Application of different markers and data-analysis tools to the examination of biodiversity can lead to different results: a case study with Starmerella bacillaris (synonym Candida zemplinina) strains

Application of different markers and data-analysis tools to the examination of biodiversity can... Abstract Starmerella bacillaris (Candida zemplinina) is a genetically heterogeneous species. In this work, the diversity of 41 strains of various origins is examined and compared by the analysis of the length polymorphism of nuclear microsatellites and the RFLP of mitochondrial genomes. The band patterns are analysed with UPGMA, neighbor joining, neighbor net, minimum spanning tree and non-metric MDS algorithms. The results and their comparison to previous analyses demonstrate that different markers and different clustering methods can result in very different groupings of the same strains. The observed differences between the topologies of the dendrograms also indicate that the positions of the strains do not necessarily reflect their real genetic relationships and origins. The possibilities that the differences might be partially due to different sensitivity of the markers to environmental factors (selection pressure) and partially to the different grouping criteria of the algorithms are also discussed. Candida zemplinina, mtDNA, microsatellite markers, strain biodiversity, RFLP-mtDNA INTRODUCTION Candida zemplinina (recently merged with the former species Saccharomyces bacillaris and Torulopsis bacillaris under the new taxonomic name Starmerella bacillaris) long considered conspecific with C. stellata is a wine-associated yeast species (Csoma and Sipicki 2008), frequently isolated from grapes and fermenting wines. Next to Saccharomyces, C. zemplinina is quantitatively one of the most important yeasts in the fermentation of botrytised grape musts and has been detected in many wine-growing regions of the world (e.g. Mills, Johannsen and Cocolin 2002; Nisiotou and Nychas 2007; Csoma and Sipiczki 2008; Urso et al.2008; Li et al.2010; Zanol, Baleiras-Couto and Duarte 2010; Zott et al.2010; Di Maio et al.2012; Gayevskiy and Goddard 2012; Tofalo et al.2012; Masneuf-Pomarede et al.2015). It is a very promising non-Saccharomyces yeast which could be potentially used in winemaking as co-starter with S. cerevisiae strains (e.g. Andorrá et al.2010; Comitini et al.2011; Di Maio et al.2012; Rantsiou et al.2012; Sadoudi et al.2012; Giaramida et al.2013; Englezos et al.2015). Its strains can have beneficial effects on the wine due to certain favourable properties such as osmo- and psychrotolerance, fructophily, high glycerol yield and a relatively low acetaldehyde, volatile acid and sulphur dioxide production and the ability to degrade malic acid (e.g. Mills, Johansen and Cocolin 2002; Sipiczki 2003, 2004; Tofalo et al. 2009, 2012; Magyar and Tóth 2011; Giaramida et al.2013; Magyar et al.2014; Pfliegler et al.2014; du Plessis et al.2017). Candida zemplinina is not associated exclusively with vineyards and wines because its strains have also occasionally be isolated from other substrates such as fermented cocoa in Ghana (Nielsen et al. 2005, 2007), soil in Italy (Csoma and Sipiczki 2008), Drosophila sp. in the USA (Phaff, Miller and Shifrine 1956; Stamps et al.2012), rotten water melon in Hungary and rotten banana in the Philippines (Csoma and Sipiczki 2008; Pfliegler et al.2014). Many authors examined the intraspecific genetic biodiversity of C. zemplinina strains. The molecular methods used were RAPD-PCR fingerprinting (Tofalo et al.2012; Pfliegler et al.2014), SAU-PCR (Englezos et al.2015), mtDNA-RFLP (Di Maio et al.2012), Fourier-transform infrared spectroscopy (Grangeteau et al.2016) and microsatlite analysis (e.g. Pfliegler et al.2014; Englezos et al.2015; Masneuf-Pomarede et al.2015). The different methods detected varying degrees of diversity. For example, Pfliegler et al. (2014) noticed a relatively low level of genetic intraspecific diversity with two types of genomic RAPD-PCR and two types of non-specific micro/minisatellite primers, whereas Masneuf-Pomarede et al. (2015) observed much higher diversity by analysing 10 species-specific microsatellite loci of the same strains in a more comprehensive analysis involving a large number of wine-related isolates of various geographical origins. The latter authors found that no specific genetic signatures could be associated with the different samples and vineyards/wineries, but the genetic diversity showed significant correlation with the geographical origin of the strains. Considerable intraspecies diversity was detected in the mitochondrial DNA as well. In a collection of 59 Sicilian isolates, 14 different RFLP patterns were distinguished (Di Maio et al.2012). In a collection of 44 mostly Greek isolates, the presence and structure of a group-IIB1 intron containing an ORF encoding a putative reverse transcriptase was examined (Pramateftaki et al.2008). Only a quarter of the strains had this intron, and their intron sequences differed in size and in the number and position of point mutations. The different extent of diversity detected in these studies does not necessary reflect real phylogenetic differences but might be attributed to the use of different markers and different bioinformatics tools in the different laboratories. In this paper, we report on the investigation of the diversity in a set of 41 C. zemplinina strains by comparing their nuclear microsatellites and mitochondrial genomes. For clustering the patterns, we used several algorithms and then compared the topologies of the dendrograms and the positions of strains of shared origins on them. Most strains examined in this study were included in previous diversity studies (Pfliegler et al.2014; Masneuf-Pomarede et al.2015), allowing thus a comparison of the results of our diversity analyses with those of previous works. The new strains were isolated from Drosophila larvae and flies in the Tokaj wine-growing region, Hungary. MATERIALS AND METHODS Yeast strains and media The 41 strains of C. zemplinina examined in this study (Table 1) were identified and described in previous works (Sipiczki 2003, 2004; Csoma and Sipiczki 2008; Pfliegler et al.2014 and references therein) or isolated from guts of Drosophila larvae and flies collected in Tokaj vineyards (Z. Kállai, unpublished). The ITS sequences of the latter strains are deposited in GenBank under the following accession numbers: 10–1496 (KT933399), 10–1539 (KT933400), 10–1541 (KT933401), 10–1544 (KT933402), 10–1529 (KT933403), 10–1573 (KT933404), 10–1562 (KT933405) and 10–1506 (KT933406). The strains were maintained at 25°C on YPGA (2% glucose, 2% agar, 1% yeast extract and 1% peptone; all w/v) or cultured in YPGL (YPGA without agar) for the extraction of mitochondrial and genomic DNA. Table 1. List of strains. Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) T: Type strain CBS: Centraalbureau voor Schimmelcultures, Delft, The Netherlands CECT: Colección Española de Cultivos Tipo, Valencia, Spain NCAIM: National Collection of Agricultural and Industrial Microorganisms, Budapest, Hungary RIVE: Research Institute of Viticulture and Enology, Bratislava, Slovakia Eszencia or Essence is a specific sweet dessert wine of high sugar content made from the juice of separately collected botrytised berries View Large Table 1. List of strains. Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) T: Type strain CBS: Centraalbureau voor Schimmelcultures, Delft, The Netherlands CECT: Colección Española de Cultivos Tipo, Valencia, Spain NCAIM: National Collection of Agricultural and Industrial Microorganisms, Budapest, Hungary RIVE: Research Institute of Viticulture and Enology, Bratislava, Slovakia Eszencia or Essence is a specific sweet dessert wine of high sugar content made from the juice of separately collected botrytised berries View Large Mitochondrial DNA extraction and restriction analysis The mitochondrial DNA (mtDNA) was extracted from cells of exponential-phase YPGL cultures according to the method described by Antunovics et al. (2005). This protocol allows isolation of the mitochondrial genome irrespective of the genomic DNA. The cell pellet was washed once in water and once in 50 mM EDTA. After this, the pellet was suspended in wash buffer [1.2 M Sorbitol, 50 mM Tris (pH 7.5), 50 mM EDTA, 2% b-mercaptoethanol] and incubated at 37°C for 10 min. The pellet was then resuspended in 1 ml solution A [0.5 M Sorbitol, 50 mM Tris (pH 7.5), 10 mM EDTA, 2% b-mercaptoethanol], to which 100 U Zymolyase 100T (MP Biomedicals) were added, and the cells were incubated at 37°C for 45 min under gentle horizontal shaking (400 rpm). The spheroplastes were then disrupted by sonication at middle energy level for 6 s. The suspension was then centrifuged at 2800 rpm for 10 min. The supernatant was transferred to a new 1.5-mL tube and centrifuged at 14 000 rpm for 10 min. The crude mitochondrial pellet was washed with 1 mL solution A and resuspended in 500 mL solution A supplemented with DNAse I (10 U) and 25 mM MgCl2. After 10 min of treatment at room temperature, it was centrifugated. To the mitochondrial pellet 0.5 mL solution B [100 mM NaCl, 10 mM EDTA, 50 mM Tris (pH 8)] and 1% sodium lauroyl sarcosine were added. After being suspended, the preparation was incubated at room temperature for 30 min to allow mitochondrial lysis. The mtDNA was then purified by phenol:chloroform:isoamyl alcohol (25:24:1) extraction followed by ethanol precipitation. The mtDNA pellet was dissolved in 50 mL TE buffer (10 mM Tris, 1 mM EDTA, pH 8). RNA was degraded by RNAse treatment at 37°C for 1 h. The isolated mtDNA was digested with EcoRI (Fermentas), EcoRV (Fermentas), DraI (Thermo Scientific), HinfI (Fermentas), MboI (Thermo Scientific), HaeIII (Fermentas) and HindIII (Promega) according to the instructions of the suppliers. The mtDNA fragments were loaded onto 1% and 1.4% (w/v) agarose gels containing ethidium-bromide, and electrophoresis was carried out in 1 × TBE buffer at 115 V for 70–120 min. A GeneRuler 1 kbp Plus DNA ladder marker (Thermo Scientific) served as size standard. After separation, the fragments were visualised and photographed. Microsatellite amplification Yeast cultures were grown at 25°C for 2 days in YPGL. Total genomic DNA was subsequently extracted from the cells using the protocol described in Hanna and Xiao (2006). The microsatellites were