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. 2025 Oct 11;18(10):e70244. doi: 10.1111/1751-7915.70244

Chromosome III Aneuploidy Enhances Ethanol Tolerance in Industrial Saccharomyces cerevisiae by Increasing the TUP1 Copy Number

Sonia Albillos‐Arenal 1, Javier Alonso del Real 1, Ana Cristina Adam 1, Eladio Barrio 1,2, Amparo Querol 1,✉
PMCID: PMC12514340  PMID: 41074565

ABSTRACT

Ethanol stress poses a considerable challenge for Saccharomyces cerevisiae during fermentation. Strains carrying an extra copy of chromosome III exhibit enhanced ethanol tolerance. Here, we investigated the underlying mechanisms of this tolerance, focusing on gene dosage effects and differential gene expression under ethanol stress. We compared the gene expression profiles of a strain with three copies of chromosome III and its derivative with two copies, exposed to 6% and 10% ethanol. Our analysis identified TUP1, located on chromosome III, as a key regulator of the ethanol stress response. Deleting one copy of TUP1 in the tolerant strain diminished its ethanol tolerance, suggesting that chromosome III aneuploidy in ethanol‐tolerant strains enhances adaptive responses by increasing TUP1 copy number. Our findings offer insights into the genetic basis of ethanol tolerance, with potential applications for optimising industrial fermentation processes and understanding the role of aneuploidy in the domestication of industrial yeasts.

Keywords: aneuploidy, ethanol tolerance, Saccharomyces cerevisiae, transcriptomic, TUP1

Chromosome III aneuploidy elevates TUP1 dosage and boosts ethanol tolerance by modulating stress‐response pathways, validated through RNA‐seq and targeted TUP1 copy number reduction.

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1. Introduction

One key reason for the widespread use of Saccharomyces in fermentation is its remarkable tolerance to relatively high ethanol concentrations. However, ethanol remains a potent stressor, impacting numerous cellular processes; it specifically inhibits respiration, arrests cell growth and can ultimately cause cell death (Alexandre et al. 2001; Stanley et al. 2010; Ma and Liu 2010). To counteract this stress, Saccharomyces cerevisiae activates various defence mechanisms, including the production of heat shock proteins (Ding et al. 2009), the accumulation of trehalose (Lucero et al. 2000) and changes in vacuole morphology (Meaden et al. 1999). Additionally, ethanol disrupts protein function, reducing enzyme activity (Chandler et al. 2004; Hu et al. 2007), compromises membrane integrity (Lairón‐Peris et al. 2021; Šajbidor et al. 1995), triggers the production of reactive oxygen species, alters carbon metabolism (Yang et al. 2012) and affects post‐translational modifications such as SUMOylation (Bradley et al. 2021). These complex responses pose significant challenges to improving fermentation efficiency and sustainability across various industries (Gallone et al. 2016). Accordingly, developing ethanol‐tolerant yeast strains is a key objective in biotechnology. Different strains of Saccharomyces exhibit varying levels of tolerance to ethanol stress. Generally, industrial strains, such as wine strains (Bisson and Block 2002; Bauer and Pretorius 2000), exhibit higher tolerance to ethanol stress compared to wild strains (Lairón‐Peris et al. 2021). This is a result of human selection over thousands of years of winemaking, a process known as domestication (Thomson et al. 2005). S. cerevisiae is well‐adapted to tolerate ethanol (Ma and Liu 2010), making it a valuable tool in various fermentation processes.

Ethanol tolerance in yeast is a multifaceted process that involves numerous genes distributed throughout the genome. Several mechanisms have been described to mitigate the harmful effects of ethanol (Stanley et al. 2010; Chandler et al. 2004; Bisson and Block 2002; Auesukaree 2017). Voordeckers et al. (2015) investigated the complex evolutionary adaptations of S. cerevisiae to high ethanol concentrations. Through experimental evolution and genomic analysis, they found that aneuploidy of chromosome III significantly contributed to increased ethanol tolerance (Voordeckers et al. 2015). This finding was further supported by Morard et al. (2019), who observed a strong correlation between polysomy of chromosome III and high ethanol tolerance. The prevalence of aneuploidy in chromosome III underscores its importance in enhancing ethanol tolerance. Chromosome duplication is a common adaptation strategy for organisms facing harsh environments (Gilchrist and Stelkens 2019; Morard et al. 2019) and acts as an initial defence mechanism, providing a rapid but temporary solution to sudden selective pressures (Yona et al. 2012).

Interestingly, aneuploidy states can be surprisingly stable in nature, particularly due to protein turnover processes. This contrasts with the transient nature of aneuploidy in laboratory strains (Muenzner et al. 2024). These observations highlight the dynamic interplay between genomic responses to stress and the evolutionary trajectory of organisms (Yona et al. 2012). Although aneuploidy in chromosome III is linked to increased ethanol tolerance, the underlying mechanisms remain unclear. Understanding this relationship is crucial for filling knowledge gaps in yeast genetics and potentially enhancing industrial fermentation processes.

