ 0.05).
Pop-1
Rio Pardo sugar mill (2010)  
Pop-2   
São Manoel sugar mill (2008)0.05455* 
Pop-3
São Manoel sugar mill (2009)0.13121*0.02119
Pop-4
Santa Adélia sugar mill (2009)0.04511–0.003300.04000

An analysis of the genetic structure of the seven populations (see Table 1) was performed using the software STRUCTURE v. 2.3.3 (Pritchard et al., 2000), which implements a Bayesian model-based clustering algorithm that attempts to identify genetically distinct subpopulations on the basis of patterns of allele frequencies. Each strain is represented by a single vertical bar, which is fractionated into coloured segments (K) that represent the estimated probability of the strain belonging to one of the genetic clusters. After all computations, the most probable K value was K = 6. A graph was constructed to facilitate the choice of the most probable K value (see Supporting information S6). Bar graphs were constructed by attributing K values (ranging from two to six different genetic clusters) to each strain (see Supporting information S7). This figure shows that some of the native strain populations studied either belong to one ancestral lineage or are the result of admixture (see Supporting information S7).

Figure 2 depicts the result of the Bayesian analysis; each bar represents an isolated strain, and each colour (K) represents an assigned cluster genotype, considering K = 6. The population isolated from the Rio Pardo sugar mill in 2010 (1) exhibits great genotypic variation when compared to the population isolated in 2011 (6), although the individual variation within both populations seems to be low.

Figure 2.

Bayesian population structure analysis, indicating the presence of six population clusters. Bar graph of highest log likelihood STRUCTURE run at K = 6. Strains are grouped by both the year and the collection sugar mill sites from which the populations were isolated: 1, Rio Pardo in 2010 (strains 5–13); 2, São Manoel in 2008 (strains 32–48 ); 3, São Manoel in 2009 (strains 14–31); 4, Santa Adélia in 2009 (strains 49–56); 5, Santa Adélia in 2010 (strains 57–60); 6, Rio Pardo in 2011 (strains 61–64); and 7, Pernambuco (strains 65–69). Each of the 65 autochthonous S. cerevisiae strains analysed is represented by a vertical bar displaying membership coefficients for each of the six clusters, which are coloured in red, green, yellow, blue, pink and turquoise

There is great genotypic difference between the population isolated from the São Manoel sugar mill in 2008 (2) and that isolated in 2009 (3). The population from 2008 comprises 17 strains: three from raw sugar cane juice (32, 33 and 34); four from molasses (37, 38, 39 and 40); one from must (36); and eight from fermented must, which is called wine (35 and 41–48) (Figure 2). Strains 37 and 38 are genotypically similar to strain 36 isolated from must. Strains 41 and 42, which were isolated from wine at the end of the season, have the same genotype as strain 33, which was isolated from sugar cane juice. The genotypes of strains isolated from juice (34) and wine (43) are also the same, suggesting the permanence of these yeasts from the raw material until the end of fermentation. The remaining strains from the wine, with the exception of strain 35, which comes from the beginning of the season, exhibit genotypic patterns that are similar to each other but different from the rest of the population. These similar genotypes seem to occur in samples collected at the same time or within a short period of time. This same pattern of genotypic similarity within a population is observed in the population from the São Manoel sugar mill in 2009 (3), which comprises 18 strains isolated from the first four months of the season: 14–18 (first collection), 19, 20 and 21 (second collection) and 22–31 (third and fourth collections).

Among the strains in Santa Adélia sugar mill population, the genotypic pattern observed in 2009 (4) was notably different from that of 2010 (5). In these two populations, a higher number of genetic fractions are found. Moreover, it can be observed that within each one of these two populations, the strains basically share the same admixture of genotypic fraction, although in different proportions. Finally, the strains from Pernambuco's population (7) exhibit few admixtures.

Conclusions

The 11 microsatellite loci used in this work were capable of detecting the high genetic diversity among the indigenous strains, which is related to the industry location and season. The wide yeast diversity found among indigenous S. cerevisiae suggests a possible inclusion of desirable autochthonous strains as starters at bioethanol plants, since nowadays in Brazil there are just five commercialized bioethanol industrial strains which do not represent the natural diversity found. To the best of our knowledge, this is the first time that microsatellite PCR has been applied as a marker to differentiate yeast strains present in sugar cane fermentation during ethanol industrial production in Brazil, where karyotyping is currently considered the gold standard method for monitoring the process.

This study revealed that a fascinating genetic diversity of strains can be present in fermentation tanks and that those autochthonous native strains that have industrially desired characteristics, such as highest rates of dominance and persistence in the fermentation process, could be considered as starter strain inocula. Further studies are necessary in order to evaluate characteristics such as cell viability and tolerance to alcohol, temperature and osmolarity.

Acknowledgements

We are grateful to our research colleagues who supplied us with yeast strains for this work: Eduardo Bagagli, Marco Antonio de Castro e Souza, Marcos de Morais Junior, Mário Henrique Barros, Sandra Regina Ceccato Antonini and Tania Maria Bordin Bonfim. We are also grateful to alcohol plant managers and microbiologists who either sent samples or allowed us to collect samples from their sugar mills: Carlos Dinucci, Miriam Roberta Henrique (São Manoel S/A sugar mill) and Maria Angélica Garcia (Santa Adélia S/A sugar mill). Finally, we would like to thank Miriam Roberta Henrique, who supplied us with the LNF commercial ethanol strains, and Genotyping Biotechnology, which provided the microsatellite primers and some yeast samples. This study was supported by CNPq, FAPESP and FINEP.

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