amplified in 50 μL reaction mixtures containing 100 ng of genomic DNA, 0.5 μL of DreamTaq® DNA Polymerase (500 U), 5 μL (10x) DreamTaq Green buffer (Thermo Scientific) and 40 pmol of CZ13, CZ11, CZ1, CZ15 or CZ4 primer pairs (Masneuf-Pomarede et al.2015). A LifeECO (Hangzhou Bioer Technology Co. Ltd) thermal cycler (3 min at 95°C; 30 cycles of 30 s at 95°C, 30 s at 54°C and 30 s at 72°C; 10 min at 72°C) was used. The amplicons were loaded onto 3% (w/v) agarose gels stained with ethidium-bromide and the electrophoresis was carried out in 1 x TBE buffer at 140 V for 80 min. A GeneRuler 20 bp DNA ladder marker (Thermo Scientific) was used as size standard. After visualisation of the amplicons, the gels were photographed. Data analyses The mtDNA and microsatellite patterns were analysed using the GelAnalyzer 2010 software (Lazar and Lazar 2010) with manual adjusting. Distances of the band patterns were calculated with the Dice's (Dice 1945) coefficient using the algorithm available at http://genomes.urv.es/UPGMA. The resulting distance matrices were subjected to cluster analysis by the unweighted pair group method with arithmetic averages (UPGMA) algorithm and by the neighbour joining (NJ) algorithm available in the PHYLIP package (Felsenstein 2007). In the case of microsatellites, dendrograms were built also from Bruvo distances (Bruvo et al.2004). For this, the numbers of repeats in the amplified fragments were determined using the method described by Masneuf-Pomarede et al. (2015). Dendrograms were visualised with the FigTree program (http://tree.bio.ed.ac.uk). The neighbor net analysis was carried out with SplitsTree4 V4.14.4 (Huson and Bryant 2006). Minimum spanning tree was constructed from the microsatellite data with the Tree and Network Inference module of the BioNumerics 7 software platform (http://www.applied-maths.com/bionumerics). Non-metric multidimensional (nMDS) analyses (Shepard 1962; Kruskal 1964) were performed with Past3 software (https://folk.uio.no/ohammer/past/) (Hammer, Harper and Ryan 2001) using the corresponding concatenated binary matrices of the strains. Bray-Curtis (Bray and Curtis 1957) was used as similarity coefficient and the dimensionality was adjusted to 3. RESULTS RFLP analysis of mitochondrial DNA To investigate the intraspecific variation present in the C. zemplinina mitochondrial genomes, we analysed the RFLP patterns of the mtDNA from a set of 41 C. zemplinina strains. Seven restriction endonucleases were used to digest the mtDNA of the strains. The digestion of the mtDNA produced reproducible mtDNA restriction profiles for each strain (examples are shown in Fig. S1, Supporting Information). The enzymes differed in the number and size range of the bands, allowing the differentiation of 7 to 27 patterns (Table 2). The size of the mitochondrial genomes calculated from the fragment sizes corresponded to the size of the sequenced genome (23 kbp) of the strain CECT 11046 (Pramateftaki et al.2008). Table 2. Fragments generated from the mtDNA of C. zemplinina strains by restriction endonuclease digestion. Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 View Large Table 2. Fragments generated from the mtDNA of C. zemplinina strains by restriction endonuclease digestion. Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 View Large The seven band patterns of each strain were converted to binary matrices which were then concatenated. The concatenated matrix contained 188 elements from which 170 were informative. The UPGMA and NJ dendrograms generated from the matrix had similar overall topologies (Fig. 1). The strains formed three well-separated clusters: two smaller but quite compact clusters and one larger, heterogeneous cluster. Cluster I harboured only Tokaj isolates. Cluster II was also dominated by isolates from Hungary; the two exceptions were a strain from Switzerland (11–19) and a strain from The Philippines (11–479). All but three strains (11–31, 11–159 and 11–479) of these clusters were isolated from wine-related habitats. The third cluster grouped strains of diverse origin and had different internal structures in the two types of dendrograms. Figure 1. View largeDownload slide Comparative dendrogram constructed with NJ and UPGMA clustering of the concatenated mtDNA-RFLP matrices. Strain 11–60 was used as outgroup. The first column of symbols shows the strain names (see Table 1). The second column shows the country of origin: C, Switzerland; E: Spain; F, France; H, Hungary; I, Italy; P, The Philippines; S, Slovakia; U, USA. The third column shows the region of origin: A, Andalucia; B, Badacsony; C, California; K, Biele Karpaty; M, Manila; S, Sardinia; T, Tokaj; W, Waedenswill. The fourth column shows the habitat (substrate) from which the strain was isolated: B, rotting banana; D, Drosophila; E, wine (Eszencia); F, fermenting wine; G, grape; J, grape juice; M, must; S, soil; W, wine; WM, watermelon. Roman numerals mark clusters. Figure 1. View largeDownload slide Comparative dendrogram constructed with NJ and UPGMA clustering of the concatenated mtDNA-RFLP matrices. Strain 11–60 was used as outgroup. The first column of symbols shows the strain names (see Table 1). The second column shows the country of origin: C, Switzerland; E: Spain; F, France; H, Hungary; I, Italy; P, The Philippines; S, Slovakia; U, USA. The third column shows the region of origin: A, Andalucia; B, Badacsony; C, California; K, Biele Karpaty; M, Manila; S, Sardinia; T, Tokaj; W, Waedenswill. The fourth column shows the habitat (substrate) from which the strain was isolated: B, rotting banana; D, Drosophila; E, wine (Eszencia); F, fermenting wine; G, grape; J, grape juice; M, must; S, soil; W, wine; WM, watermelon. Roman numerals mark clusters. Surprisingly, we obtained different RFLP patterns for certain strains isolated from the same wine, vineyard or vintage. The differences were sometimes so big that the analysis placed them on distant branches of the dendrograms. For example, the Tokaj strains isolated in Szegi (10–372 to10–377) were assigned to three clusters. In contrast, the majority of the strains isolated from Drosophila larvae and flies collected in the Bakonyi vineyard (Tarcal, Hungary) formed a quite compact group in Cluster III. However, even these isolates had representatives in the other two clusters. For example, 10–1496 had a pattern highly similar to those of the strains 1–88 and 11–24 (grape, Szarvas vineyard 2003) strains, whereas the mtDNA pattern of 10–1539 was similar to that of 11–159 (rotten watermelon, Hungary). The nMDS ordinations of the mtDNS RFLP profiles (Fig. 2) presented stress values of 0.05 indicating a confident representation with no prospect of misinterpretations (Clarke and Warwick 2001). The plots are ordinations of strains based on their relative similarities. The agreement between the Figs 1 and 2 is very good: the same clusters are sharply defined demonstrating that the two methods determined the clusters much the same way. Figure 2. View largeDownload slide Non-metric MDS configurations of the mtDNA RFLP patterns. The groups highlighted in Fig. 1 are marked with the same Roman numerals. Figure 2. View largeDownload slide Non-metric MDS configurations of the mtDNA RFLP patterns. The groups highlighted in Fig. 1 are marked with the same Roman numerals. Microsatellite analysis In order to compare the genetic relationships of strains obtained with mtDNA-RFLP analysis to those of the nuclear genomes, five species-specific microsatellite markers (CZ1, CZ4, CZ11, CZ13 and CZ15) described by Masneuf-Pomarede et al. (2015) were also examined. Interestingly, the fragments amplified from the type strain CBS 9494T (10–372T) slightly differed in size from those obtained previously by Masneuf-Pomarede et al. (2015) (Table 3). The fragments obtained from the other strains varied in the size range of 105–347 base pairs (Table 3). All strains were homozygous for the examined loci, except for 11–6 which was heterozygous for the locus CZ15. This result is in agreement with that observed by Masneuf-Pomarede et al. (2015). Table 3. Size diversity of the microsatellite loci of C. zemplinina strains. Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) aAllele size in bp. View Large Table 3. Size diversity of the microsatellite loci of C. zemplinina strains. Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) aAllele size in bp. View Large From the amplified fragments, a binary matrix was compiled for each microsatellite locus then the matrices of the same strain were concatenated. The concatenated matrices of the strains were used to generate a distance matrix. From the distance matrix UPGMA and NJ dendrograms were constructed. The dendrograms (Fig. S2, Supporting Information) showed marked topological differences and also differed from those deduced from the mtDNA analysis (Fig. 1). Here only two clusters could be distinguished and neither corresponded to any of the mtDNA clusters. As the microsatellite motifs differed in the size of their repeats (Masneuf-Pomarede et al.2015), we also performed clustering by analysing Bruvo distance values calculated from the repeat numbers of the amplicons (Fig. 3). Both the UPGMA and NJ dendrograms grouped the majority of strains into two clusters but the larger cluster was divided into two subclusters in the UPGMA dendrogram. The composition of these clusters only partially overlapped with the composition of the clusters of the dendrograms drawn from the length differences of the amplicons (Fig. S2, Supporting Information). For example, all but one grape strains isolated in Tarcal were assigned to Cluster B in Fig. S2 (Supporting Information), whereas they were represented equally in both clusters of the Bruvo-distance dendrogram. The internal structures of the clusters also differed on the two dendrograms. For example, five of the wine strains isolated from botrytised wine in Szegi (strains 10–372 to 10–375 and 10–377) were in the same subcluster of Fig. S2 (Supporting Information), but were grouped with strains of different origin (Spanish must and grapes, Swiss grapes) on the Bruvo-distance dendrogram. The dendrograms indicate two groups of the Hungarian strains mixed with the others. The neighbour net analysis identified the same clusters and also reinforced the heterogeneity of Cluster 1 (Fig. 4). The stress for the nMDS configuration of the microsatellite data was high (at 0.4) indicating difficulty in displaying the relationships between the strains (data are not shown). Figure 3. View largeDownload slide Comparison of the UPGMA and NJ dendrograms generated from Bruvo distances of the microsatellite amplicons. Strain 11–60 was used as outgroup. For the explanation of symbols, see Fig. 1. Numbers 1 and 2 mark clusters. Figure 3. View largeDownload slide Comparison of the UPGMA and NJ dendrograms generated from Bruvo distances of the microsatellite amplicons. Strain 11–60 was used as outgroup. For the explanation of symbols, see Fig. 1. Numbers 1 and 2 mark clusters. Figure 4. View largeDownload slide Equal angle neighbor net deduced from the Bruvo distances of the microsatellite amplicons. Thick marks denote splits separating clusters. Double-line arrows mark splits separating subclusters. 