We hypothesise that specific elements on chromosome III are responsible for the beneficial effects observed with increased copy number. One possibility is that key ethanol tolerance genes located on chromosome III are duplicated, leading to an increased gene copy number that results in elevated mRNA transcription and enhanced protein production of these important genes. Another possibility is that a transcription factor situated on chromosome III benefits from the extra copy number, causing differential regulation of its target genes involved in the ethanol stress response. This amplification may ultimately enhance ethanol tolerance. Our analysis revealed differential expression of several genes between two strains with varying copy numbers of chromosome III. However, the most significant finding was the identification of TUP1, located on chromosome III, as a crucial regulator of the ethanol stress response. TUP1 is a global transcriptional repressor that plays a crucial role in regulating various cellular processes in S. cerevisiae , including the response to environmental stresses such as ethanol exposure (Tanaka and Mukai 2015; Proft and Struhl 2002). Tup1p functions in association with Ssn6p (also known as Cyc8) to form the Tup1‐Cyc8 complex (Lee et al. 2023; Wong and Struhl 2011; Chen et al. 2013). Despite its primary role as a repressor, Tup1‐Cyc8 complex indirectly activates genes required for the stress response (Proft and Struhl 2002). When we deleted one copy of TUP1 in the ethanol‐tolerant strain, we observed a reduction in its ethanol tolerance. This suggests that the aneuploidy of chromosome III in ethanol‐tolerant strains enhances adaptive responses specifically by increasing the copy number of Tup1p. These findings provide valuable insights into the genetic underpinnings of ethanol tolerance, which could have important applications in optimising industrial fermentation processes. Moreover, our results contribute to the broader understanding of how aneuploidy may have played a role in the domestication of industrial yeast strains.

2. Materials and Methods

2.1. Strains and Media

S. cerevisiae strain 2‐200‐2 (MATα/α) was originally obtained from Voordeckers et al. (2015), and used in this study. This strain was derived from FY5 (MATα), a background in which the FLO1, FLO10 and FLO11 genes had been deleted. Following these deletions, the strain underwent 200 generations of adaptive evolution under ethanol stress. The evolved strain, 2‐200‐2, exhibits a hypermutator phenotype resulting from an insertion in MSH2, and carries additional genetic alterations, including aneuploidy of chromosome III and indels in ASG1 and PET123. 2‐200‐2‐S4 is a derivative of 2‐200‐2 with one copy of chromosome III deleted (Morard et al. 2019). Therefore, we have 2‐200‐2 (3xChrIII), and 2‐200‐2‐S4 (2xChrIII). Yeast strains on a 2‐200‐2 background, but with TUP1 deleted, were created in the present study and are explained later. Yeast cells were cultured in Glucose Peptone Yeast Extract (GPY) medium, which contained 20 g/L of glucose, 20 g/L of bacteriological peptone and 10 g/L of yeast extract. For solid media, 20 g/L of agar was added.

2.2. Fermentation for Sample Extraction

Strains 2‐200‐2 and 2‐200‐2‐S4 were inoculated in GPY medium and grown overnight. The cell suspensions were then adjusted to an initial OD600 of 0.2 in 1 L erlenmeyer flasks containing GPY medium with 0%, 6% or 10% ethanol. This setup was performed in triplicates for each strain and condition. The flasks were incubated at 28°C with orbital agitation at 150 rpm. At 1‐ and 10‐h post‐inoculation, approximately 108 cells were collected from each flask. These samples were immediately frozen in liquid nitrogen and subsequently stored at −80°C for further analysis.

2.3. RNA Isolation and Sequencing

RNA was isolated using the High Pure RNA Isolation kit (Roche Applied Science, Mannheim, Germany) and oligo (dT) mRNA purification. RNAseq libraries were generated using the TruSeq Stranded mRNA Library Preparation Kit (Illumina Inc., San Diego, CA). The information about the sequences area available in BioProject ID PRJNA1153811.

2.4. RNASeq Data Analysis

Reads were mapped to the S. cerevisiae reference strain S288C using Bowtie2 (Bowtie2 v.2.2.9, local alignment mode) (Langmead and Salzberg 2012). Alignments were then compressed and sorted using SAMtools v.1.4.1 (Li et al. 2009). Finally, read counts for each gene were determined using HTSeq‐Count (HTSeq‐0.6.1p1, parameters −m union –a 10) (Anders et al. 2015).

