What does the 34/70 in Saccharomyces pastorianus Weihenstephan 34/70 stand for?

What does the 34/70 in Saccharomyces pastorianus Weihenstephan 34/70 stand for?

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I've searched everywhere.
No Wikipedia page.
No information on NCBI.
I searched all occurrences of 34/70 in some primary research articles!
The best I've found is this brewery forum where someone asked the same question.

And the user rockfish42 answered:

No idea why they use that number, but it's the catalog number at Weihenstephan's hefebank.

I went to the Yeastbank website at Weihenstephan for some info. The keyword here is "Stamm," which is German for stem, clade, clan, or strain. So, I would take this to mean that the 34/70 is an isolate (#70) of strain 34. Two of 34/70's strengths, according to the link above are it makes clean beer and gives a pleasant taste profile due to its low yeast-like aroma in the finished beer. I can attest to that firsthand, having had on numerous occasions the pleasure of partaking of Weihenstephaner beer in its home city of Freising.

I am not sure why you say there is no information… a quick Google search returned a few interesting pages…

In this paper:

Progress in Metabolic Engineering of Saccharomyces cerevisiae - Nevoigt, Microbiol Mol Biol Rev. 2008

the author says:

The identification of the entire genomic sequence of a commonly used lager brewer's yeast strain, i.e., Weihenstephan Nr. 34 (34/70), represents a breakthrough in the molecular analysis of lager brewer's yeast.

So, it would look like 34/70 is just a catalogue number, with no specific meaning.

Curiously, according to the Wikipedia page on Saccharomyces pastorianus:

S. pastorianus never grows above 34 °C (93 °F)

So, I cannot exclude the hypothesis that 34 could come from there although, well, I personally propend for the catalogue number.

Other interesting links:

The paper about the S. pastorianus genome sequencing:
Genome sequence of the lager brewing yeast, an interspecies hybrid. - Nakao et al., DNA Res. 2009

An article comparing two different strains of S. pastorianus, 34/70 and 34/78 (again, catalog number hypothesis seems to be the most obvious explanation)

Molecular species of phosphatidylethanolamine from continuous cultures of Saccharomyces pastorianus syn. carlsbergensis strains. - Tosch, Yeast. 2006

The NCBI taxonomy page (entry #520522)

Saccharomyces pastorianus: genomic insights inspiring innovation for industry

A combination of biological and non-biological factors has led to the interspecific hybrid yeast species Saccharomyces pastorianus becoming one of the world's most important industrial organisms. This yeast is used in the production of lager-style beers, the fermentation of which requires very low temperatures compared to other industrial fermentation processes. This group of organisms has benefited from both the whole-genome duplication in its ancestral lineage and the subsequent hybridization event between S. cerevisiae and S. eubayanus, resulting in strong fermentative ability. The hybrid has key traits, such as cold tolerance and good maltose- and maltotriose-utilizing ability, inherited either from the parental species or originating from genetic interactions between the parent genomes. Instability in the nascent allopolyploid hybrid genome may have contributed to rapid evolution of the yeast to tolerate conditions prevalent in the brewing environment. The recent discovery of S. eubayanus has provided new insights into the evolutionary history of S. pastorianus and may offer new opportunities for generating novel industrially-beneficial lager yeast strains. Copyright © 2014 John Wiley & Sons, Ltd.


Studies on inducible homologous promoters for the regulation of gene expression in self-cloning yeasts are limited. Existing research focuses mainly on induction triggered by additives such as copper and galactose (West, Yocum and Ptashne 1984, Labbe and Thiele 1999, Farhi et al. 2006) or induction that occurs during sequential utilization of carbohydrates (Lagunas 1993). The addition of substances such as copper or galactose is not permitted for the food and beverage industry their use is regulated in the union list of food additives (Commission Regulation No. 1129/2011). In addition, the carbohydrate and free amino nitrogen (FAN) compositions of the wort differ from stock to stock (Lea, Piggott and Piggott 2003). Therefore, the use of promoters induced by these conditions is not favourable.

The stress responses of yeast and their associated gene regulation could be an option for successfully targeting the induction of gene expression during the industrial fermentation processes. Industrial yeasts adapt to different stresses during the fermentation process, including stresses like osmotic pressure, insufficient supply of FAN, temperature shifts and elevated concentrations of ethanol, under industrial conditions in particular (Gibson et al. 2007). This adaption is generated by different stress-response genes, which are regulated by transcription-factor binding sites on their promoters and transcription factors, including the stress response element, which binds Msn2/4 transcription factors the heat shock element, which is controlled by Hsf1 and the AP-1-responsive element, which link to the transcription factors Gcn4 and Yap (Estruch 2000 Kandror et al. 2004 Aguilera, Randez-Gil and Prieto 2007 Ma and Liu 2010 Schade et al. 2004). Few studies have focused on gene regulation during shifts to cold or near freezing temperatures (Kondo and Inouye 1991 Kowalski, Kondo and Inouye 1995 Sahara, Goda and Ohgiya 2002 Becerra et al. 2003 Homma, Iwahashi and Komatsu 2003 Schade et al. 2004 Murata et al. 2006) or high temperatures (Estruch 2000 Izawa et al. 2008). Genes involved in trehalose and glycogen production are upregulated during shifts to low temperature (TPS1 and TPS2), as are genes associated with cell wall mannoproteins (TIP-related genes). A ≥2-fold increase in the induction of TPS1, TPS2, UBI4 and SSA3 has been reported after a temperature shift to 10°C (Sahara, Goda and Ohgiya 2002). Exposure to 4°C results in a >2-fold upregulation of TIR1, TIR2, TPS1, TIP1 and SSA3 (Homma, Iwahashi and Komatsu 2003). Further analysis of gene expression after temperature shifts to near freezing (4°C) shows the highest expression of TIR1 and TIR2 at the beginning of the shock situation (with a fold change of 9.0 and 6.2, respectively, after 6 h), with much smaller fold changes of 3.2 and 1.9, respectively, after 48 h (Murata et al. 2006). Moreover, TIR1 and TIR2 are strongly induced by a decrease in temperature, which is consistent with their low basal expression during fermentation (Kowalski, Kondo and Inouye 1995). Apart from these, genes from the heat shock protein (HSP) family are also induced during cold shock (Homma, Iwahashi and Komatsu 2003 Murata et al. 2006 Izawa et al. 2008). These proteins function as molecular chaperones to refold damaged proteins, protect thermally damaged proteins from aggregation and contribute to cell wall restructuring (Verghese et al. 2012). A higher concentration of ethanol also leads to stress that is associated with induced gene expression. A minimum of 4% (v/v) ethanol has been reported to be needed for a notable induction of HSP expression (Piper et al. 1994 Piper 1995). However, subsets of HSP genes show ideal expression patterns at different ethanol concentrations (Piper et al. 1994). Further, the promoter of TPS1 has been used for ethanol-induced yeast flocculation (Li et al. 2012).