1 and 2: clusters corresponding to the clusters of the NJ dendrogram shown in Fig. 3. Figure 4. View largeDownload slide Equal angle neighbor net deduced from the Bruvo distances of the microsatellite amplicons. Thick marks denote splits separating clusters. Double-line arrows mark splits separating subclusters. 1 and 2: clusters corresponding to the clusters of the NJ dendrogram shown in Fig. 3. We compared the positions of the 17 strains on our NJ tree generated from Bruvo distances of microsatellite with their positions on the tree of Masneuf-Pomarede et al. (2015) on the basis of the figure in their paper. We found that most of the strains are similarly located. For example, 10–372 and 10–375 are close to each other on both trees. However, 10–373 and 10–374 are apart from each other and the other two on both trees. Certain strains (11–1, 10–373, 11–20, 11–19, 11–149, 11–150 and 11–6) were grouped together in the Miscellanous group on the Masneuf-Pomarede et al. (2015) tree and in Cluster 1 on our Bruvo distance NJ tree (Fig. 3). Strains 11–4 and 10–374 [group ‘France’ on the Masneuf-Pomarede et al. (2015) tree] are further apart on our tree, where 11–4 is near the 11–479 and 11–101 strains (‘Spain/France’ group) and 10–374 is among the ‘Miscellanous’ strains. Comparison of mtDNA and microsatellite analyses Although the analysis of the mtDNA patterns and the two types of microsatellite analysis resulted in different tree topologies, we sought to determine whether there are strains in the examined collection which tend to group together on all trees. For that purpose, we aligned the mtDNA dendrograms in all possible pairwise combinations with the microsatellite dendrograms. We found little correspondence in the positions of the strains. Figures S3 and S4 (Supporting Information) show the alignments of the UPGMA dendrograms generated from the mtDNA RFLP patterns and the microsatellite size patterns. Very few strains had similar positions on both trees. Only four pairs of strains are together on both dendrograms: two wine isolates from Szegi (10–373 and 10–377), two grape isolates from Mád (11–135 and 11–138), two Drosophila isolates from Tarcal (10–1544 and 10–1529), two grape isolates from Spain (10–622 and 10–624) and an Italian isolate from wine with a French isolate from grape juice (11–6 and 11–8). Interestingly, even less similarity can be seen when the mtDNA dendrogram is compared with the Bruvo-distance microsatellite dendrogram. We also compared our data with those of Pfliegler et al. (2014) obtained previously by using different molecular markers. To better visualise the correspondence, we redraw their dendrogram using their original Newick file. We used 11–60 as outgroup. The alignment with our mtDNA UPGMA dendrogram is shown in Fig. S5 (Supporting Information). None of the mtDNA clusters can be recognised on it and very few strains are grouped together on both dendrograms: two Eszencia strains isolated in different locations of the Tokaj region (11–149, Tarcal and 11–152 Bodrogkeresztúr), two Tokaj strains isolated from different types of wines in different locations (11–144 from Eszencia in Erdőbénye and 10–376 from fermenting botrytised wine in Szegi), two Spanish isolates of different origin (10–624 and 11–1) and three grape isolates from two countries (11–4, 11–135 and 11–138). When our microsatellite dendrograms were compared with the dendrogram of Pfliegler et al. (2014), the correspondence was even poorer. Minimum spanning tree of the microsatellites From the matrix of the pairwise Bruvo distances, we also created a minimum spanning tree (MST) (Fig. 5). It displays three main clusters and four additional branches which consist of only one or two strains. The interior node with the largest number of edges is the isolate 10–375 derived from the Szegi region of Tokaj, Hungary. It has diversified in three major directions. Towards node 10–374 (also isolated in Szegi) which then split in two subclusters. One of them consists of two Tarcal isolates (isolated from sweet botrytised wine, Tarcal region of Tokaj), two Swiss strains and an isolate from water melon. The other subcluster contains the Tarcal isolate 11–148 (the node with the second largest numbers of edges) connected to a very diverse group of Californian, Italian, Spanish and Tokaj strains. The second cluster is connected to the central node through 10–377 (isolated from sweet botrytised must, Szegi region of Tokaj) and also incorporates strains of diverse geographical origins, including two Hungarian (Tokaj and Badacsony), French, Italian, Slovakian and Spanish regions. The third, smallest cluster contains strains from two Tokaj vineyards (Tarcal and Mád) and a Swiss wine region. No correlation between the positions of the strains on the tree and the substrate from which they were isolated can be seen. For example, the eight strains isolated from Drosophilas collected in the Tarcal vineyard of the Tokaj region are scattered over the entire tree. Figure 5. View largeDownload slide Minimum spanning tree analysis based on the Bruvo distances of the microsatellite amplicons. Each circle corresponds to a microsatellite pattern (genotype). The lines between circles indicate the similarity between profiles: normal line, one locus in common; bold line, more than one microsatellite loci in common. Figure 5. View largeDownload slide Minimum spanning tree analysis based on the Bruvo distances of the microsatellite amplicons. Each circle corresponds to a microsatellite pattern (genotype). The lines between circles indicate the similarity between profiles: normal line, one locus in common; bold line, more than one microsatellite loci in common. DISCUSSION In a previous biodiversity study, we already demonstrated by the analysis of a set of S. cerevisiae wine yeasts that different methods can result in different dendrogram topologies and may not group together strains of shared origin (Pfliegler and Sipiczki 2016). In the less investigated C. zemplinina, the diversity studies also indicate that the outcome of a diversity analysis is critically dependent on the selection of the molecular marker and the analysing algorithm. The most comprehensive analysis involving 163 strains from 28 vineyards of seven countries revealed high degree of microsatellite diversity and highlighted that the diversity of this species is shaped, at least in part, by geographical location but no specific genetic signatures could be associated with the different vineyards/wineries (Masneuf-Pomarede et al.2015). Other studies analysing different markers, smaller groups of isolates and covering fewer locations detected lower diversity (Pramateftaki et al.2008; Di Maio et al.2012; Tofalo et al.2012; Pfliegler et al.2014). These works either did not examine the relationships between the patterns and the isolation sites or detected no clear correlation. Interestingly, very few studies found correspondence between the polymorphism of genetic markers and the geographical origin of strains in other wine-related yeast species either. Versavaud et al. (1995) observed no correlation between marker patterns (electrophoretic karyotyping, mitochondrial DNA restriction fragment length polymorphism analysis and PCR amplification of Ty transposons) and geographical origin amongst S. cerevisiae strains isolated from 42 wine cellars in the Charentes area (Cognac region, France). An analysis of South-American S. cerevisiae strains isolated from wines of three geographically distant countries by electrophoretic karyotyping and mitochondrial DNA restriction analysis detected some correspondence between the molecular patterns and the geographical origin but found that such a correlation can easily be lost (Martinez et al.2004). Guillamon, Barrio and Querol (1996) found that certain Spanish red wine strains (but not the white-wine strains) grouped according to their geographical origin, when their electrophoretic karyotypes and mitochondrial DNA RFLP profiles were compared (Guillamon, Barrio and Querol 1996). No clear correlation was found between the chromosomal patterns and the geographical locations of sample collection among Saccharomyces strains isolated in four Hungarian wine-growing regions either (Csoma et al.2010). In a large group of Hanseniaspora uvarum strains isolated in five continents, most South African isolates formed a distinct cluster on the microsatellite dendrogram, but most French strains clustered on the basis of the year of isolation instead of their geographical origin (Albertin et al.2016). The microsatellite analysis of 110 Torulaspora delbrueckii strains separated most wine isolates from those isolated from the nature or other biotechnological processes, but the group of the wine isolates was not structured according to the geographical origin (Albertin et al.2014). In this study, the analysis of two molecular markers, microsatellites and mtDNA, in a group of 41 C. zemplinina strains by various bioinformatics tools also resulted in certain cases different clustering, and none of the dendrograms grouped the strains fully consistently with their geographical origin. Deliberately, the strains were selected for the project so that their majority was from one wine-growing region. These strains were isolated from wines of the Tokaj region (Hungary), where the type strain of C. zemplinina had been isolated (Sipiczki 2003) and this yeast is a regular component of the yeast communities fermenting botrytised wines (Csoma and Sipiczki 2008). In the same region, strains were also isolated from Drosophila flies and larvae which we assume might contribute