Principal component analysis (PCA) was performed on the gene expression data using the ‘dds’ function from the DESeq2 R package, which normalises and adjusts the sample counts to a negative binomial distribution and then applies a variance stabilising transformation function. The DEGs between pairs of conditions were identified using the contrast function within DESeq2, with comparisons specified as ‘2‐200‐2’ versus ‘2‐200‐2‐S4’, such that positive log2 fold changes reflect higher expression in the ancestral strain (2‐200‐2). Fold changes and corresponding p values were determined for each DEG.

GO enrichment analysis was performed using PANTHER19.0 (Thomas et al. 2022) with Fisher's exact test and a false discovery rate threshold of p < 0.05 (Benjamini‐Hochberg correction). Pathway enrichment analysis was performed using ShinyGO (Ge et al. 2020) with the list of DEGs. Finally, potential transcription factors responsible for the observed differential gene expression were identified using the YEASTRACT+ (Teixeira et al. 2023) and DB (Choi and Wyrick 2017) databases.

2.5. Deletion of a Single TUP1 Copy

To disrupt the TUP1 gene in strain 2‐200‐2, we employed the LiAc/SS Carrier DNA/PEG transformation method (Gietz and Woods 2006). The KanMX cassette was amplified from plasmid pUG6 using primers incorporating homology regions flanking the TUP1 open reading frame (Table S1). Transformants were selected on GPY medium supplemented with G418. After three days, colony PCR was performed with genomic DNA extracted using the LiAc method (Lõoke et al. 2011) and specific primers to confirm the insertion of the cassette. Since 2‐200‐2 harbours three copies of TUP1, the disruption could potentially result in the deletion of one or two copies of TUP1. We used qPCR analysis to determine the remaining copies of this gene (see Table S2).

The primers were designed to amplify an internal sequence of TUP1 and ABP1, which is also found in chromosome III near TUP1. ABP1 has previously been used to confirm chromosome copy number in Saccharomyces (Van den Broek et al. 2015).

DNA from all strains was extracted in quintuplicate using a modification of a published extraction method (Querol et al. 1992). The extracted genomic DNA was then treated with RNAse A and phenol‐chloroform to remove RNA and proteins. DNA concentration was quantified by fluorimetry using a Qubit 4 Fluorometer with the Qubit 1× dsDNA BR Assay (Invitrogen, Carslbad, CA), and samples were diluted to 10 ng/μL. Real‐time qPCR was performed with 2 μL of each sample, primers specific for TUP1 and ABP1 and the NZYSpeedy qPCR Green Master Mix (2×) (NZYtech, Lisbon, Portugal) on a LightCycler 480 System (Roche Applied Science). Three technical replicates were conducted for each of the five DNA extractions from every strain. The results from the qPCRs were statistically analysed to calculate the average expression levels of the target gene TUP1 and the reference gene ABP1. The ratio TUP1/ABP1 was then compared between the wild strains (FY5, 2‐200‐2 and 2‐200‐2‐S4) and their respective mutants to assess whether the copy number decreased. Finally, the mutant stains were sequenced to confirm the introduced changes.

2.6. Ethanol Tolerance Measurements

Saccharomyces strains were cultured overnight in 1 mL of GPY. Subsequently, cultures were centrifuged to separate the cells, washed and resuspended in PBS for 2 h. Cell density was determined using a DeNOVIX CellDrop FL (Wilmington, DE) cell counter. Based on these measurements, the appropriate volume of each strain was calculated to achieve a final concentration of 4 × 107 cells/mL. From this suspension, 11 μL of each strain was inoculated (in triplicate) into 96‐well plates. Each well contained 220 μL of minimal YNB medium and different ethanol concentrations. To prevent evaporation, 100 μL of vaseline oil was overlaid on the culture medium. Yeast growth was monitored by measuring the OD600 using a Stacker Microplate Handling System connected to a SPECTROstar Omega plate reader (BMG LABTECH, Ortenberg, Germany). The microplates were incubated within a 25°C, 70% humidity chamber equipped with an orbital shaker. Microplates were shaken for 20 s at 400 rpm every hour. Growth curves were analysed using the Growth Curve Analysis Tool (GCAT) (Bukhman et al. 2015) and the best‐fitting model (Richards, Gompertz or logistic sigmoid). Subsequently, growth parameters (lag time, growth rate and asymptotic growth value) were determined using reparametrized formulas described by Zwietering et al. (1990). To quantify overall growth, the area under the curve was obtained by integrating the curve from 0 to 70 h (final time). The relative growth of each yeast strain at different ethanol concentrations was determined by calculating the fractional area (fa). This is calculated by:

fa=Area under the curveControl area under the curve

A modified Gompertz function was used to relate the fractional area (y) to the log of ethanol concentration (x) (Lambert and Pearson 2000):

y=A+Ce−eBx−M

In this formula, A is the lower asymptote of y, B is the slope parameter, C is the distance between the upper and lower asymptote and M is the log concentration of the inflection point. The values for NIC and MIC are described as the intersection of the lines y = A + C and y = A, with the equation of the line tangential to the point (M) respectively.