Self-cloning yeasts offer different advantages for industrial application during food and beverage production. For example, research on wort fermentation has been focused on enhanced flocculation after fermentation (Ishida-Fujii et al. 1998), reduced maturation time (Kusunoki and Ogata 2012) and enhanced glutathione content and foam stability (Wang, He and Zhang 2007 Wang et al. 2008, 2009). In contrast to genetic modification, self-cloning does not result in genetically modified organisms (Fischer, Procopio and Becker 2013). Due to self-cloning, only homologous nucleic acids are utilized. In case of brewing yeast, research does not focus heavily on the lager yeast strain Saccharomyces pastorianus var. carlsbergensis however, this strain contributes to 90% of the worldwide beer market (Kodama, Kielland-Brandt and Hansen 2006 Saerens, Duong and Nevoigt 2010). The lager yeast is an allotetraploid hybrid of the ale yeast S. cerevisiae and an S. eubayanus strain (Bing et al. 2014) and due to the genetically differences to the ale yeast more investigation is necessary.

In the present study, a total of 10 different native promoters of temperature-induced genes were evaluated during the brewing process. In addition to promoters of the HSP-gene family (Fischer et al. 2016), promoters of the TIP-related gene family were also considered due to the variety of results concerning temperature shifts to near freezing by laboratory yeasts, as mentioned above. In addition to the induction of these promoters by different temperature shifts, the influence of different ethanol contents was also investigated. To understand gene regulation during these stress situations, an enhanced green fluorescence protein (EGFP)-based method was used under industrial fermentation conditions (Fischer et al. 2016).


Based on the new findings, it was possible in Finland at the beginning of 2015 to create several new lines of bottom-fermenting yeast through artificially generated hybridization of S. eubayanus with S. cerevisiae . It is hoped that a broad selection of starting strains of the two parent species will result in favorable properties not previously achieved for the new types: processing of maltotriose , production of higher alcohols as aromatic carriers, etc. New hybridizations of these two or other Saccharomyces species are to be expected that the range of bottom-fermented beers will expand significantly in the future, even if Saccharomyces eubayanus itself should not find commercial use.

Dothideomycetes Edit

  • Aureobasidium pullulans, A. melanogenum, A. subglacialeand A.namibiae, polyextremotolerant (2014 [1] )
  • Hortaea werneckii, extremely halotolerant (2013 [2] 2017 [3] )
  • Leptosphaeria maculans, plant pathogen (2011 [4] )
  • Macrophomina phaseolina, plant pathogen (2012 [5] )
  • Mycosphaerella fijiensis, plant pathogen (2007 [6] )
  • Mycosphaerella graminicola IPO323, wheat pathogen (2008 [7] )
  • Phaeosphaeria nodorum SN15, wheat pathogen (2005 [8] )
  • Pyrenophora tritici-repentis Pt-1C-BFP, wheat pathogen (2007 [9] )

Eurotiomycetes Edit

  • Ajellomyces capsulataseveral strains, Darling's disease (2009, unpubl. [10] )
  • Ajellomyces dermatitidisseveral strains (2009, unpubl. [11] )
  • Arthroderma benhamiaeCBS 112371, skin infection (2010, unpubl. [12] )
  • Arthroderma gypseumCBS 118893, athlete's foot (2008 [13] )
  • Arthroderma otaeCBS 113480, athlete's foot (2008 [13] )
  • Aspergillus aculeatus ATCC16872, industrial use (2010 [14] )
  • Aspergillus carbonarius ITEM 5010, food pathogen (2009 [15] )
  • Aspergillus clavatus Strain:NRRL1 (2008 [16] )
  • Aspergillus fumigatus Strain:A1163, human pathogen (2008 [16] )
  • Aspergillus fumigatus Strain:Af293, human pathogen (2005 [17] )
  • Aspergillus kawachii IFO 4308, food industry (2011 [18] )
  • Aspergillus nidulans Strain:FGSC A4, model organism (2005 [19] )
  • Aspergillus niger Strain:ATCC 1015 (DOE Joint Genome institute)
  • Aspergillus niger Strain:CBS 513.88, industrial use (2007 [20] )
  • Aspergillus oryzae Strain:RIB40, industrial use (2005 [21] )
  • Aspergillus terreus NIH 2624, statin producer and pathogen (2005, unpubl. [22] )
  • Coccidioides immitis, human pathogen, Valley fever (2009 [23] )
  • Coccidioides posadasiiC735 delta SOWgp, human pathogen, Valley fever (2009 [23] )
  • Neosartorya fischeri Strain:NRRL181 (2008 [16] )
  • Paracoccidioides brasiliensis, several strains, human pathogen (2007 [24]
  • Penicillium chrysogenum Strain: Wisconsin54-1255, industrial use (2008 [25] )
  • Penicillium digitatum Strain PHI26 (2012 [26] )
  • Penicillium digitatum Strain Pd1 (2012 [26]
  • Talaromyces marneffei, human pathogen (2011 [27]
  • Uncinocarpus reesii (2009 [23] )

Leotiomycetes Edit

  • Blumeria graminis ffsp hordei Strain:DH14, plant pathogen (2010)
  • Botrytis cinerea (Botryotinia fuckeliana) Strain:B05.10 and T4, plant pathogen (2011 [28] )
  • Glarea lozoyensis (2012 [29] )
  • Sclerotinia sclerotiorum Strain:1980 (2011 [28] )
  • Ascocoryne sarcoides Strain: NRRL50072 (2012 [30] )

Pezizomycetes Edit

Saccharomycetes Edit

  • Ashbya gossypii Strain:ATCC 10895, plant pathogen (2004 [33] )
  • Candida albicans Strain:SC5314, human pathogen (2004 [34] )
  • Candida albicans Strain:WO-1, human pathogen (2009 [35] )
  • Candida dubliniensis CD36, human pathogen (2009 [36] )
  • Candida glabrata Strain:CBS138, human pathogen (2004 [37] )
  • Candida guilliermondii, human pathogen (2009 [35] )
  • Candida lusitaniae, human pathogen (2009 [35] )
  • Candida parapsilosis, human pathogen (2009 [35] )
  • Candida orthopsilosis'', human pathogen (2012 [38] )
  • Candida tropicalis, human pathogen (2009 [35] )
  • Debaryomyces hansenii Strain:CBS767, industrial use (2004 [37] )
  • Debaryomyces hansenii Strain:MTCC 234, salt-tolerant (2012 [39] )
  • Dekkera bruxellensis Strain:CBS2499, wine yeast (2012 [40] )
  • Hansenula polymorpha NCYC 495 leu1.1, industrial use (2010 [41] )
  • Kluyveromyces aestuariiATCC 18862 (2010, unpubl. [42] )
  • Kluyveromyces lactis Strain:CLIB210, industrial use (2004 [37] )
  • Kluyveromyces wickerhamiiUCD 54-210 (2010, unpubl. [43] )
  • Lachancea kluyveri (Saccharomyces kluyveri) NRRL Y-12651, plant pathogen (2009 [44] )
  • Lodderomyces elongisporus, human pathogen (2009 [35] )
  • Naumovozyma castellii Strain:AS 2.2404, CBS 4309 (Saccharomyces castellii 2003, [45] 2011 [46] )
  • Naumovozyma dairenensis Strain:CBS 421 (2011 [46] )
  • Saccharomyces bayanus (2003, [45][47] 2011 [48] )
  • Saccharomyces arboricolus (2013, [49] )
  • Saccharomyces cerevisiae Strain:JAY291, industrial/model (2009 [50] )
  • Saccharomyces cerevisiae Strain:S288C, industrial/model (1996 [51] )
  • Saccharomyces cerevisiae Strain:Sigma1278b, industrial/model (2010 [52] )
  • Saccharomyces kudriavzevii (2003 [45][48] )
  • Saccharomyces mikatae (2003, [45][47] 2011 [48] )
  • Saccharomyces paradoxus (2003 [47] 2009 [53] )
  • Saccharomyces pastorianusWeihenstephan 34/70, industrial, beer (2009 [54] )
  • Scheffersomyces stipitis (Pichia stipitis) CBS 6054, lignin/xylose degrader (2007 [55] )
  • Spathaspora passalidarum NRRL Y-27907, model xylose fermenter (2010 [56] )
  • Tetrapisispora phaffii van der Walt Y 89, CBS 4417 (2011 [46] )
  • Torulaspora delbrueckii Strain:Wallerstein 129, CBS 1146 (2011 [46] )
  • Vanderwaltozyma polysporaDSM 70294 (2007 [57] )
  • Yarrowia lipolytica Strain:CLIB99, industrial use (2004 [37] )
  • Zygosaccharomyces rouxii strain CBS732, food spoiler (2009 [58] )