to the survival of this asporogenic yeast between vintage seasons. For each strain, the size of five microsatellite loci found highly variable in a previous study (Masneuf-Pomarede et al.2015) and the RFLP pattern of the mitochondrial DNA were determined. From the experimental results, distance matrices were generated and analysed with UPGMA, NJ, neighbour net, MST and nMDS algorithms. Most dendrograms generated by different algorithms showed rather limited similarity with each other. The different topologies of the UPGMA and NJ trees inferred from the same distance matrices can be attributed to the different mode of branch-length calculation. UPGMA assumes equal rates of evolution on all branches, whereas the NJ algorithm allows unequal rates of changes on the branches (Saitou and Nei 1987). If rates on different branches are markedly unequal, the branching orders produced by the two methods will differ. The situation is further complicated by the possibility of the calculation of microsatellite distance matrices in two ways: from the size differences of the amplified fragments and from the differences of their repeat numbers. According to several authors, the longer and purer the repeat, the higher the mutation frequency, whereas shorter repeats with lower purity have a lower mutation frequency (Vieira et al.2016). We computed distance matrices in both ways and obtained rather different tree topologies. On the dendrograms obtained in the first case, the majority of the Hungarian strains formed a separate group, whereas in the second case the non-Hungarian isolates were scattered on the dendrogram between the two major groups of Hungarian isolates. In principle, the dendrogram inferred from the repeat number differences (Bruvo distances) can be assumed to show better the relationships of the strains. It can be traced back to the replication slippage which is one of the main mechanisms affecting the microsatellites. It is a DNA replication error in which the template and nascent strands are mismatched. This means that the template strand can loop out, causing contraction. The nascent strand can also loop out, leading to repeat expansion. The process is involving a gain or loss of one or more repeat units (Vieira et al.2016). To the observed length polymorphism may also contribute the so-called interrupting motifs, which means that a sequence of a few base pairs is inserted into the motif from which it follows that the sequences will deviate from the repeating motif. Certain microsatellite alleles sequenced from the C. zemplinina type strain and used in this study have such interruptions (Masneuf-Pomarede et al.2015). The ignorance of their presence risks inaccurate calculation of Bruvo distances. As precise calculation can be done only when all amplified alleles are sequenced, most works based on locus amplification ignore this aspect. Since we ourselves used this practice, we cannot take a definitive stand on which mode of distance calculation can result in more realistic topologies. The MST generated from the Bruvo-distance matrix of the microsatellites also failed to show good correspondence between the position of the strains on the tree and their geographical origin. An MST is an acyclic graph that consists of nodes (strains) connected by edges that link together nodes by the shortest possible distance reflecting thus the concept of minimal evolution. By allowing individuals (strains) to be placed in interior nodes, MST is assumed to better convey the peculiarities of short-term intraspecific evolution than the conventional trees (Excoffier and Smouse 1994). Although it linked numerous Tokaj strains together, the lineages of the Tokaj strains were interspersed with strains isolated in remote wine-growing regions, and certain Tokaj strains were placed far from the major groups and close to strains that could hardly have had common recent history with them. The inconsistency between the microsatellite and the mtDNA tree topologies can be attributed to several factors, such as different impact of the selection pressure on these markers and the different rates and mechanisms of their changes. Being involved in metabolic processes and stress tolerance (e.g. Carmona-Gutierrez et al.2012), the mitochondria are likely to be under stronger selection pressure than the physiologically neutral or less important microsatellite loci (e.g. Reis et al.2017). In general, the mitochondrial DNA appears to mutate at a greater rate than the nuclear DNA in many organisms and most mutations are base substitutions and small insertions/deletions (e.g. Lynch et al.2008). In contrast, microsatellites mutate to novel length variants by replication slippage, with the mutation rate generally increasing dramatically with the number of repeats at the locus (Wierdl, Dominska and Petes 1997), most probably irrespective of which environmental condition is changing. Thus, microsatellite changes occur more accidentally and at variable rates depending on the locus size. The mutation rate of these elements could be between 103 and 106 per cell generation, which are 10 orders of magnitude greater than that of point mutations (Gemayel et al.2012). However, it seems that eukaryotes that have more DNA repeats might provide a molecular device for faster adaptation to environmental stresses (Li et al.2004). Consistent with this, we found somewhat better correspondence between the positions of the strains and their geographical origin on the mtDNA dendrograms than on the microsatellite trees. This seems to be confirmed by the nMDS ordinations of the mtDNA RFLP profiles. NMDS is an ordination technique which is a complex numerical algorithm. It focuses on the rank order of the dissimilarity matrix and requires the final configuration to contain distances that follow the rank of the original dissimilarity matrix as closely as possible (Zhu and Yu 2009). The mtDNA dendrograms showed better correspondence also with certain isolation sources. For example, they grouped five of the eight Drosophila isolates together. In contrast, the best grouping of the strains isolated from Tokaj Eszencia was observed on the microsatellite dendrogram inferred from the Bruvo distances of the microsatellite patterns. In the case of strains isolated in closely located vineyards and wineries, neither method could clearly separate the grape-born and the wine-born isolates. As most strains analysed in this work were included in previous diversity studies, we could compare their relative positions on our dendrograms and on the dendrograms constructed in those studies. Our analyses reinforced neither the results of the previous UPGMA analysis of combined band patterns obtained with non-specific mini/microsatellite and RAPD primers (Pfliegler et al.2014) nor those (only partially) obtained with NJ analysis of the Bruvo distances of 10 species-specific microsatellites (Masneuf-Pomarede et al.2015). However, when interpreting the poor correspondence one has to take into consideration that the three studies examined very different sets of strains, analysed different markers and outgroup was used only in our study. Nevertheless, it is worth mentioning that some isolates (11 out of 18) were grouped the same way in both the Masneuf-Pomarede et al. (2015) and our microsatellite NJ trees. The results presented in this work and their comparisons to previous analyses demonstrate that different markers and different clustering methods can result in different groupings of the same strains. The observed differences between the topologies also indicate that the positions of the strains do not necessarily reflect their real historical relationships. Strains placed close to one another on a microsatellite tree can be assigned to different clusters on the mtDNA tree and vice versa. For example, on none of the dendrograms and trees formed the Tokaj isolates compact separate clades and neither method grouped together all Drosophila isolates or all Eszencia isolates. The poor correspondence further indicates that the strains of this species do not form geographically well-isolated populations. SUPPLEMENTARY DATA Supplementary data are available at FEMSYR online. Acknowledgements The authors thank Anita Kovács for the expert technical assistance and Zoltán Kállai for strains. Conflict of interest. None declared. REFERENCES Albertin W , Chasseriaud L , Comte G et al. Winemaking and bioprocesses strongly shaped the genetic diversity of the ubiquitous yeast Torulaspora delbrueckii . Food Microbiol 2014 ; 9 : 559 – 67 . Albertin W , Setati ME , Miot-Sertier C et al. Hanseniaspora uvarum from winemaking environments show spatial and temporal genetic clustering . Front Microbiol 2016 ; 6 : 1569 . Google Scholar CrossRef Search ADS PubMed Andorrà I , Landi S , Mas A et al. 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Application of different markers and data-analysis tools to the examination of biodiversity can lead to different results: a case study with Starmerella bacillaris (synonym Candida zemplinina) strains

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Abstract