MIC=10M+1BNIC=10M−1.718B

The values of A, C, B and M can be calculated using a non‐linear fitting procedure, and NIC and MIC are determined (Table S3).

3. Results

3.1. Aneuploidy of Chromosome III Drives Subtle but Consistent Expression Changes During Ethanol Exposure

To investigate the potential link between chromosome III copy number and enhanced ethanol tolerance, we compared the gene expression profiles of two genetically similar S. cerevisiae strains under ethanol stress. One strain (2‐200‐2) carried three copies of chromosome III (3xChrIII), whereas the other had two copies (2‐200‐2‐S4, 2xChrIII) due to the deletion of one copy (Morard et al. 2019). Both strains were cultured in glucose‐peptone‐yeast extract (GPY) medium containing 0%, 6% or 10% ethanol and samples were collected after 1 and 10 h of exposure for gene expression analysis.

PCA of gene expression levels revealed consistent clustering patterns across the two strains (Figure S1), suggesting that culture conditions and ethanol exposure time were the determinants of gene expression rather than strain‐specific differences. Indeed, inter‐strain variations appeared minimal. As the sole genetic distinction between these strains is the copy number of chromosome III, it is plausible that these subtle strain‐specific expression differences are primarily driven by this chromosomal variation.

We analysed RNA‐seq data (2‐200‐2 vs. 2‐200‐2‐S4) to examine how increased gene dosage on chromosome III affects the regulation of differentially expressed genes (DEGs) and overall transcriptional changes in metabolic pathways. In the absence of ethanol stress, almost all DEGs were located on chromosome III (Data S1), likely due to the extra copy of chromosome III in the aneuploid strain. However, ethanol exposure triggered a much broader transcriptional response, with numerous DEGs observed between the 3xChrIII and 2xChrIII strains (Figure 1). Since few genes showed differential expression without ethanol stress and had a low fold‐change, we focused our analysis on DEGs identified after ethanol exposure. Some DEGs overlapped across different time points and ethanol concentrations. Notably, the highest number of shared genes was observed in the 10% ethanol condition at both 1 and 10 h of fermentation. To isolate the effects of the chromosomal imbalance, we separately analysed genes on chromosome III and those on other chromosomes.

FIGURE 1.

FIGURE 1

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Number of genes with higher expression (orange circles) or lower expression (blue circles) in strain 2‐200‐2 (3 × ChrIII) relative to strain 2‐200‐2‐S4 (2 × ChrIII) during growth with GPY supplemented with 6% or 10% ethanol, measured at 1 or 10 h after inoculation. The figure separately displays the differentially expressed genes (DEGs) located on chromosome III and those located on other chromosomes.

3.2. Ethanol Stress Increases the Expression of Genes Involved in Ethanol Tolerance Located on Chromosome III

In this study, our primary objective was to elucidate the mechanisms by which chromosome III aneuploidy contributes to enhanced ethanol tolerance. To achieve this, we focused our analysis on the DEGs located on chromosome III. We hypothesised that genes on this chromosome exhibiting significantly different logFC values between the two strains could play a crucial role in the ethanol response. Expression analysis revealed that 17 genes showed a higher FC (with a p value cut‐off of 0.05) in strain 2‐200‐2 than in strain 2‐200‐2‐S4 after 1 h of 6% ethanol exposure, and 10 genes after 10 h (Figure 1). When exposed to 10% ethanol, the number of genes increased to 35 after 1 h and 50 after 10 h. Notably, 5 genes (SPB1, GFD2, ADF1, SRO9 and RSA4) exhibited a logFC > 2 (Data S1). These genes play crucial roles, either directly or indirectly, in ribosome biogenesis or translation regulation, essential processes for protein synthesis. Only one gene, YCR024C‐A (PMPI), showed lower expression in strain 2‐200‐2 than in strain 2‐200‐2‐S4 (logFC −1.37). This occurred after 10 h exposure to 10% ethanol. PMP1 encodes the regulatory subunit of the plasma membrane H(+)‐ATPase Pma1p. This finding suggests that regulatory mechanisms are in place to suppress its expression, even in the presences of an extra copy of the gene.

We then conducted an analysis of DEGs across all chromosomes to identify potential regulators on chromosome III. This investigation aimed to elucidate the factors that could explain the observed differences in gene expression and enriched pathways between strains with varying copies of chromosome III.