Schizosaccharomycetes Edit

  • Schizosaccharomyces japonicus yFS275, model for invasive growth (2006 [59] )
  • Schizosaccharomyces pombe Strain:972h, model eukaryote (2002 [60] )

Sordariomycetes Edit

  • Colletotrichum graminicola, corn pathogen (2012 [61] )
  • Colletotrichum higginsianum, Arabidopsis thaliana pathogen (2012 [61] )
  • Chaetomium cochliodes Strain:CCM F-232, soil fungus (2016 [62] )
  • Chaetomium globosum Strain:CBS 148.51, soil fungus (2005 [63] )
  • Chaetomium thermophilum Strain:CBS 144.50, soil fungus (2011 [64] )
  • Fusarium oxysporum f. sp. lycopersici 4287, human/plant pathogen (2010 [65] )
  • Gibberella moniliformis 7600, plant pathogen (2010 [65] )
  • Gibberella zeae PH-1, plant pathogen (2008 [66] )
  • Gaeumannomyces graminis triticiR3-111a-1 (2010, unpubl. [67] )
  • Grosmannia clavigera kw1407, plant pathogen (2011 [68] )
  • Magnaporthe grisea, plant pathogen (20054 [69] )
  • Metarhizium acridum CQMa 102, and
  • Metarhizium anisopliae ARSEF 23, insect pathogens (2011 [70] )
  • Neurospora crassa, model eukaryote (2003 [71] )
  • Neurospora tetrasperma FGSC 2508 mat A, model (2010 [72] )
  • Nectria haematococcaMPVI, plastic/pest./lignin degrader (2009 [73] )
  • Podospora anserina:S mat+[74]
  • Sporotrichum thermophile, thermophilic cellulose degrader (2010 [75] )
  • Thielavia terrestris, model thermophile/industrial (2010 [76] )
  • Trichoderma atroviride, industrial/soil, (2010 [77] )
  • Trichoderma reeseiQM6a, biomass-degrading (2008 [78] )
  • Trichoderma virens Gv29-8, industrial/pathogen (2007 [79] )
  • Verticillium albo-atrum VaMs.102, plant pathogen (2008, unpubl. [80] )

Agaricomycetes Edit

  • Agaricus bisporus var. bisporus Strain:H97, Champignon (2009 [81] )
  • Agrocybe aegerita, ack Poplar or Sword-belt Mushroom (2018 [82] ) )
  • Auricularia delicata (2012 [83] )
  • Auricularia heimuer, Chinese Auricularia (2019 [84] )
  • Coniophora puteana (2012 [83] )
  • Coprinopsis cinerea (Coprinus cinereus), model organism for multicellular fungi (2010 [85] )
  • Dichomitus squalens (2012 [83] )
  • Fibroporia radiculosa Strain:TFFH 294 (2012 [86] )
  • Fomitiporia mediterranea (2012 [83] )
  • Fomitopsis pinicola (2012 [83] )
  • Gloeophyllum trabeum (2012 [83] )
  • Hebeloma cylindrosporum
  • Heterobasidion annosum, plant pathogen (2009 [87] )
  • Laccaria bicolor Strain:S238N-H82, mycorrhiza (2008 [88] ) , Shiitake mushroom (2016 [89] )
  • Moniliophthora perniciosa, Witches' Broom Disease of cacao (2008 [90] )
  • Phanerochaete chrysosporium Strain:RP78, mycoremediation (2004 [91] )
  • Piriformospora indica endophyte (2011 [92] )
  • Pleurotus ostreatus, industrial/lignin degrader (2010 [93] )
  • Pleurotus tuber-regium, White-rot fungus (2018 [94] )
  • Postia placenta, cellulose degrader (2008 [78][95] )
  • Punctularia strigosozonata (2012 [83] )
  • Schizophyllum commune, mushroom (2010 [96] )
  • Serpula lacrymans, plant pathogen (2011 [97] )
  • Stereum hirsutum (2012 [83] )
  • Trametes versicolor (2012 [83] )
  • Wolfiporia cocos (2012 [83] )

Pucciniomycetes (formerly Urediniomycetes) Edit

  • Melampsora laricis-populina, pathogen of populars (2008 [98] )
  • Puccinia graminis f. sp. tritici, plant pathogen (2011 [99][100][101] )
  • Puccinia triticina 1-1 BBBD Race 1, pathogen of wheat( [101] )
  • Rhodotorula graminis strain WP1, plant symbiont (2010 [102] )
  • Sporobolomyces roseus, associated with plants ( [103] )

Tremellomycetes Edit

  • Cryptococcus (Filobasidiella) neoformans JEC21, human pathogen (2005, [104] other strains unpubl. [105] )
  • Dacryopinax sp. (2012 [83] )
  • Tremella mesenterica (2012 [83] )

Ustilaginomycetes Edit

  • Malassezia globosa CBS 7966, dandruff-associated (2007 [106] )
  • Malassezia restricta CBS 7877, dandruff-associated (2007 [106] )
  • Sporisorium rellianum, plant pathogen (2010 [107] )
  • Ustilago maydis, plant pathogen (2006 [108] )

Wallemiomycetes Edit

Chytridiomycota includes fungi with spores that have flagella (zoospores) and are a sister group to more advanced land fungi that lack flagella. Several chytrid species are pathogens, but have not had their genomes sequenced yet.