Abstract Starmerella bacillaris (Candida zemplinina) is a genetically heterogeneous species. In this work, the diversity of 41 strains of various origins is examined and compared by the analysis of the length polymorphism of nuclear microsatellites and the RFLP of mitochondrial genomes. The band patterns are analysed with UPGMA, neighbor joining, neighbor net, minimum spanning tree and non-metric MDS algorithms. The results and their comparison to previous analyses demonstrate that different markers and different clustering methods can result in very different groupings of the same strains. The observed differences between the topologies of the dendrograms also indicate that the positions of the strains do not necessarily reflect their real genetic relationships and origins. The possibilities that the differences might be partially due to different sensitivity of the markers to environmental factors (selection pressure) and partially to the different grouping criteria of the algorithms are also discussed. Candida zemplinina, mtDNA, microsatellite markers, strain biodiversity, RFLP-mtDNA INTRODUCTION Candida zemplinina (recently merged with the former species Saccharomyces bacillaris and Torulopsis bacillaris under the new taxonomic name Starmerella bacillaris) long considered conspecific with C. stellata is a wine-associated yeast species (Csoma and Sipicki 2008), frequently isolated from grapes and fermenting wines. Next to Saccharomyces, C. zemplinina is quantitatively one of the most important yeasts in the fermentation of botrytised grape musts and has been detected in many wine-growing regions of the world (e.g. Mills, Johannsen and Cocolin 2002; Nisiotou and Nychas 2007; Csoma and Sipiczki 2008; Urso et al.2008; Li et al.2010; Zanol, Baleiras-Couto and Duarte 2010; Zott et al.2010; Di Maio et al.2012; Gayevskiy and Goddard 2012; Tofalo et al.2012; Masneuf-Pomarede et al.2015). It is a very promising non-Saccharomyces yeast which could be potentially used in winemaking as co-starter with S. cerevisiae strains (e.g. Andorrá et al.2010; Comitini et al.2011; Di Maio et al.2012; Rantsiou et al.2012; Sadoudi et al.2012; Giaramida et al.2013; Englezos et al.2015). Its strains can have beneficial effects on the wine due to certain favourable properties such as osmo- and psychrotolerance, fructophily, high glycerol yield and a relatively low acetaldehyde, volatile acid and sulphur dioxide production and the ability to degrade malic acid (e.g. Mills, Johansen and Cocolin 2002; Sipiczki 2003, 2004; Tofalo et al. 2009, 2012; Magyar and Tóth 2011; Giaramida et al.2013; Magyar et al.2014; Pfliegler et al.2014; du Plessis et al.2017). Candida zemplinina is not associated exclusively with vineyards and wines because its strains have also occasionally be isolated from other substrates such as fermented cocoa in Ghana (Nielsen et al. 2005, 2007), soil in Italy (Csoma and Sipiczki 2008), Drosophila sp. in the USA (Phaff, Miller and Shifrine 1956; Stamps et al.2012), rotten water melon in Hungary and rotten banana in the Philippines (Csoma and Sipiczki 2008; Pfliegler et al.2014). Many authors examined the intraspecific genetic biodiversity of C. zemplinina strains. The molecular methods used were RAPD-PCR fingerprinting (Tofalo et al.2012; Pfliegler et al.2014), SAU-PCR (Englezos et al.2015), mtDNA-RFLP (Di Maio et al.2012), Fourier-transform infrared spectroscopy (Grangeteau et al.2016) and microsatlite analysis (e.g. Pfliegler et al.2014; Englezos et al.2015; Masneuf-Pomarede et al.2015). The different methods detected varying degrees of diversity. For example, Pfliegler et al. (2014) noticed a relatively low level of genetic intraspecific diversity with two types of genomic RAPD-PCR and two types of non-specific micro/minisatellite primers, whereas Masneuf-Pomarede et al. (2015) observed much higher diversity by analysing 10 species-specific microsatellite loci of the same strains in a more comprehensive analysis involving a large number of wine-related isolates of various geographical origins. The latter authors found that no specific genetic signatures could be associated with the different samples and vineyards/wineries, but the genetic diversity showed significant correlation with the geographical origin of the strains. Considerable intraspecies diversity was detected in the mitochondrial DNA as well. In a collection of 59 Sicilian isolates, 14 different RFLP patterns were distinguished (Di Maio et al.2012). In a collection of 44 mostly Greek isolates, the presence and structure of a group-IIB1 intron containing an ORF encoding a putative reverse transcriptase was examined (Pramateftaki et al.2008). Only a quarter of the strains had this intron, and their intron sequences differed in size and in the number and position of point mutations. The different extent of diversity detected in these studies does not necessary reflect real phylogenetic differences but might be attributed to the use of different markers and different bioinformatics tools in the different laboratories. In this paper, we report on the investigation of the diversity in a set of 41 C. zemplinina strains by comparing their nuclear microsatellites and mitochondrial genomes. For clustering the patterns, we used several algorithms and then compared the topologies of the dendrograms and the positions of strains of shared origins on them. Most strains examined in this study were included in previous diversity studies (Pfliegler et al.2014; Masneuf-Pomarede et al.2015), allowing thus a comparison of the results of our diversity analyses with those of previous works. The new strains were isolated from Drosophila larvae and flies in the Tokaj wine-growing region, Hungary. MATERIALS AND METHODS Yeast strains and media The 41 strains of C. zemplinina examined in this study (Table 1) were identified and described in previous works (Sipiczki 2003, 2004; Csoma and Sipiczki 2008; Pfliegler et al.2014 and references therein) or isolated from guts of Drosophila larvae and flies collected in Tokaj vineyards (Z. Kállai, unpublished). The ITS sequences of the latter strains are deposited in GenBank under the following accession numbers: 10–1496 (KT933399), 10–1539 (KT933400), 10–1541 (KT933401), 10–1544 (KT933402), 10–1529 (KT933403), 10–1573 (KT933404), 10–1562 (KT933405) and 10–1506 (KT933406). The strains were maintained at 25°C on YPGA (2% glucose, 2% agar, 1% yeast extract and 1% peptone; all w/v) or cultured in YPGL (YPGA without agar) for the extraction of mitochondrial and genomic DNA. Table 1. List of strains. Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) T: Type strain CBS: Centraalbureau voor Schimmelcultures, Delft, The Netherlands CECT: Colección Española de Cultivos Tipo, Valencia, Spain NCAIM: National Collection of Agricultural and Industrial Microorganisms, Budapest, Hungary RIVE: Research Institute of Viticulture and Enology, Bratislava, Slovakia Eszencia or Essence is a specific sweet dessert wine of high sugar content made from the juice of separately collected botrytised berries View Large Table 1. List of strains. Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) Origin Geographical location Strain Other identifier Source habitat Region Country Original reference From wine-related habitats 10–622 Grape Unknown Spain Clemente-Jimenez et al. (2004) 10–624 Grape Unknown Spain Clemente-Jimenez et al. (2004) 11–4 RIVE 3.16.2 Grape Biele Karpaty Slovakia E. Minarik, Csoma and Sipiczki (2008) 11–19 Stasa 444; Rbst 9–00 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–20 Stasa 214; Rst 98/10/7 Grape Waedenswill Switzerland J. Gaffner, Csoma and Sipiczki (2008) 11–101 16.4.21 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–88 T1.3.29 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–124 T2.3.1 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–128 5.3.52 Botrytised grape Tarcal, Tokaj region (Szarvas vineyard) Hungary Csoma and Sipiczki (2008) 11–107 10.5.11 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–135 25.1.1 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–138 26.1.35 Botrytised grape Mád, Tokaj region (Király vineyard) Hungary Csoma and Sipiczki (2008) 11–1 CECT 11969 Grape must Andalucia Spain L. Mingorance-Cazorla; Csoma and Sipiczki (2008) 11–8 CBS 2649 Grape juice Médoc France E. Peynaud, Csoma and Sipiczki (2008) 11–659 IV.BK21 Fermenting must Badacsony Hungary Pfliegler et al. (2014) 11–18 Stasa 8, FAW3 Fermenting wine Waedenswill Switzerland J. Gaffner; Csoma and Sipiczki (2008) 10–372 T CBS 9494T Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–373 NCAIM Y016668 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–374 NCAIM Y016669 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–375 NCAIM Y016670 Fermenting botrytised wine Szegi, Tokaj region (wine 1) Hungary Sipiczki (2003) 10–376 Aszu2 1/16 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 10–377 Aszu2 1/31 Fermenting botrytised wine Szegi, Tokaj region (wine 2) Hungary Sipiczki (2003) 11–6 CBS 1713 wine Unknown Italy O. Verona; Csoma and Sipiczki (2008) 11–144 I.VM4 Botrytised wine (Eszencia) Erdőbénye, Tokaj region (Viva Mus) Hungary Csoma and Sipiczki (2008) 11–148 I.DE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Degenfeld) Hungary Csoma and Sipiczki (2008) 11–149 I.SE1 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–150 II.SE12 Botrytised wine (Eszencia) Tarcal, Tokaj region (Királyudvar) Hungary Csoma and Sipiczki (2008) 11–152 II.LA6 Botrytised wine (Eszencia) Bodrogkeresztúr, Tokaj region Hungary Csoma and Sipiczki (2008) 10–1496 L-4 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1539 L-10 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1541 L-15 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1544 L-28 Drosophila sp. larva Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1529 B-5 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1573 B-29 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1562 B-62 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai 10–1506 B-78 Drosophila sp. adult Tarcal, Tokaj region (Bakonyi vineyard) Hungary Z. Kállai From other habitats 11–9 CBS 2799 Soil Sardinia Italy A Capriotti; Csoma and Sipiczki (2008) 11–31 NCAIM Y.00402 Unknown Unknown Hungary Csoma and Sipiczki (2008) 11–60 CBS 4729 Drosophila pinicola Yosemite, California USA Phaff et al. (1956) 11–159 NCAIM Y.01025 Rotten watermelon Unknown Hungary G. Péter, Csoma and Sipiczki (2008) 11–479 Rotten banana Manila The Philippines Pfliegler et al. (2014) T: Type strain CBS: Centraalbureau voor Schimmelcultures, Delft, The Netherlands CECT: Colección Española de Cultivos Tipo, Valencia, Spain NCAIM: National Collection of Agricultural and Industrial Microorganisms, Budapest, Hungary RIVE: Research Institute of Viticulture and Enology, Bratislava, Slovakia Eszencia or Essence is a specific sweet dessert wine of high sugar content made from the juice of separately collected botrytised berries View Large Mitochondrial DNA extraction and restriction analysis The mitochondrial DNA (mtDNA) was extracted from cells of exponential-phase YPGL cultures according to the method described by Antunovics et al. (2005). This protocol allows isolation of the mitochondrial genome irrespective of the genomic DNA. The cell pellet was washed once in water and once in 50 mM EDTA. After this, the pellet was suspended in wash buffer [1.2 M Sorbitol, 50 mM Tris (pH 7.5), 50 mM EDTA, 2% b-mercaptoethanol] and incubated at 37°C for 10 min. The pellet was then resuspended in 1 ml solution A [0.5 M Sorbitol, 50 mM Tris (pH 7.5), 10 mM EDTA, 2% b-mercaptoethanol], to which 100 U Zymolyase 100T (MP Biomedicals) were added, and the cells were incubated at 37°C for 45 min under gentle