3.3. Tup1p Was Identified as the Key Chromosome III Regulator of Ethanol Tolerance Genes

As our primary goal was to identify a transcription factor encoded on chromosome III that regulates genes involved in ethanol tolerance, we systematically analysed the DEGs between the two strains with varying chromosome III copy numbers (Data S1) and examined shared regulatory patterns using the DB database (Choi and Wyrick 2017). This database contains information on mutant regulator expression, allowing us to investigate transcription factors that regulate these DEGs. Among the identified regulators, the Tup1p‐Ssn6p complex emerged as the most prominent candidate with a p value of < 10−6 (Figure 2). Furthermore, regulator enrichment analysis revealed YCR084C (TUP1) as the sole enriched transcription factor located on chromosome III. Notably, Tup1p displayed increased expression in the tolerant strain (3xChrIII) under various ethanol exposure conditions, with logFC values ranging from 0.64 to 0.81. Additionally, we utilised the YEASTRACT+ database (Teixeira et al. 2023), which catalogues regulatory relationships between transcription factors and their target genes, to analyse TUP1‐regulated genes in each condition. Notably, we calculated that almost half (45%) of the DEGs were regulated by TUP1.

FIGURE 2.

FIGURE 2

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Cluster analysis of transcription factors regulating genes differentially expressed between strains 200‐2 (3xChrIII) versus 2‐200‐2‐S4 (2xChrIII), performed using the Regulator Cluster tool from RegulatorDB. This tool groups regulators based on the log2 fold change in mRNA expression of their target genes in the corresponding regulator mutants, allowing visualisation of shared regulatory patterns. Regulators identified in this analysis were those significantly affecting the expression of the DEGs, using significance thresholds (p < 0.05; fold change > 1).

Among the DEGs identified between 2‐200‐2 (3xChrIII) vs. 2‐200‐2‐S4 (2xChrIII) across different ethanol concentrations and exposure times, we focused on those regulated by Tup1p with a logFC greater than 1 (Figure 3). Within these DEGs, the genes with the highest logFC (> 4), represented in red in Figure 3, included PHO84 (a high‐affinity inorganic phosphate transporter and low‐affinity manganese transporter, downregulated at 6% ethanol and 10 h exposure), SPB1 (located on chromosome III, an aldoMet‐dependent methyltransferase involved in rRNA) and HXT12 (a sugar transporter). The highest number of DEGs appeared with 10% ethanol presence. We conducted gene ontology (GO) analysis on these DEGs (Data S2), focusing specifically on those regulated by TUP1. After 1‐h exposure to 10% ethanol, Tup1p‐downregulated genes were primarily involved in chromatin structure. Following 10 h of exposure to 10% ethanol, upregulated genes were associated with the GO terms cellular component of cytosolic ribosome and ribonucleoprotein complex. By contrast, downregulated genes were associated with the GO term hexose transmembrane transporter activity. Given the diverse functions of the regulated genes, we performed a global pathway enrichment analysis to identify the most significant routes differentiating strains with varying copies of chromosome III.

FIGURE 3.

FIGURE 3

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Subset of differentially expressed genes (DEGs) between strain 2–200‐2 (3 × ChrIII) and 2–200‐2‐S4 (2 × ChrIII) that are regulated by TUP1, shown for each fermentation condition. The DESeq2 contrast was specified as ‘2‐200‐2’ versus ‘2‐200‐2‐S4’, so positive log2 fold change values (+, orange circles) indicate higher expression in 3xChrIII strain, whereas negative values (‘–‘, blue circles) indicate higher expression in the evolved strain. Only DEGs with log2 fold change > 1 or < −1 are shown. Genes are colour‐coded by magnitude of expression change: Blue (> 2), green (2–3), orange (3–4) and red (≥ 4). p values were calculated for all genes. The p value was obtained from YEASTRACT's regulation enrichment tool, which uses the hypergeometric test to estimate the probability of observing at least the number of DEGs regulated by TUP1 given the size of the DEG list, compared to the whole YEASTRACT database. This probability is corrected for multiple testing using the Bonferroni method.