Self-cloning brewing yeast: a new dimension in beverage production

Since the mid-1990s, biotechnology has advanced, and there has been an increased focus on using genetically modified yeast in the production of fermented beverages and the manufacturing of bioethanol. Yeast is the primary microorganism for fermented beverages such as beer, wine and sake. However, existing individual strains will not completely fulfill future demands for an efficient and high-quality fermentation. In this case, several research groups have been working on genetic modifications of yeast to create an up-to-date application. Genetically modified organisms (GMO) such as yeast, crops and plants in the food and beverage production are not desired by the consumer. A possible solution to overcome the consumer distaste of products labeled as containing GMO could be the application of self-cloning yeasts. Thus, connotated, the modification of the genome occurs without heterologous DNA. This review is an overview of current research regarding the use of self-cloning yeast in brewing, wine making, baked goods and sake production. The main focus of this paper concerns the possibilities of promoter usage and the construction of self-cloning yeast and the monitoring of self-cloning yeast.

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68.4% — Mecca Grade Estate Malt Pelton: Pilsner-style Barley Malt — Grain — 1.8 SRM
26.1% — Weyermann Barke Pilsner — Grain — 1.8 SRM
4.7%) — BestMalz Chit Malt — Grain — 1.3 SRM
0.9%) — Weyermann Caramunich II — Grain — 63 SRM

Miscs (RO Water)
1.25 g — Calcium Chloride (CaCl2) — Mash
1.25 g — Canning Salt (NaCl) — Mash
2 g — Epsom Salt (MgSO4) — Mash
2.1 g — Gypsum (CaSO4) — Mash
8.5 ml — Lactic Acid 88% — Mash

Protein Peptidase — 126 °F — 10 min
Temperature — 151 °F — 40 min
Mash Out — 171 °F — 10 min

2.5 oz (22 IBU) — Tettnang 3.5% — Boil — 60 min
1.75 oz (15 IBU) — Tettnang 3.5% — Boil — 45 min
1.25 oz (1 IBU) — Hersbrucker 2.3% — Aroma — 20 min hopstand @ 180 °F
1.25 oz (2 IBU) — Tettnang 3.5% — Aroma — 20 min hopstand @ 180 °F

0.53 oz — Tettnang 4.5% — Dry Hop — day 2
0.53 oz — Tettnang 3.5% — Dry Hop — day 2
1.2 oz — Hersbrucker 2.3% — Dry Hop — day 10
1.2 oz — Tettnang 3.5% — Dry Hop — day 10

Fermentis W-34/70 and Tum 35

Primary — 53 °F — 7 days
Primary — 58 °F — 3 days
Conditioning — 33 °F — 14 days


Analysis of maltose and maltotriose utilization by Saccharomyces strains

To analyse the maltose and maltotriose utilization patterns of a fairly large number of laboratory and industrial yeast strains, while also taking into account the high price of maltotriose, we decided to use 96-well microplates and a Tecan GENios reader to obtain growth curves for the 53 different yeast strains described in Tables 1 and 2. These yeast strains included nine laboratory and 20 industrial S. cerevisiae strains, as well as one S. bayanus and three S. cerevisiae × S. bayanus hybrids, and 20 lager brewing strains of the species S. pastorianus. All the strains analysed utilized maltose efficiently, reaching the stationary phase of growth with this carbon source after 15–30 h of incubation, although the rate of growth and the maximal OD reached varied to different extents depending on the strain analysed (Fig. 1).

Growth on rich YP medium containing 2% maltose (left panel) or maltotriose (right panel) by representative yeast strains (a) belonging to Group 1 (G1), or (b) belonging to Group 2 (G2) and Group 3 (G3). G1: () 1403-7A () CBS1513 () CBS1260 () DBVPG6283 () WY2124 and () CLIB180 G2: () LCM001 () SA-1 and () CBS1503 G3: () LCM003 () CBS1486 and () GDB-379.

However, three different patterns of growth during maltotriose utilization by these same yeast cells were observed. The 27 strains belonging to Group 1 – cells that efficiently used both maltose and maltotriose as carbon sources for growth (Fig. 1a) – included only nine of the 29 S. cerevisiae strains (two laboratory, six baker’s and one ale brewing yeast strain), but included the majority (17 out of 20) of the S. pastorianus lager brewing yeasts and also the S. pastorianus (monacensis) distiller’s yeast (Table 3). All these strains reached the stationary phase of growth in 15–30 h of incubation in the presence of maltotriose, and the analysis of ethanol production by several strains belonging to this Group 1 revealed efficient maltose and maltotriose fermentation, with ethanol concentrations reaching 5–7 g l −1 at the moment of sugar exhaustion from the medium (data not shown).

Group 1 Efficient maltose and maltotriose utilization
Strains 1403-7A CEN.PK2-1C G11 G13 G14 G15 G30 G35 GSY924 CBS1174 CBS1483 CBS1484 CBS2156 CBS6903 CLIB180 DBVPG6033 DBVPG6047 DBVPG6257 DBVPG6282 DBVPG6283 DBVPG6284 DBVPG6285 DBVPG6560 LBCC-L52 W-34/70 WY2124, WY2206
Group 2 Efficient maltose utilization, and slow/delayed maltotriose utilization
Strains CAT-1 G34 LBCC-A3 LCM001 PE-2 SA-1 UCD522 UCD819 VR-1 CBS2440 DBVPG6258 DBVPG6261
Group 3 Efficient maltose utilization, no maltotriose utilization
Strains CMY001 GSY2 GDB-178 GDB-379 LCM003 RM11-1a Y55 YJM789 UFMG-A905 UFMG-A1007 CBS7001 Y251 Y165

The yeast strains belonging to Group 2 (12 strains, see Table 3) had a very different pattern of maltotriose utilization when compared to the strains in Group 1 (Fig. 1b). These yeasts utilized and fermented maltose efficiently, but when cultivated in the presence of maltotriose a very slow growth rate was observed in some cases, the growth rate improved only after several days of incubation in this carbon source. The majority of strains belonging to this group were industrial S. cerevisiae strains (only one, LCM001, was a laboratory strain), as well as three S. pastorianus brewing strains. Finally, the remaining yeast strains (a total of 13 strains, including the eight remaining S. cerevisiae laboratory strains) belonged to Group 3 (see Table 3) and were characterized by their complete inability to grow on maltotriose (see Fig. 1b), while maltose fermentation and utilization by these cells was normal. Within this group was also the S. bayanus var. uvarum CBS7001 yeast strain as well as two S. cerevisiae × S. bayanus hybrid strains used for wine and cider production.

Microarray karyotyping of Saccharomyces cerevisiae strains

We hypothesized that gene CNVs between the yeast strains may account for some of the differences in observed maltotriose utilization and fermentation efficiency, and thus we performed aCGH on each of the strains to determine whether there were observable CNVs. As microarray karyotyping detects changes in DNA copy number relative to a reference genome (in this case the genome of laboratory strain S288C), gene duplications or deletions that result in CNV can be easily detected. As shown in Fig. 2a, the aCGH results can easily detect the presence of a deleted AGT1 gene in the genome of strain LCM001, but not in the otherwise isogenic wild-type strain 1403-7A from which it derives, while the same data indicate that these two strains have amplifications relative to S288C of both the MALx1 and MALx2 genes (known from previous work to be represented by the MAL31 maltose permease, and the MAL12 and MAL32 maltases present in the genome of strain S228C, see Feuermann et al. 1995 and Volckaert et al. 1997 ).