horizontal shaking (400 rpm). The spheroplastes were then disrupted by sonication at middle energy level for 6 s. The suspension was then centrifuged at 2800 rpm for 10 min. The supernatant was transferred to a new 1.5-mL tube and centrifuged at 14 000 rpm for 10 min. The crude mitochondrial pellet was washed with 1 mL solution A and resuspended in 500 mL solution A supplemented with DNAse I (10 U) and 25 mM MgCl2. After 10 min of treatment at room temperature, it was centrifugated. To the mitochondrial pellet 0.5 mL solution B [100 mM NaCl, 10 mM EDTA, 50 mM Tris (pH 8)] and 1% sodium lauroyl sarcosine were added. After being suspended, the preparation was incubated at room temperature for 30 min to allow mitochondrial lysis. The mtDNA was then purified by phenol:chloroform:isoamyl alcohol (25:24:1) extraction followed by ethanol precipitation. The mtDNA pellet was dissolved in 50 mL TE buffer (10 mM Tris, 1 mM EDTA, pH 8). RNA was degraded by RNAse treatment at 37°C for 1 h. The isolated mtDNA was digested with EcoRI (Fermentas), EcoRV (Fermentas), DraI (Thermo Scientific), HinfI (Fermentas), MboI (Thermo Scientific), HaeIII (Fermentas) and HindIII (Promega) according to the instructions of the suppliers. The mtDNA fragments were loaded onto 1% and 1.4% (w/v) agarose gels containing ethidium-bromide, and electrophoresis was carried out in 1 × TBE buffer at 115 V for 70–120 min. A GeneRuler 1 kbp Plus DNA ladder marker (Thermo Scientific) served as size standard. After separation, the fragments were visualised and photographed. Microsatellite amplification Yeast cultures were grown at 25°C for 2 days in YPGL. Total genomic DNA was subsequently extracted from the cells using the protocol described in Hanna and Xiao (2006). The microsatellites were amplified in 50 μL reaction mixtures containing 100 ng of genomic DNA, 0.5 μL of DreamTaq® DNA Polymerase (500 U), 5 μL (10x) DreamTaq Green buffer (Thermo Scientific) and 40 pmol of CZ13, CZ11, CZ1, CZ15 or CZ4 primer pairs (Masneuf-Pomarede et al.2015). A LifeECO (Hangzhou Bioer Technology Co. Ltd) thermal cycler (3 min at 95°C; 30 cycles of 30 s at 95°C, 30 s at 54°C and 30 s at 72°C; 10 min at 72°C) was used. The amplicons were loaded onto 3% (w/v) agarose gels stained with ethidium-bromide and the electrophoresis was carried out in 1 x TBE buffer at 140 V for 80 min. A GeneRuler 20 bp DNA ladder marker (Thermo Scientific) was used as size standard. After visualisation of the amplicons, the gels were photographed. Data analyses The mtDNA and microsatellite patterns were analysed using the GelAnalyzer 2010 software (Lazar and Lazar 2010) with manual adjusting. Distances of the band patterns were calculated with the Dice's (Dice 1945) coefficient using the algorithm available at http://genomes.urv.es/UPGMA. The resulting distance matrices were subjected to cluster analysis by the unweighted pair group method with arithmetic averages (UPGMA) algorithm and by the neighbour joining (NJ) algorithm available in the PHYLIP package (Felsenstein 2007). In the case of microsatellites, dendrograms were built also from Bruvo distances (Bruvo et al.2004). For this, the numbers of repeats in the amplified fragments were determined using the method described by Masneuf-Pomarede et al. (2015). Dendrograms were visualised with the FigTree program (http://tree.bio.ed.ac.uk). The neighbor net analysis was carried out with SplitsTree4 V4.14.4 (Huson and Bryant 2006). Minimum spanning tree was constructed from the microsatellite data with the Tree and Network Inference module of the BioNumerics 7 software platform (http://www.applied-maths.com/bionumerics). Non-metric multidimensional (nMDS) analyses (Shepard 1962; Kruskal 1964) were performed with Past3 software (https://folk.uio.no/ohammer/past/) (Hammer, Harper and Ryan 2001) using the corresponding concatenated binary matrices of the strains. Bray-Curtis (Bray and Curtis 1957) was used as similarity coefficient and the dimensionality was adjusted to 3. RESULTS RFLP analysis of mitochondrial DNA To investigate the intraspecific variation present in the C. zemplinina mitochondrial genomes, we analysed the RFLP patterns of the mtDNA from a set of 41 C. zemplinina strains. Seven restriction endonucleases were used to digest the mtDNA of the strains. The digestion of the mtDNA produced reproducible mtDNA restriction profiles for each strain (examples are shown in Fig. S1, Supporting Information). The enzymes differed in the number and size range of the bands, allowing the differentiation of 7 to 27 patterns (Table 2). The size of the mitochondrial genomes calculated from the fragment sizes corresponded to the size of the sequenced genome (23 kbp) of the strain CECT 11046 (Pramateftaki et al.2008). Table 2. Fragments generated from the mtDNA of C. zemplinina strains by restriction endonuclease digestion. Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 View Large Table 2. Fragments generated from the mtDNA of C. zemplinina strains by restriction endonuclease digestion. Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 Restriction endonuclease Total number of bands Average number of bands/strain Size range of the bands in base pairs Total number of patterns EcoRI 13 3.7 18 000–1350 7 EcoRV 18 7 6000–390 11 DraI 35 19.4 7000–200 27 HinfI 39 21.5 2300–150 19 MboI 35 15.6 4000–200 18 HaeIII 34 7.7 10 000–350 18 HindIII 14 4.7 8000–1400 12 View Large The seven band patterns of each strain were converted to binary matrices which were then concatenated. The concatenated matrix contained 188 elements from which 170 were informative. The UPGMA and NJ dendrograms generated from the matrix had similar overall topologies (Fig. 1). The strains formed three well-separated clusters: two smaller but quite compact clusters and one larger, heterogeneous cluster. Cluster I harboured only Tokaj isolates. Cluster II was also dominated by isolates from Hungary; the two exceptions were a strain from Switzerland (11–19) and a strain from The Philippines (11–479). All but three strains (11–31, 11–159 and 11–479) of these clusters were isolated from wine-related habitats. The third cluster grouped strains of diverse origin and had different internal structures in the two types of dendrograms. Figure 1. View largeDownload slide Comparative dendrogram constructed with NJ and UPGMA clustering of the concatenated mtDNA-RFLP matrices. Strain 11–60 was used as outgroup. The first column of symbols shows the strain names (see Table 1). The second column shows the country of origin: C, Switzerland; E: Spain; F, France; H, Hungary; I, Italy; P, The Philippines; S, Slovakia; U, USA. The third column shows the region of origin: A, Andalucia; B, Badacsony; C, California; K, Biele Karpaty; M, Manila; S, Sardinia; T, Tokaj; W, Waedenswill. The fourth column shows the habitat (substrate) from which the strain was isolated: B, rotting banana; D, Drosophila; E, wine (Eszencia); F, fermenting wine; G, grape; J, grape juice; M, must; S, soil; W, wine; WM, watermelon. Roman numerals mark clusters. Figure 1. View largeDownload slide Comparative dendrogram constructed with NJ and UPGMA clustering of the concatenated mtDNA-RFLP matrices. Strain 11–60 was used as outgroup. The first column of symbols shows the strain names (see Table 1). The second column shows the country of origin: C, Switzerland; E: Spain; F, France; H, Hungary; I, Italy; P, The Philippines; S, Slovakia; U, USA. The third column shows the region of origin: A, Andalucia; B, Badacsony; C, California; K, Biele Karpaty; M, Manila; S, Sardinia; T, Tokaj; W, Waedenswill. The fourth column shows the habitat (substrate) from which the strain was isolated: B, rotting banana; D, Drosophila; E, wine (Eszencia); F, fermenting wine; G, grape; J, grape juice; M, must; S, soil; W, wine; WM, watermelon. Roman numerals mark clusters. Surprisingly, we obtained different RFLP patterns for certain strains isolated from the same wine, vineyard or vintage. The differences were sometimes so big that the analysis placed them on distant branches of the dendrograms. For example, the Tokaj strains isolated in Szegi (10–372 to10–377) were assigned to three clusters. In contrast, the majority of the strains isolated from Drosophila larvae and flies collected in the Bakonyi vineyard (Tarcal, Hungary) formed a quite compact group in Cluster III. However, even these isolates had representatives in the other two clusters. For example, 10–1496 had a pattern highly similar to those of the strains 1–88 and 11–24 (grape, Szarvas vineyard 2003) strains, whereas the mtDNA pattern of 10–1539 was similar to that of 11–159 (rotten watermelon, Hungary). The nMDS ordinations of the mtDNS RFLP profiles (Fig. 2) presented stress values of 0.05 indicating a confident representation with no prospect of misinterpretations (Clarke and Warwick 2001). The plots are ordinations of strains based on their relative similarities. The agreement between the Figs 1 and 2 is very good: the same clusters are sharply defined demonstrating that the two methods determined the clusters much the same way. Figure 2. View largeDownload slide Non-metric MDS configurations of the mtDNA RFLP patterns. The groups highlighted in Fig. 1 are marked with the same Roman numerals. Figure 2. View largeDownload slide Non-metric MDS configurations of the mtDNA RFLP patterns. The groups highlighted in Fig. 1 are marked with the same Roman numerals. Microsatellite analysis In order to compare the genetic relationships of strains obtained with mtDNA-RFLP analysis to those of the nuclear genomes, five species-specific microsatellite markers (CZ1, CZ4, CZ11, CZ13 and CZ15) described by Masneuf-Pomarede et al. (2015) were also examined. Interestingly, the fragments amplified from the type strain CBS 9494T (10–372T) slightly differed in size from those obtained previously by Masneuf-Pomarede et al. (2015) (Table 3). The fragments obtained from the other strains varied in the size range of 105–347 base pairs (Table 3). All strains were homozygous for the examined loci, except for 11–6 which was heterozygous for the locus CZ15. This result is in agreement with that observed by Masneuf-Pomarede et al. (2015). Table 3. Size diversity of the microsatellite loci of C. zemplinina strains. Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) aAllele size in bp. View Large Table 3. Size diversity of the microsatellite loci of C. zemplinina strains. Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) Allele sizea (repeat number) for CBS9494T (10–372T) Microsatellite name Masneuf-Pomarede et al. (2015) This study Allele sizea (repeat number) range in all strains CZ1 168 (15) 163 (15) 154–172 (10–20) CZ4 248 (15) 230 (15) 221–246 (12–20) CZ11 339 (43) 327 (43) 296–347 (29–46) CZ13 125 (21) 111 (21) 105–115 (19–22) CZ15 299 (13) 281 (13) 249–296 (2–19) aAllele size in bp. View Large From the amplified fragments, a binary matrix was compiled for each microsatellite locus then the matrices of the same strain were concatenated. The concatenated matrices of the strains were used to generate a distance matrix. From the distance matrix UPGMA and NJ dendrograms were constructed. The dendrograms (Fig. S2, Supporting Information) showed marked topological differences and also differed from those deduced from the mtDNA analysis (Fig. 1). Here only two clusters could be distinguished and neither corresponded to any of the mtDNA clusters. As the microsatellite motifs differed in the size of their repeats (Masneuf-Pomarede et al.2015), we also performed clustering by analysing Bruvo distance values calculated from the repeat numbers of the amplicons (Fig. 3). Both the UPGMA and NJ dendrograms grouped the majority of strains into two clusters but the larger cluster was divided into two subclusters in the UPGMA dendrogram. The composition of these clusters only partially overlapped with the composition of the clusters of the dendrograms drawn from the length differences of the amplicons (Fig. S2, Supporting Information). For example, all but one grape strains isolated in Tarcal were assigned to Cluster B in Fig. S2 (Supporting Information), whereas they were represented equally in both clusters of the Bruvo-distance dendrogram. The internal structures of the clusters also differed on the two dendrograms. For example, five of the wine strains isolated from botrytised wine in Szegi (strains 10–372 to 10–375 and 10–377) were in the same subcluster of Fig. S2 (Supporting Information), but were grouped with strains of different origin (Spanish must and grapes, Swiss grapes) on the Bruvo-distance dendrogram. The dendrograms indicate two groups of the Hungarian strains mixed with the others. The neighbour net analysis identified the same clusters and also reinforced the heterogeneity of Cluster 1 (Fig. 4). The stress for the nMDS configuration of the microsatellite data was high (at 0.4) indicating difficulty in displaying the relationships between the strains (data are not shown). Figure 3. View largeDownload slide Comparison of the UPGMA and NJ dendrograms generated from Bruvo distances of the microsatellite amplicons. Strain 11–60 was used as outgroup. For the explanation of symbols, see Fig. 1. Numbers 1 and 2 mark clusters. Figure 3. View largeDownload slide Comparison of the UPGMA and NJ dendrograms generated from Bruvo distances of the microsatellite amplicons. Strain 11–60 was used as outgroup. For the explanation of symbols, see Fig. 1. Numbers 1 and 2 mark clusters. Figure 4. View largeDownload slide Equal angle neighbor net deduced from the Bruvo distances of the microsatellite amplicons. Thick marks denote splits separating clusters. Double-line arrows mark splits separating subclusters. 1 and 2: clusters corresponding to the clusters of the NJ dendrogram shown in Fig. 3. Figure 4. View largeDownload slide Equal angle neighbor net deduced from the Bruvo distances of the microsatellite amplicons. Thick marks denote splits separating clusters. Double-line arrows mark splits separating subclusters. 1 and 2: clusters corresponding to the clusters of the NJ dendrogram shown in Fig. 3. We compared the positions of the 17 strains on our NJ tree generated from Bruvo distances of microsatellite with their positions on the tree of Masneuf-Pomarede et al. (2015) on the basis of the figure in their paper. We found that most of the strains are similarly located. For example, 10–372 and 10–375 are close to each other on both trees. However, 10–373 and 10–374 are apart from each other and the other two on both trees. Certain strains (11–1, 10–373, 11–20, 11–19, 11–149, 11–150 and 11–6) were grouped together in the Miscellanous group on the Masneuf-Pomarede et al. (2015) tree and in Cluster 1 on our Bruvo distance NJ tree (Fig. 3). Strains 11–4 and 10–374 [group ‘France’ on the Masneuf-Pomarede et al. (2015) tree] are further apart on our tree, where 11–4 is near the 11–479 and 11–101 strains (‘Spain/France’ group) and 10–374 is among the ‘Miscellanous’ strains. Comparison of mtDNA and microsatellite analyses Although the analysis of the mtDNA patterns and the two types of microsatellite analysis resulted in different tree topologies, we sought to determine whether there are strains in the examined collection which tend to group together on all trees. For that purpose, we aligned the mtDNA dendrograms in all possible pairwise combinations with the microsatellite dendrograms. We found little correspondence in the positions of the strains. Figures S3 and S4 (Supporting Information) show the alignments of the UPGMA dendrograms generated from the mtDNA RFLP patterns and the microsatellite size patterns. Very few strains had similar positions on both trees. Only four pairs of strains are together on both dendrograms: two wine isolates from Szegi (10–373 and 10–377), two grape isolates from Mád (11–135 and 11–138), two Drosophila isolates from Tarcal (10–1544 and 10–1529), two grape isolates from Spain (10–622 and 10–624) and an Italian isolate from wine with a French isolate from grape juice (11–6 and 11–8). Interestingly, even less similarity can be seen when the mtDNA dendrogram is compared with the Bruvo-distance microsatellite dendrogram. We also compared our data with those of Pfliegler et al. (2014) obtained previously by using different molecular markers. To better visualise the correspondence, we redraw their dendrogram using their original Newick file. We used 11–60 as outgroup. The alignment with our mtDNA UPGMA dendrogram is shown in Fig. S5 (Supporting Information). None of the mtDNA clusters can be recognised on it and very few strains are grouped together on both dendrograms: two Eszencia strains isolated in different locations of the Tokaj region (11–149, Tarcal and 11–152 Bodrogkeresztúr), two Tokaj strains isolated from different types of wines in different locations (11–144 from Eszencia in Erdőbénye and 10–376 from fermenting botrytised wine in Szegi), two Spanish isolates of different origin (10–624 and 11–1) and three grape isolates from two countries (11–4, 11–135 and 11–138). When our microsatellite dendrograms were compared with the dendrogram of Pfliegler et al. (2014), the correspondence was even poorer. Minimum spanning tree of the microsatellites From the matrix of the pairwise Bruvo distances, we also created a minimum spanning tree (MST) (Fig. 5). It displays three main clusters and four additional branches which consist of only one or two strains. The interior node with the largest number of edges is the isolate 10–375 derived from the Szegi region of Tokaj, Hungary. It has diversified in three major directions. Towards node 10–374 (also isolated in Szegi) which then split in two subclusters. One of them consists of two Tarcal isolates (isolated from sweet botrytised wine, Tarcal region of Tokaj), two Swiss strains and an isolate from water melon. The other subcluster contains the Tarcal isolate 11–148 (the node with the second largest numbers of edges) connected to a very diverse group of Californian, Italian, Spanish and Tokaj strains. The second cluster is connected to the central node through 10–377 (isolated from sweet botrytised must, Szegi region of Tokaj) and also incorporates strains of diverse geographical origins, including two Hungarian (Tokaj and Badacsony), French, Italian, Slovakian and Spanish regions. The third, smallest cluster contains strains from two Tokaj vineyards (Tarcal and Mád) and a Swiss wine region. No correlation between the positions of the strains on the tree and the substrate from which they were isolated can be seen. For example, the eight strains isolated from Drosophilas collected in the Tarcal vineyard of the Tokaj region are scattered over the entire tree. Figure 5. View largeDownload slide Minimum spanning tree analysis based on the Bruvo distances of the microsatellite amplicons. Each circle corresponds to a microsatellite pattern (genotype). The lines between circles indicate the similarity between profiles: normal line, one locus in common; bold line, more than one microsatellite loci in common. Figure 5. View largeDownload slide Minimum spanning tree analysis based on the Bruvo distances of the microsatellite amplicons. Each circle corresponds to a microsatellite pattern (genotype). The lines between circles indicate the similarity between profiles: normal line, one locus in common; bold line, more than one microsatellite loci in common. DISCUSSION In a previous biodiversity study, we already demonstrated by the analysis of a set of S. cerevisiae wine yeasts that different methods can result in different dendrogram topologies and may not group together strains of shared origin (Pfliegler and Sipiczki 2016). In the less investigated C. zemplinina, the diversity studies also indicate that the outcome of a diversity analysis is critically dependent on the selection of the molecular marker and the analysing algorithm. The most comprehensive analysis involving 163 strains from 28 vineyards of seven countries revealed high degree of microsatellite diversity and highlighted that the diversity of this species is shaped, at least in part, by geographical location but no specific genetic signatures could be associated with the different vineyards/wineries (Masneuf-Pomarede et al.2015). Other studies analysing different markers, smaller groups of isolates and covering fewer locations detected lower diversity (Pramateftaki et al.2008; Di Maio et al.2012; Tofalo et al.2012; Pfliegler et al.2014). These works either did not examine the relationships between the patterns and the isolation sites or detected no clear correlation. Interestingly, very few studies found correspondence between the polymorphism of genetic markers and the geographical origin of strains in other wine-related yeast species either. Versavaud et al. (1995) observed no correlation between marker patterns (electrophoretic karyotyping, mitochondrial