3.4. Amplified TUP1 Expression Regulates Key Metabolic Routes Enhancing Ethanol Resistance

We examined genes with high differential expression, focusing on those enriched in specific pathways according to the KEGG database (Figure 4). Furthermore, we explored the relationship between these highly expressed pathways and TUP1. The most enriched pathway in strain 2‐200‐2 (3xChrIII) was steroid biosynthesis, which contributes to ethanol resistance by modulating plasma membrane fluidity and is known to be regulated by TUP1‐SSN6 (Jordá et al. 2022). Consistently, we observed differential regulation (3xChrIII vs. 2xChrIII) of key lipid‐ and sterol‐related genes regulated by TUP1, including ELO1 and ELO2, the ergosterol genes ERG25, ERG3 and ERG11, the sphingolipid transporter RSB1, and the membrane‐associated protein MRH1. Also, the tricarboxylic acid (TCA) pathway was highly enriched. Notably, Tup1p plays a key role in regulating metabolic transitions in response to nutrient availability by repressing genes involved in oxidative metabolism, including TCA cycle‐related pathways, particularly under glucose‐rich conditions (Bailey et al. 2022). As environmental conditions change, Tup1p repression is alleviated, allowing for the upregulation of metabolic pathways, such as the TCA cycle, to facilitate aerobic respiration and energy production. The next most enriched pathway was porphyrin biosynthesis, which has been linked to CYC3, which is highly affected by TUP1. In terms of the number of affected genes, the biosynthesis of secondary metabolites was the most enriched pathway, followed by meiosis, cell cycle (including TUP1‐regulated genes such as CDC10 and DOC1), biosynthesis of amino acids (also including TUP1‐regulated genes like ILV1, ILV6, TRP2, THR1, THR4, LYS20, GDH1 and PRS4) and carbon metabolism (containing many DEGs regulated by TUP1: HXT5, HXT9, HXT11, HXT12, GAP1, PFK2 and GPP1).

FIGURE 4.

FIGURE 4

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Enriched pathways identified by comparing gene expressions between strains 2‐200‐2 and 2‐200‐2‐S4 exposed to ethanol. The network visually represents the fold enrichment of each pathway, the number of genes associated with it and the false discovery rate (FDR). Node size corresponds to the number of genes involved in the respective pathway.

3.5. Reducing TUP1 Copy Number Highlights Its Critical Function in Ethanol Tolerance

To investigate the role of TUP1 copy number in ethanol tolerance, we deleted one copy of TUP1 (located on chromosome III) from strain 2‐200‐2 through homologous recombination. Quantitative PCR analysis confirmed that the resulting mutant, 2‐200‐2ΔTUP1, had 2/3 the normal copy number of TUP1, indicating successful deletion of one copy (Table S2). We hypothesised that reducing TUP1 copy number would decrease ethanol tolerance in 2‐200‐2ΔTUP1 mutants, bringing them to a level like 2‐200‐2‐S4. To test this, we determined the non‐inhibitory concentration (NIC) and minimum inhibitory concentration (MIC) of seven 2‐200‐2ΔTUP1 mutants and compared them with 2‐200‐2 and 2‐200‐2‐S4 strains (Table 1). NIC is the concentration above which growth is first visibly affected, whereas MIC is the lowest concentration of ethanol that completely inhibits visible growth. As expected, 2‐200‐2ΔTUP1 mutants exhibited reduced NIC and MIC values compared with strain 2‐200‐2, aligning with the levels observed with strain 2‐200‐2‐S4. These findings indicate that the increased copy number of TUP1 on chromosome III contributes to enhanced ethanol tolerance.

TABLE 1.

Analysis of NIC and MIC under ethanol exposure in 2‐200‐2, 2‐200‐2ΔTUP1 mutants and 2‐200‐2‐S4.

2‐200‐2 2‐200‐2ΔTUP1 S4
NIC 8.81 ± 0.13 (a) 5.54 ± 0.62 (b) 6.39 ± 0.68 (b)
MIC 11.44 ± 0.14 (a) 10.23 ± 0.33 (b) 10.72 ± 0.17 (b)
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Note: Values were calculated using the area under the curve obtained following the growth curve of the strains under different ethanol concentrations and represent the mean (bold) and standard error. Data were analysed using analysis of variance (ANOVA) followed by Tukey's HSD post hoc test, with different groups indicated by the letters ‘a’ or ‘b’.

Mean values are shown in bold. Statistical analysis was performed using ANOVA followed by Tukey's test. Different letters denote statistically significant differences (p < 0.05).

4. Discussion

Ethanol tolerance is a complex trait that remains challenging to fully understand. Previous research has shown that strains with an extra copy of chromosome III exhibit superior tolerance to ethanol than their derivatives with only two copies (Voordeckers et al. 2015; Morard et al. 2019). Although this suggests a link between chromosome III and ethanol tolerance, the basis for the increased copy number was unclear. In the present study, we compared the expression profiles of two strains with identical genetic backgrounds but differing numbers of chromosome III copies. This allowed us to isolate the effects of the extra chromosome copy. Under normal, ethanol‐free conditions, we observed minimal differences in gene expression between the two strains. However, when exposed to high (10%) and low (6%) ethanol concentrations, significant differences in gene expression and activated mechanism emerged. Notably, a substantially larger number of genes were differentially expressed in response to 10% ethanol than to 6% ethanol. These findings align with previous observations that different yeast strains exhibit varying levels of ethanol tolerance, and that these differences may be attributed to diverse underlying mechanisms (Sazegari et al. 2022). Additionally, the time‐dependent nature of ethanol resistance suggests that immediate responses to ethanol stress may differ from longer‐term adaptations (Voordeckers et al. 2015).