Correlation between the microarray karyotyping of the laboratory strain 1403-7A and its isogenic Δagt1 strain LCM001 (a). The microarray comparative genome hybridization (aCGH) data (in log2 of the R/G ratio) for the MAL genes analysed are highlighted. Chromosomal blotting (b) of the indicated yeast strains with the AGT1 gene (upper panel) or MAL31 gene (lower panel) as probe, and (c) correlation of copy number variation of the AGT1 (open symbols) and MALx1 (black symbols) genes, as determined by aCGH (expressed as log2 of the R/G ratio) and chromosomal blotting (log2 of gene copy number per diploid genome), present in strains CAT-1 (circles), PE-2 (triangles), VR-1 (diamonds), SA-1 (squares), 1403-7A (inverted triangles), LCM001 (stars) and UFMG-1007 (crosses). For the chromosomal blotting, an arbitrary value of <0·05 was assumed for strains lacking the AGT1 gene.

Chromosome blotting and hybridization with MAL31 and AGT1 probes revealed indeed the presence of several (MAL21, MAL31 and MAL41) maltose permease genes in the chromosomes of these two (1403-7A and LCM001) strains, while, as expected, only strain LCM001 lacked the AGT1 permease (Fig. 2b). Most of the S. cerevisiae strains analysed also contained several maltose permease genes. For example, strains VR-1 and SA-1 had maltose permeases on both chromosomes VII (MAL11) and chromosome II (MAL31), while strains CAT-1 and UFMG-A1007 also had these two maltose transporters genes but were heterozygous for chromosome VII, having both the AGT1 and MAL11 permease genes in each of the two chromosomes of these diploid yeast strains (see data for strain VR-1 and CAT-1 in Fig. 2b). Strain PE-2 was similar to strains CAT-1 and UFMG-A1007 (AGT1/MAL11 and MAL31), but also contained the MAL41 permease (chromosome XI) in its genome (Fig. 2b). Indeed, a good correlation was observed between gene CNV of these α-glucoside transporters present in the genome of the yeast strains, as revealed by chromosomal blotting, and the aCGH data for the corresponding AGT1 and MAL31 genes (Fig. 2c).

The aCGH data of MAL genes present among selected S. cerevisiae yeast strains shown in Fig. 3 indicates that the copy number of MPH2-MPH3 genes probably has little influence on maltotriose (and maltose) utilization by the S. cerevisiae yeasts analysed, as strains lacking these two genes were found among all three groups of strains with differing maltotriose utilization profiles described previously. Regarding the MALx1 transporters, practically all strains analysed in Fig. 3 showed increased copy number of this gene relative to S288C, indicating that more than one functional MAL locus is present in these strains, allowing efficient maltose utilization.

Microarray karyotyping data of relative gene copy number variation (compared to strain S288C) present in the genomes of selected yeast strains from Group 1 (G1), Group 2 (G2) or Group 3 (G3).

The CGH results revealed a very different pattern regarding the AGT1 permease (Fig. 3). All the efficient maltotriose utilization strains (Group 1) analysed by microarray karyotyping have this gene in their genome, while most of the strains belonging to either Group 2 (slow/delayed maltotriose utilization) or Group 3 (no maltotriose utilization) had a lower copy number (just one gene per diploid genome), or even lacked the AGT1 gene (Fig. 3, see also Fig. 2c). Finally, although our microarrays were designed to determine gene CNVs in S. cerevisiae genomes, Fig. 3 also shows the S. cerevisiae-related aCGH data for an interspecific hybrid between this species and S. bayanus (strain CLIB180). As can be seen for this strain, which belongs to Group 1, the aCGH results indicate the presence of the AGT1 permease and amplification of the MALx1 genes, similar to what is seen in the S. cerevisiae Group 1 strains.

New maltotriose utilization phenotypes in Saccharomyces yeasts

The results shown in Fig. 1 regarding the slow/delayed maltotriose utilization (Group 2) pattern observed for some yeast strains were quite unexpected and prompted us to perform a more detailed analysis of these new phenotypes. Figure 4 shows the patterns of maltotriose utilization by two laboratory S. cerevisiae strains (CEN.PK2-1C and 1403-7A) and their corresponding agt1Δ isogenic yeast strains (LCM003 and LCM001, respectively). As we have already reported for strain LCM003 ( Alves et al. 2008 ), these agt1Δ cells are completely unable to utilize maltotriose, even after an extensive (>8 days) incubation in the presence of this carbon source. However, and in accordance with the growth assays shown in Fig. 1, strain LCM001 (also agt1Δ) had an unexpected different phenotype: it did not grow on maltotriose during the first 3–4 days of incubation, but after this extensive lag phase the cells started to consume the sugar, allowing efficient aerobic growth on maltotriose (note, though, that no ethanol was produced during sugar consumption, see Fig. 4c). This extensive lag phase phenotype was always reproducible and takes place even if cells growing exponentially in maltotriose (for example after 100 h of incubation in this carbon source) are diluted back into new YP-2% maltotriose medium this shows that the lag phase phenotype is not merely because of selection of new maltotriose fermentative yeast mutants (data not shown).

Typical cell growth (a), sugar consumption (b) and ethanol production (c) during growth on maltotriose by cells of the laboratory strains CEN.PK2-1C (black triangles) and its isogenic Δagt1 strain LCM003 (open triangles), or by strain 1403-7A (black circles) and its isogenic Δagt1 strain LCM001 (open circles).

Similar maltotriose utilization phenotypes were observed for some other S. cerevisiae industrial yeast strains belonging to Group 2. For example, cells of the industrial strain VR-1 also displayed long lag times (3–4 days) before starting to consume maltotriose for growth, and no ethanol was produced from this carbon source, although this yeast consumes and ferments maltose efficiently (Fig. 5c). Thus, this VR-1 yeast strain resembles the phenotype observed for the agt1Δ LCM001 strain shown above indeed our aCGH and chromosomal blotting results indicate that this strain lacks the AGT1 permease in its genome (see Fig. 2b–c). However, for the remaining members of the Group 2 yeasts (the industrial fuel ethanol strains CAT-1, SA-1 and PE-2), yet another novel phenotype was observed: like LCM001 and VR-1, these strains consumed maltotriose only after an extensive lag phase, but unlike LCM001 and VR-1, they produced ethanol from maltotriose. Note that maltose consumption and fermentation was normal in the CAT-1, SA-1 and PE-2 strains. Nevertheless, in most cases, the ethanol yields on maltotriose were significantly lower than those obtained during maltose fermentation, as shown in Fig. 5c for the industrial S. cerevisiae yeast strain PE-2.

Typical cell growth (a), sugar consumption (b) and ethanol production (c) during growth on maltose (circles) or maltotriose (triangles) by cells of the industrial strains PE-2 (black symbols) or VR-1 (open symbols).


Electrophoretic karyotyping of brewing yeast strains reveals chromosome pattern variability

Firstly, we have evaluated the chromosome profiles of 29 brewing yeast strains both top-fermenting ale strains and bottom-fermenting lager strains that were purchased from multiple suppliers and classified as S. cerevisiae (Table ​ (Table1, 1 , Fig. ​ Fig.1 1 ).