DNA restriction fragment length polymorphism analysis and PCR amplification of Ty transposons) and geographical origin amongst S. cerevisiae strains isolated from 42 wine cellars in the Charentes area (Cognac region, France). An analysis of South-American S. cerevisiae strains isolated from wines of three geographically distant countries by electrophoretic karyotyping and mitochondrial DNA restriction analysis detected some correspondence between the molecular patterns and the geographical origin but found that such a correlation can easily be lost (Martinez et al.2004). Guillamon, Barrio and Querol (1996) found that certain Spanish red wine strains (but not the white-wine strains) grouped according to their geographical origin, when their electrophoretic karyotypes and mitochondrial DNA RFLP profiles were compared (Guillamon, Barrio and Querol 1996). No clear correlation was found between the chromosomal patterns and the geographical locations of sample collection among Saccharomyces strains isolated in four Hungarian wine-growing regions either (Csoma et al.2010). In a large group of Hanseniaspora uvarum strains isolated in five continents, most South African isolates formed a distinct cluster on the microsatellite dendrogram, but most French strains clustered on the basis of the year of isolation instead of their geographical origin (Albertin et al.2016). The microsatellite analysis of 110 Torulaspora delbrueckii strains separated most wine isolates from those isolated from the nature or other biotechnological processes, but the group of the wine isolates was not structured according to the geographical origin (Albertin et al.2014). In this study, the analysis of two molecular markers, microsatellites and mtDNA, in a group of 41 C. zemplinina strains by various bioinformatics tools also resulted in certain cases different clustering, and none of the dendrograms grouped the strains fully consistently with their geographical origin. Deliberately, the strains were selected for the project so that their majority was from one wine-growing region. These strains were isolated from wines of the Tokaj region (Hungary), where the type strain of C. zemplinina had been isolated (Sipiczki 2003) and this yeast is a regular component of the yeast communities fermenting botrytised wines (Csoma and Sipiczki 2008). In the same region, strains were also isolated from Drosophila flies and larvae which we assume might contribute to the survival of this asporogenic yeast between vintage seasons. For each strain, the size of five microsatellite loci found highly variable in a previous study (Masneuf-Pomarede et al.2015) and the RFLP pattern of the mitochondrial DNA were determined. From the experimental results, distance matrices were generated and analysed with UPGMA, NJ, neighbour net, MST and nMDS algorithms. Most dendrograms generated by different algorithms showed rather limited similarity with each other. The different topologies of the UPGMA and NJ trees inferred from the same distance matrices can be attributed to the different mode of branch-length calculation. UPGMA assumes equal rates of evolution on all branches, whereas the NJ algorithm allows unequal rates of changes on the branches (Saitou and Nei 1987). If rates on different branches are markedly unequal, the branching orders produced by the two methods will differ. The situation is further complicated by the possibility of the calculation of microsatellite distance matrices in two ways: from the size differences of the amplified fragments and from the differences of their repeat numbers. According to several authors, the longer and purer the repeat, the higher the mutation frequency, whereas shorter repeats with lower purity have a lower mutation frequency (Vieira et al.2016). We computed distance matrices in both ways and obtained rather different tree topologies. On the dendrograms obtained in the first case, the majority of the Hungarian strains formed a separate group, whereas in the second case the non-Hungarian isolates were scattered on the dendrogram between the two major groups of Hungarian isolates. In principle, the dendrogram inferred from the repeat number differences (Bruvo distances) can be assumed to show better the relationships of the strains. It can be traced back to the replication slippage which is one of the main mechanisms affecting the microsatellites. It is a DNA replication error in which the template and nascent strands are mismatched. This means that the template strand can loop out, causing contraction. The nascent strand can also loop out, leading to repeat expansion. The process is involving a gain or loss of one or more repeat units (Vieira et al.2016). To the observed length polymorphism may also contribute the so-called interrupting motifs, which means that a sequence of a few base pairs is inserted into the motif from which it follows that the sequences will deviate from the repeating motif. Certain microsatellite alleles sequenced from the C. zemplinina type strain and used in this study have such interruptions (Masneuf-Pomarede et al.2015). The ignorance of their presence risks inaccurate calculation of Bruvo distances. As precise calculation can be done only when all amplified alleles are sequenced, most works based on locus amplification ignore this aspect. Since we ourselves used this practice, we cannot take a definitive stand on which mode of distance calculation can result in more realistic topologies. The MST generated from the Bruvo-distance matrix of the microsatellites also failed to show good correspondence between the position of the strains on the tree and their geographical origin. An MST is an acyclic graph that consists of nodes (strains) connected by edges that link together nodes by the shortest possible distance reflecting thus the concept of minimal evolution. By allowing individuals (strains) to be placed in interior nodes, MST is assumed to better convey the peculiarities of short-term intraspecific evolution than the conventional trees (Excoffier and Smouse 1994). Although it linked numerous Tokaj strains together, the lineages of the Tokaj strains were interspersed with strains isolated in remote wine-growing regions, and certain Tokaj strains were placed far from the major groups and close to strains that could hardly have had common recent history with them. The inconsistency between the microsatellite and the mtDNA tree topologies can be attributed to several factors, such as different impact of the selection pressure on these markers and the different rates and mechanisms of their changes. Being involved in metabolic processes and stress tolerance (e.g. Carmona-Gutierrez et al.2012), the mitochondria are likely to be under stronger selection pressure than the physiologically neutral or less important microsatellite loci (e.g. Reis et al.2017). In general, the mitochondrial DNA appears to mutate at a greater rate than the nuclear DNA in many organisms and most mutations are base substitutions and small insertions/deletions (e.g. Lynch et al.2008). In contrast, microsatellites mutate to novel length variants by replication slippage, with the mutation rate generally increasing dramatically with the number of repeats at the locus (Wierdl, Dominska and Petes 1997), most probably irrespective of which environmental condition is changing. Thus, microsatellite changes occur more accidentally and at variable rates depending on the locus size. The mutation rate of these elements could be between 103 and 106 per cell generation, which are 10 orders of magnitude greater than that of point mutations (Gemayel et al.2012). However, it seems that eukaryotes that have more DNA repeats might provide a molecular device for faster adaptation to environmental stresses (Li et al.2004). Consistent with this, we found somewhat better correspondence between the positions of the strains and their geographical origin on the mtDNA dendrograms than on the microsatellite trees. This seems to be confirmed by the nMDS ordinations of the mtDNA RFLP profiles. NMDS is an ordination technique which is a complex numerical algorithm. It focuses on the rank order of the dissimilarity matrix and requires the final configuration to contain distances that follow the rank of the original dissimilarity matrix as closely as possible (Zhu and Yu 2009). The mtDNA dendrograms showed better correspondence also with certain isolation sources. For example, they grouped five of the eight Drosophila isolates together. In contrast, the best grouping of the strains isolated from Tokaj Eszencia was observed on the microsatellite dendrogram inferred from the Bruvo distances of the microsatellite patterns. In the case of strains isolated in closely located vineyards and wineries, neither method could clearly separate the grape-born and the wine-born isolates. As most strains analysed in this work were included in previous diversity studies, we could compare their relative positions on our dendrograms and on the dendrograms constructed in those studies. Our analyses reinforced neither the results of the previous UPGMA analysis of combined band patterns obtained with non-specific mini/microsatellite and RAPD primers (Pfliegler et al.2014) nor those (only partially) obtained with NJ analysis of the Bruvo distances of 10 species-specific microsatellites (Masneuf-Pomarede et al.2015). However, when interpreting the poor correspondence one has to take into consideration that the three studies examined very different sets of strains, analysed different markers and outgroup was used only in our study. Nevertheless, it is worth mentioning that some isolates (11 out of 18) were grouped the same way in both the Masneuf-Pomarede et al. (2015) and our microsatellite NJ trees. The results presented in this work and their comparisons to previous analyses demonstrate that different markers and different clustering methods can result in different groupings of the same strains. The observed differences between the topologies also indicate that the positions of the strains do not necessarily reflect their real historical relationships. Strains placed close to one another on a microsatellite tree can be assigned to different clusters on the mtDNA tree and vice versa. 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FEMS Yeast ResearchOxford University Press

Published: Mar 6, 2018

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