A key finding in the present study was that the increased copies of TUP1 on chromosome III impacted the expression of multiple genes that have already been linked to ethanol tolerance including membrane composition (Lairón‐Peris et al. 2021; Šajbidor et al. 1995), carbon metabolism (Yang et al. 2012), and cell cycle (Ma and Liu 2010). TUP1, a conserved transcriptional corepressor, is regulated by glucose depletion and plays a critical role in deacetylation processes, affecting various biological processes including gene expression and transporter activity. It has been shown to influence nucleosome positioning at the HXT family (Tanaka and Mukai 2015; Chen et al. 2013; Parnell et al. 2021) and is essential for quiescent cell survival when acting in concert with SSN6 (Bailey et al. 2022).

Of note, the Tup1p‐Ssn6p complex plays a dual role in S. cerevisiae , functioning both as a repressor and an activator depending on cellular conditions (Lee et al. 2023; Parnell et al. 2021). Under normal conditions, Tup1p primarily functions as a repressor, silencing over 300 genes involved in diverse processes, including carbohydrate metabolism, transport and stress responses (Bailey et al. 2022). It is recruited to specific promoters by DNA‐binding proteins such as Sko1p, repressing transcription through both chromatin‐dependent and chromatin‐independent mechanisms (Wong and Struhl 2011; Chen et al. 2013). Interestingly, the repression of genes encoding chromatin structural components, observed in our study after short‐term ethanol stress (1 h, 10% ethanol), may facilitate broader transcriptional changes. During stress conditions, including ethanol or osmotic stress, the function of Tup1p shifts (Sazegari et al. 2022; Nadel et al. 2019), as the cell undergoes a complex reorganisation of gene expression, characterised by increased activation of genes involved in the cytosolic ribosomal complex. Tup1p is implicated in recruiting coactivators such as SAGA, SWI/SNF and mediators to promoters, suggesting a switch from repressor to activator (Proft and Struhl 2002). Concurrently, the cell exhibits differential regulation of sugar transporters, finely tuned to ethanol stress levels. At higher concentrations (10% ethanol), our results showed that sugar transporter genes are repressed, whereas at lower levels (6% ethanol), the high‐affinity transporter HXT7 is activated. This strategy optimises resource utilisation (Adamczyk and Szatkowska 2017; Buziol et al. 2008; Diderich et al. 1999). Tup1p is likely involved in this dynamic regulation, given its role in repressing carbohydrate metabolism and transport genes under normal conditions (Bailey et al. 2022). During osmotic stress, activation of the HOG pathway leads to Hog1p phosphorylation, causing the disassembly of the Tup1p‐Ssn6p‐Sko1p repressor complex and converting Sko1p from a repressor to an activator (Proft and Struhl 2002). During hyperosmotic stress, Tup1p undergoes rapid and transient SUMOylation at lysine 270 (K270), which is crucial for its functional switch (Nadel et al. 2019; Oeser et al. 2016). This dynamic regulation allows S. cerevisiae to rapidly adapt to environmental changes (Mennella et al. 2003). Aneuploidy, specifically chromosome III duplication, can further influence this stress response. Increased copy number of TUP1 can alter gene expression patterns through gene dosage effects impacting ethanol tolerance. Changes in copy number can lead to varying levels of gene expression, potentially leading to different levels of transcription (Hastings et al. 2009). Additionally, chromosomal duplication serves as an initial evolutionary defence mechanism, enabling organisms to withstand sudden and intensive selective pressures (Yona et al. 2012).

In conclusion, our study reveals that the aneuploidy of chromosome III in the 2‐200‐2 strain, which emerged after 200 generations of adaptive evolution under ethanol stress (Voordeckers et al. 2015), presents a mechanism for ethanol tolerance centred around the transcription factor TUP1. We found that the copy number of TUP1, located on chromosome III, significantly influences ethanol tolerance, as evidenced by the decreased ethanol tolerance in 2‐200‐2ΔTUP1 mutants. Ethanol‐tolerant strains exhibit increased copy number of chromosome III, likely amplifying TUP1 expression. This chromosomal duplication serves as an initial evolutionary response to sudden, intense selective pressures. The ability of TUP1 to rapidly switch between activator and repressor roles through SUMOylation allows for rapid adaptation to changing environments. Although TUP1 is a general stress regulator, our study highlights its specific importance in ethanol tolerance. We identified numerous genes differentially regulated by TUP1 at high ethanol concentrations in ethanol‐tolerant strains, emphasising its crucial role in orchestrating the cellular response to ethanol stress. This comprehensive evidence underscores the complex interplay between chromosomal duplication, gene regulation and adaptive responses mediated by TUP1 in ethanol tolerance, providing insights into the evolution of stress resistance in yeast.