The dendrogram of chromosome band-based similarity created after electrophoretic karyotyping of 30 brewing yeast strains (lanes from 1 to 30). The yeast S. cerevisiae chromosome marker YNN295 (BIORAD) is also presented (lane M). Lager strains (strains 6, 7, 18, and 29) are denoted as L, whereas cider strain (strain 26) is denoted as C. Strains 4, 6, 8, and 9 with various chromosome profiles were selected for further analysis (in red frames) (Color figure online)

Indeed, after PFGE separation, we were able to observe S. cerevisiae-like chromosome profiles (Fig. ​ (Fig.1). 1 ). In general, the chromosome number of analyzed strains is 16 (Fig. ​ (Fig.1). 1 ). However, some additional bands can be also observed e.g., an additional band between chromosomes IV and VII was shown for strains 6, 7, 18, and 29 that is a characteristic feature of Saccharomyces bayanus karyotype (Naumov et al. 1992). Perhaps, some of analyzed strains may be considered as hybrids between S. cerevisiae and S. bayanus. Indeed, strains 6, 7, 18, and 29 are bottom-fermenting lager strains, and in general, lager yeasts are natural hybrids between S. cerevisiae and S. eubayanus (Dunn and Sherlock 2008 Walther et al. 2014 Wendland 2014). Some other chromosome variabilities may also reflect increased level of translocations and aneuploidy events and dynamic nature of industrial yeast genomes (Bond et al. 2004 Querol and Bond 2009). Similar chromosome profiles among analyzed strains were revealed using UPGMA clustering e.g., lager strains were grouped together (Fig. ​ (Fig.1). 1 ). Four strains, namely strains 4, 6, 8, and 9, representing different karyotype profiles were then selected for further analysis (Fig. ​ (Fig.1, 1 , in red frames). Additionally, one cider yeast strain (strain 26) was included for chromosome comparison (Fig. ​ (Fig.1 1 ).

Differences in growth rate, viability, and ploidy state

Secondly, the kinetics of growth of selected brewing yeasts both top-fermenting strains (strains 4, 8, and 9) and bottom-fermenting strain (strain 6) was inspected using standard yeast growth medium (YPD medium) (Fig. ​ (Fig.2 2 a).

Growth rate, viability, and ploidy state of selected brewing yeast strains. a Yeast growth was monitored turbidimetrically at 600 nm in a microplate reader every 2 h during a 10 h. Bars indicate SD, n =ਆ. b Cell viability was estimated with a LIVE/DEAD® Yeast Viability Kit using the standard protocol according to the manufacturer’s instructions. The percentage of live and dead cells is shown. n =򠈀. c Fluorescence-activated cell sorting (FACS)-based analysis of DNA content of strains 4, 6, 8, and 9. Representative histograms are shown. Diploid, triploid, and tetraploid reference strains are also presented

The growth rate of strains 4 and 9 was accelerated compared to the growth rate of strains 6 and 8 in the first 6 h of experiment (Fig. ​ (Fig.2a). 2 a). However, the delay of growth of strains 6 and 8 was overcome in the next 2 h, and after 10 h, the growth yield was comparable between all analyzed strains (Fig. ​ (Fig.2a). 2 a). The viability of cells at the logarithmic phase of growth was similar and ranging from 99.5 to 98 % (Fig. ​ (Fig.2b). 2 b). Fluorescence-activated cell sorting (FACS)-based analysis of DNA content revealed diverse ploidy states of analyzed strains (Fig. ​ (Fig.2c). 2 c). Strains 4 and 9 are tetraploid and strain 8 is diploid. The histogram for strain 6 is more ambiguous and shows some features of the tetraploid reference strain histogram (Fig. ​ (Fig.2 2 c).

Intracellular redox equilibrium is shifted toward more oxidation state in Saflager W-34/70 strain and, to lesser degree, in Windsor British ale strain

We then analyzed intracellular reactive oxygen species (ROS) production and superoxide production in the control growth conditions (Fig. ​ (Fig.3 3 ).

Intracellular redox state of selected brewing yeast strains. Reactive oxygen species (ROS) production was assessed using H2DCF-DA fluorogenic probe (a), and superoxide production was monitored using dihydroethidium fluorogenic probe (b). The results are presented as relative fluorescence units per minute (RFU/min). Bars indicate SD, n =਄. c The level of 8-hydroxy-2′-deoxyguanosine (8-oxo-dG) was analyzed using ELISA-based assay. Bars indicate SD, n =ਃ, *p <਀.05 compared to strain 6 (ANOVA and Tukey’s a posteriori test)

Redox imbalance was observed in strains 6 and 9 compared to strains 4 and 8 (Fig. ​ (Fig.3). 3 ). Higher level of ROS production of approximately 3.5-fold and 1.8-fold was shown in strains 6 and 9, respectively (Fig. ​ (Fig.3a). 3 a). In contrast, augmented superoxide production was only observed in strain 6 (Fig. ​ (Fig.3b). 3 b). Intracellular superoxide production was higher approximately 2-fold in strain 6 compared to other strains (Fig. ​ (Fig.3b). 3 b). Statistically significant higher level of ROS and superoxide production was observed in strain 6 compared to other strains analyzed (p <਀.05) (Fig. ​ (Fig.3a, 3 a, b). Redox disequilibrium resulted in elevated levels of oxidative DNA damage (the level of 8-hydroxy-2′-deoxyguanosine (8-oxo-dG)) in strains 6 and 9 (Fig. ​ (Fig.3c). 3 c). Increased 8-oxo-dG levels of approximately 60 % were observed in strains 6 and 9 compared to strains 4 and 8 (Fig. ​ (Fig.3c). 3 c). Statistically significant higher level of oxidative DNA damage was noticed in strain 6 compared to strains 4 and 8 (p <਀.05) (Fig. ​ (Fig.3 3 c).

Subtelomeric regions are sites of the most accented differences in the gene copy number and loci-specific gains and losses

The genome of selected strains was further characterized using array-based comparative genomic hybridization (array-CGH) (Figs. ​ (Figs.4 4 and ​ and5 5 ).

Analysis of the variability in the gene copy number of strains 4, 6, 8, and 9 using array-CGH. a Array-CGH profiles are shown. Each gray dot represents the value of the log2 ratio for an individual gene. Blue lines were provided to emphasize the most accented differences (DNA losses and gains). b The relatedness of strains analyzed using cluster analysis. Similarity tree is shown (Color figure online)

The divergence of relative abundance of genes as determined by array-CGH represented by standard deviation (SD) of log2 ratio values for each gene in strains 4, 6, 8, and 9. a The summary plot for the whole genome. b Individual plots for each chromosome. Blue dots indicate the SD values for individual genes, the red lines denote the smoother trend calculated by moving average of SD values to expose the genome regions of higher log2 ratio divergence, and green triangles indicate centromere position. Individual plots for mitochondrial genome are also presented (Mt) (Color figure online)

The genome of strain 4 of a euploid nature was characterized by decreased number of subtelomeric genes (Fig. ​ (Fig.4a). 4 a). The gains of chromosomes I, III, and VI were observed in strain 8, whereas the losses of chromosomes I, III, VI, and IX were shown in strain 9 (Fig. ​ (Fig.4a). 4 a). The most affected genome was strain 6 compared to the other analyzed genomes with the majority of its chromosomes containing gains and/or losses (Fig. ​ (Fig.4a). 4 a). The gains of fragments of chromosomes II, III, VII, VIII, and XI and the losses of fragments of chromosomes III, V, and X were observed (Fig. ​ (Fig.4a). 4 a). Moreover, some other losses were much more accented, e.g., gross deficiencies of chromosomes I, VI, XII, and XVI (Fig. ​ (Fig.4a). 4 a). In the case of chromosome XII, the lack of whole chromosome and, in the case of chromosome XVI, the lack of distal part of right arm were observed (Fig. ​ (Fig.4a). 4 a). Additionally, array-CGH profiles were used to estimate the level of similarity (relatedness) between selected strains analyzed on the basis of observed genomic diversity (Fig. ​ (Fig.4b). 4 b). As expected, the most variable was lager strain (strain 6) with its own category (Fig. ​ (Fig.4b). 4 b). All three ale strains were grouped together (Fig. ​ (Fig.4b). 4 b). Array-CGH data allowed us also to analyze the diversity of the copy number of individual genes among all brewing yeast strains studied. As a measure of this diversity, we used standard deviation (SD) of log2 ratio values. Figure ​ Figure5 5 plots SD of log2 ratio values for all genes. Figure ​ Figure5a 5 a gives an overview of the whole yeast genome, and Fig. ​ Fig.5b 5 b shows an expanded view of the same data divided into individual chromosomes. The data points for single genes (blue dots) are overplayed with the red line representing the moving average of the individual data points to visualize greater regions of high diversity. According to these plots, the most evident diversity in the gene copy number was revealed within subtelomeric regions in almost all analyzed chromosomes and also within short intrachromosomal regions of chromosomes IV, IX, XII, and XIII (Fig. ​ (Fig.5). 5 ). Also, highly diverse is the whole mitochondrial chromosome (Fig. ​ (Fig.5b, 5 b, Mt).

Gene ontology overrepresentation profiles vary between strains

As the observed differences in the gene copy number and loci-specific gains and losses may affect the functional properties of brewing strains, the genes that were most divergent according to array-CGH-based analysis (showing log2 ratio values higher than 2 or lower than 𢄢 for at least one of analyzed strains) were then subjected to gene ontology overrepresentation analysis (Fig. ​ (Fig.6 6 ).

A heat map generated from array-CGH data. Functional categories overrepresented in the group of genes that were the most divergent among analyzed strains are shown. The strains were ordered according to the result of clustering analysis (Fig. ​ (Fig.4b), 4 b), and the selected genes were grouped according to their functional assignment. Positive and negative log2 ratio values represent higher and lower than average abundance of the gene, as determined by array-CGH analysis

Five functional categories overrepresented in the group of selected genes were revealed, namely (1) maltose metabolism and transport, (2) response to toxin, (3) siderophore transport, (4) cellular aldehyde metabolic process, and (5) L-iditol 2-dehydrogenase activity (p <਀.05) and are presented as a heat map in Fig. ​ Fig.6. 6 . Within two functional categories of genes involved in response to toxin and cellular aldehyde metabolic process, the loss of aryl alcohol dehydrogenase (AAD) genes was observed in strains 6 and 9 with unbalanced redox equilibrium (Figs. ​ (Figs.3 3 and ​ and6). 6 ). The effects were statistically significant for AAD3, AAD6, AAD10, and AAD15 genes (p <਀.05) (Fig. ​ (Fig.6), 6 ), whereas similar but weak tendency for AAD4 and AAD14 genes was not significant (Supplementary Material). Moreover, the most accented loss of genes involved in siderophore transport was also shown in strain 6 (p <਀.05) (Fig. ​ (Fig.6). 6 ). In contrast, the most evident loss of genes involved in maltose metabolism was observed in strain 8 (p <਀.05) (Fig. ​ (Fig.6). 6 ). A heat map generated from array-CGH data reflecting the variability in the gene copy number of the whole genome of brewing strains analyzed is also presented in Supplementary Material.

Validation of array-based comparative genomic hybridization data

To test if the variations in the gene copy number are reflected by the levels of mRNA for those genes, qRT-PCR assay was employed for FIT3, MAL13, AAD10, and ALD2 genes representing major functional categories depicted in Fig. ​ Fig.6. 6 . The qRT-PCR results are presented in Table ​ Table3 3 .

Table 3

The relative mRNA levels for genes selected from the set shown in Fig. ​ Fig.6 6

40.0180 ±਀.00101.0668 ±਀.06930.2257 ±਀.04170.4143 ±਀.0423
60.0004 ±਀.00010.9243 ±਀.00670.0003 ±਀.00010.5779 ±਀.0418
80.0558 ±਀.00210.0004 ±਀.00010.4108 ±਀.00840.5524 ±਀.0461
90.0264 ±਀.00180.9239 ±਀.04351.3551 ±਀.02740.0004 ±਀.0003

The numbers represent the levels of respective transcripts normalized to the data for a housekeeping gene ALG9, relative to the normalized levels of transcript in BY4741 strain. The data represent the mean ± SD from at least three independent experiments

Moreover, the comparison of gene copy number and mRNA levels for these genes is shown in Fig. ​ Fig.7 7 .

Validation of gene copy number data obtained using array-CGH analysis with mRNA levels determined by qRT-PCR. The comparisons to the array-CGH results were made for genes selected from the set shown in Fig. ​ Fig.6. 6 . The qRT-PCR data from Table ​ Table3 3 were normalized with the average of the data for each gene and converted to log2 values to bring them to the same format as array-CGH data. The correlation coefficient between both sets of data is 0.89. a Log2 values obtained with both methods. b Graphical representation of these data

To make this comparison possible, the qRT-PCR data had to be processed in the same way as array-CGH data. Therefore, the individual data points for each gene were divided by the average of the values for that gene in all strains. The resulting normalized data were converted to log2 values. As seen in Fig. ​ Fig.7, 7 , the results obtained with both methods correlate very well, with correlation coefficient of 0.89. The negative values obtained for the genes that were absent in some strains are lower using qRT-PCR method than using array-CGH assay, but this is because the former method is more sensitive. Yet, array-CGH result for a gene that is below 𢄢 means that this gene is absent in that strain.

Genomic stability and nucleolus state are affected in Saflager W-34/70 strain

We were then interested if strains with redox disequilibrium and decreased dosage of genes involved in stress responses, e.g., strain 6, may be susceptible to DNA breaks and changes in nucleolus state. Indeed, strain 6 was found to be the most affected by DNA double-strand breaks (DSBs) in the control growth conditions (p <਀.05) (Fig. ​ (Fig.8 8 a).