Author Contributions

Sonia Albillos‐Arenal: methodology, investigation, validation, formal analysis, writing – original draft. Javier Alonso del Real: conceptualization, software, formal analysis, writing – original draft. Ana Cristina Adam: methodology, formal analysis. Eladio Barrio: conceptualization, supervision, funding acquisition, writing – review and editing. Amparo Querol: conceptualization, formal analysis, supervision, funding acquisition, writing – review and editing, resources.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: DEGs calculated using the DESeq2 contrast 2‐200‐2 (3xChrIII) vs 2‐200‐2‐S4 (2xChrIII).

MBT2-18-e70244-s005.xlsx (167.3KB, xlsx)

Data S2: GO‐terms from the DEGs between 2‐200‐2 (3xChrIII) vs 2‐200‐2‐S4 (2xChrIII).

MBT2-18-e70244-s004.xlsx (12.7KB, xlsx)

Fig. S1: Principal component analysis (PCA) of gene expression levels under different ethanol conditions (6% and 10%) at 1 and 10 h of fermentation, comparing strains 2–200‐2 and 2–200‐2‐S4.

MBT2-18-e70244-s001.docx (82.3KB, docx)

Table S1: Primers used to replace TUP1 with a kanamycin cassette, test for correct transformation and determine TUP1 copy number.

MBT2-18-e70244-s002.docx (14.2KB, docx)

Table S2: Experiment: 2023 09 12 TUP1_ABP1 placa1 Active filter: SYBR Green I/HRM Dye (465‐510).

MBT2-18-e70244-s006.xlsx (15.4KB, xlsx)

Table S3: Are under the Curve calculated by the control and two mutants from 2‐200‐2 with a TUP1 copy deletion.

MBT2-18-e70244-s003.xlsx (16.6KB, xlsx)

Acknowledgements

S.A. was supported by an FPI contract from Ministerio de Ciencia, Innovación y Universidades (ref. PRE2019‐088621). This project received funding from the Spanish government and EU ERDF‐FEDER projects PID2021‐126380OB‐C31 and PID2021‐126380OB‐C33 to A.Q. and E.B., respectively and PID2024‐161806OB‐C21 to A.Q. and E.B. Finally, IATA‐CSIC acknowledges the award of the Spanish government MICIU/AEI to the IATA‐CSIC as a Center of Excellence Accreditation Severo Ochoa (CEX2021‐001189‐S/MICIU/AEI/10.13039/501100011033) with A.Q. as the Principal Investigator.

Albillos‐Arenal, S. , Alonso del Real J., Adam A. C., Barrio E., and Querol A.. 2025. “Chromosome III Aneuploidy Enhances Ethanol Tolerance in Industrial Saccharomyces cerevisiae by Increasing the TUP1 Copy Number.” Microbial Biotechnology 18, no. 10: e70244. 10.1111/1751-7915.70244.

Funding: This work was supported by ‘Ministerio de Ciencia, Innovacion y Universidades’, CEX2021‐001189‐S/MICIU/AEI/10.13039/501100011033, PID2021‐126380OB‐C31, PID2021‐126380OB‐C33 to AQ, PID2024‐161806OB‐C21, PRE2019‐088621.

Data Availability Statement

The data that support the findings of this study are available in BioProject NCBI at https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1153811, reference number PRJNA1153811. These data were derived from the following resources available in the public domain: NCBI database, https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1153811.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1: DEGs calculated using the DESeq2 contrast 2‐200‐2 (3xChrIII) vs 2‐200‐2‐S4 (2xChrIII).

MBT2-18-e70244-s005.xlsx (167.3KB, xlsx)

Data S2: GO‐terms from the DEGs between 2‐200‐2 (3xChrIII) vs 2‐200‐2‐S4 (2xChrIII).

MBT2-18-e70244-s004.xlsx (12.7KB, xlsx)

Fig. S1: Principal component analysis (PCA) of gene expression levels under different ethanol conditions (6% and 10%) at 1 and 10 h of fermentation, comparing strains 2–200‐2 and 2–200‐2‐S4.

MBT2-18-e70244-s001.docx (82.3KB, docx)

Table S1: Primers used to replace TUP1 with a kanamycin cassette, test for correct transformation and determine TUP1 copy number.

MBT2-18-e70244-s002.docx (14.2KB, docx)

Table S2: Experiment: 2023 09 12 TUP1_ABP1 placa1 Active filter: SYBR Green I/HRM Dye (465‐510).

MBT2-18-e70244-s006.xlsx (15.4KB, xlsx)

Table S3: Are under the Curve calculated by the control and two mutants from 2‐200‐2 with a TUP1 copy deletion.

MBT2-18-e70244-s003.xlsx (16.6KB, xlsx)

Data Availability Statement

The data that support the findings of this study are available in BioProject NCBI at https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1153811, reference number PRJNA1153811. These data were derived from the following resources available in the public domain: NCBI database, https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1153811.

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