Evaluation of genomic instability and nucleolus state in selected brewing yeast strains in the control growth conditions. a The susceptibility to DNA double-strand breaks (DSBs). DSBs were assessed using neutral comet assay. As a DNA damage marker, the % tail DNA was used. The bars indicate SD, n =򠅐, *p <਀.05 compared to strain 6 (ANOVA and Tukey’s a posteriori test). The typical micrographs are shown (right). DNA was visualized using YOYO-1 staining (green). b Western blot analysis of Nop1, Fob1, Rad1, and Rap1 contents. Anti-Tub1 antibody served as a loading control. Anti-Act1 antibody was ruled out as a loading control because analyzed strains are characterized by different levels of beta-actin. c Analysis of chromosome I, XI, and XII signals using fluorescence in situ hybridization and whole-chromosome painting probes (WCPPs). Chromosome-specific signals were scored in 100 nuclei and presented as a percentage, n =򠄀. Three categories were considered, i.e., cells with one, two, and more than two chromosome specific signals. d Analysis of rDNA content. rDNA was visualized using WCPP specific to chromosome XII that contains rDNA locus in yeast. Fluorescence signals of chromosome XII were quantified using ImageJ software. The integrated fluorescence density is presented in relative fluorescence units (RFUs). Box-and-whisker plots are shown, n =򠄀. The typical micrographs are shown (right). The cells were labeled with FITC to detect chromosome XII-specific signals (green). DNA was visualized using DAPI staining (blue) (Color figure online)

We have then compared the levels of protein involved in DNA damage repair, namely Rad1p, but its level was not lower in strain 6 compared to other strains analyzed in the control growth conditions (Fig. ​ (Fig.8b). 8 b). In contrast, the levels of nucleolar proteins Nop1 and Fob1 and transcription regulator Rap1 were lower in strain 6 compared to other strains analyzed in the control growth conditions (Fig. ​ (Fig.8b). 8 b). Interestingly, anti-Act1p antibody cannot be considered as a loading control in strain 6 because strain 6 is characterized by very low level of beta-actin compared to other analyzed strains (Fig. ​ (Fig.8b). 8 b). We selected then three chromosomes of different size, namely small chromosome I, medium-sized chromosome XI, and large chromosome XII to analyze their signal variability in brewing strains using FISH with WCPPs (Fig. ​ (Fig.8c). 8 c). One should remember that array-CGH method is a population-scale approach and is not designed to study the discrete cellular observations, whereas FISH, here single-cell analysis of chromosome instability, can be used to address cellular heterogeneity. Some of our FISH data are in agreement with array-CGH results, especially on genomic diversity observed in strain 6 (Figs. ​ (Figs.4 4 and ​ and8c). 8 c). Gross deficiencies of chromosomes I and XII (Fig. ​ (Fig.4) 4 ) were revealed using array-CGH that may reflect low frequency of signals of chromosomes I and XII observed using WCPPs (Fig. ​ (Fig.8c). 8 c). Analogically, the gains of chromosome XI (Fig. ​ (Fig.4) 4 ) were correlated with higher frequency of signals of chromosome XI in strain 6 compared to other strains (Fig. ​ (Fig.8c). 8 c). Interestingly, higher frequency of signals of chromosome XII was observed in strain 8 (Fig. ​ (Fig.8c, 8 c, d). Because similar effect was not revealed using array-CGH not detecting rDNA sequences, higher frequency of signals of chromosome XII that contains rDNA locus in yeast may suggest chromosome XII fragmentation and/or nucleolus (rDNA) fragmentation in strain 8. Chromosome XII (rDNA) signals were also quantified (Fig. ​ (Fig.8d). 8 d). However, except of strain 4, rDNA content was comparable among analyzed strains (Fig. ​ (Fig.8d). 8 d). Perhaps, chromosome XII fragmentation does not affect rDNA levels in strain 8 (Fig. ​ (Fig.8 8 d).

Tolerance to fermentation-associated stress stimuli is diminished in Saflager W-34/70 strain

We then asked the question of whether lower copy number of aryl-alcohol dehydrogenase (AAD) genes, imbalanced redox homeostasis, and genetic instability in strain 6 compared to other strains analyzed may also affect fermentation performance in strain 6. First, the utilization of non-fermentable carbon sources, namely glycerol and ethanol, was investigated (Fig. ​ (Fig.9 9 a).

Analysis of the utilization of non-fermentable carbon sources (a) and tolerance to fermentation-associated stress stimuli in selected brewing yeast strains (strains 4, 6, 8, and 9) (b) using spot assay. a Yeast cells at the logarithmic phase of growth were diluted (1 ×ꀐ 7 , 1 ×ꀐ 6 , 1 ×ꀐ 5 , 1 ×ꀐ 4 , and 1 ×ꀐ 3 cells/ml), and growth on solid YPG and YPE media was inspected after 48 h. The growth of strain 6 was improved in the presence of 0.1 % glucose in YPG medium. b Yeast cells at the logarithmic phase of growth were diluted (1 ×ꀐ 7 , 1 ×ꀐ 6 , 1 ×ꀐ 5 , 1 ×ꀐ 4 , and 1 ×ꀐ 3 cells/ml), and growth on solid YPD medium in the presence of different stress stimuli was inspected after 48 h. In the case of hydrogen peroxide, cells were incubated with hydrogen peroxide for 40 min and then transferred to solid YPD medium. The growth of cells incubated at 4 ଌ was inspected after 120 h. Representative photographs are shown

The growth capacity of strain 6 was diminished in YPG and YPE media compared to control YPD medium and also to growth of other strains analyzed (Fig. ​ (Fig.9a). 9 a). The growth of strain 6 was improved when YPG medium was supplemented with 0.1 % glucose (Fig. ​ (Fig.9a). 9 a). Second, the tolerance to fermentation-associated stress stimuli was considered, namely salt, osmotic, oxidative, ethanol, high glucose, and cold/heat stresses (Fig. ​ (Fig.9b). 9 b). In general, diminished resistance to stress stimuli of strain 6 was observed compared to other strains analyzed (Fig. ​ (Fig.9b). 9 b). Strain 6 was found to be more sensitive to NaCl, KCl, sorbitol, hydrogen peroxide, ethanol and high-glucose treatments, and heat stress (Fig. ​ (Fig.9b). 9 b). Strain 6 was unable to grow at 37 ଌ (Fig. ​ (Fig.9b). 9 b). In contrast, cryotolerant lager strain 6 grew better at 4 ଌ compared to ale strains (strains 4, 8, and 9) (Fig. ​ (Fig.9 9 b).

Example 8

The parent strain and ScCTT1-highly expressed strain obtained in Example 7, are used to carry out fermentation test under the following conditions.

The fermentation broth was sampled with time to observe the cell growth (OD660) (FIG. 10) and extract consumption with time (FIG. 11). Quantification of sulfite concentration at completion of fermentation was carried out by collecting sulfite into hydrogen peroxide aqueous solution by distillation under acidic condition, and titration with alkali (Revised BCOJ Beer Analysis Method by the Brewing Society of Japan).

As shown in FIG. 12, the ScCTT1-highly expressed strain produced sulfite approximately 1.7 times greater than the parent strain. In addition, significant differences were not observed between the parent strain and the highly expressed strain in cell growth and extract consumption in this testing.

Watch the video: Brew Day: Pilsner fermented at ale temperatures with Saflager 3470 yeast (August 2022).