Transcriptomics-guided identification of engineering targets for improving salt tolerance in Saccharomyces cerevisiae

Abstract

Background

High-salinity conditions frequently impair the fermentation performance of Saccharomyces cerevisiae in industrial processes involving high-osmolarity substrates. Identifying genetic determinants that enhance salt tolerance is therefore essential for the development of robust yeast cell factories. In this study, a comparative transcriptomic analysis was performed to investigate the transcriptional responses of a salt-tolerant strain, E-158, and its parental strain, KF-7, under 1.25 M NaCl stress, with the aim of identifying potential targets for strain engineering.

Results

Comparative transcriptomic analysis revealed extensive transcriptional differences between E-158 and KF-7 under high-salt conditions, involving central carbon and nitrogen metabolism, peroxisome-associated oxidative stress responses, ion transport, cell wall-related processes, and sporulation-related pathways. Based on these profiles, two transcription factors (CUP9 and ZNF1) and three functional genes (DAL1, IDP2, and CTA1) were selected for functional validation. Overexpression or deletion of the transcription factors, as well as overexpression of the functional genes, was carried out in KF-7. Fermentation experiments under 1.25 M NaCl demonstrated that all engineered strains outperformed the parental strain. Among them, overexpression of CTA1 resulted in the greatest improvement, with glucose consumption and ethanol production increased by 35.04% and 45.66%, respectively, after 96 h of fermentation.

Conclusions

This study demonstrates that comparative transcriptomics can serve as an effective strategy for identifying engineering targets associated with salt tolerance in S. cerevisiae. The evaluated genes provide potential targets for strain improvement and offer insights for the rational design of yeast cell factories suited for high-salinity biofuel and bioproduct fermentation processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-026-03005-x.

Introduction

As a well-established eukaryotic model organism, Saccharomyces cerevisiae is widely employed in the food, chemical, and pharmaceutical industries [1]. Its extensive industrial use is supported by a solid understanding of its genetics and physiology, which facilitates genetic manipulation, as well as by its generally regarded as safe (GRAS) status, high ethanol productivity, and relatively strong stress tolerance [2]. Nevertheless, during industrial-scale fermentation, S. cerevisiae is frequently exposed to diverse environmental stresses, among which salt stress is particularly relevant. Such high-salinity conditions frequently occur during ethanol production from molasses, the manufacturing of soy sauce and other fermented seasonings, and the treatment or valorization of saline wastewater [3–5]. Under such conditions, salt stress can severely impair yeast growth and fermentation efficiency, thereby limiting industrial performance. Improving salt tolerance therefore remains an important objective for the development of robust yeast cell factories.

Current studies have demonstrated that S. cerevisiae primarily responds to high-salinity stress through the mitogen-activated protein kinases (MAPK) signaling network, notably via the high-osmolarity glycerol (HOG) and the cell wall integrity (CWI) pathways [6, 7]. In addition, salt tolerance involves multiple physiological processes, such as Na⁺ extrusion mediated by ENA-type P-type ATPases, ion homeostasis regulated by the calcineurin-Crz1 signaling axis, and nutrient and stress integration through the target of rapamycin (TOR) pathway [8–10]. However, the current understanding of yeast salt tolerance remains fragmented. Most existing studies have focused on standard laboratory strains and have typically examined individual pathways in isolation or a limited subset of genes [11–14]. Such reductionist approaches hinder a holistic understanding of how multiple regulatory layers act in concert to support robust salt tolerance, thereby constraining the rational engineering of industrial yeast strains.

In our previous work, an integrated engineering strategy combining atmospheric and room-temperature plasma (ARTP) mutagenesis, genome shuffling, and hybridization was applied to the industrial S. cerevisiae strain KF-7. This approach yielded the derivative strain E-158, which exhibited superior fermentation performance under high-salinity conditions, maintaining robust activity even at 1.5 M NaCl [15]. Notably, the salt tolerance of E-158 exceeds that of most previously reported yeast strains, which typically grow only up to 1.45 M NaCl and for which fermentation performance under such conditions has not been clearly demonstrated [16]. Initial comparative transcriptomic analysis of E-158 and KF-7 under 1.25 M NaCl stress revealed significant upregulation of ENA5 and CRZ1 [17]. Subsequent functional validation confirmed that overexpressing either gene in both E-158 and KF-7 further enhanced salt tolerance, demonstrating the efficacy of mining resistance genes from a tolerant strain [17]. While the molecular basis by which CRZ1 overexpression enhances salt tolerance in KF-7 has been previously characterized [5], the broader transcriptional and functional features underlying the superior salt tolerance of E-158 have yet to be systematically explored. The enhanced performance of E-158 under high-salinity conditions is therefore likely driven by coordinated adaptations across multiple cellular processes rather than by a single regulatory pathway.

In this study, comparative transcriptomic analysis was applied to characterize the transcriptional features associated with the salt-tolerant phenotype of E-158 under high-salt conditions. By integrating transcriptional profiling with targeted functional validation in the KF-7 background, candidate genetic factors linked to enhanced salt tolerance were identified, and their effects on fermentation performance were assessed. The results highlight transcriptional patterns associated with salt adaptation and provide candidate targets for further validation and rational strain engineering to improve yeast performance under saline fermentation conditions.

Materials and methods

Strains, plasmids, primers, and media

All strains and plasmids used in this study are listed in Table 1. The flocculating diploid industrial S. cerevisiae strain KF-7 was used as the parental strain [18]. The multi-tolerant strain E-158 was derived from KF-7 [15]. Escherichia coli DH5α (TransGen Biotech Co., Ltd., Beijing, China) was used for gene cloning and manipulation. Primers used in this study were presented in Additional file 1: Table S1.

Table 1.

Strains and plasmids used in the study

Strains and plasmids	Description	References
Strains
KF-7	MATa/α, Flo+	[18]
E-158	KF-7, ARTP mutagenesis, genome rearrangement, and hybridization	[15]
KF7Cas9	KF-7, Cas9-NAT	This study
KF7-ΔCUP9	KF-7, ΔCUP9	This study
KF7-ΔZNF1	KF-7, ΔZNF1	This study
KF7-CUP9	KF-7, Replacement of promoter PCUP9 to PHHF2	This study
KF7-ZNF1	KF-7, Replacement of promoter PZNF1 to PHHF2	This study
KF7-DAL1	KF-7, Replacement of promoter PDAL1 to PHHF2	This study
KF7-IDP2	KF-7, Replacement of promoter PIDP2 to PHHF2	This study
KF7-CTA1	KF-7, Replacement of promoter PCTA1 to PHHF2	This study
Plasmids
Cas9-NAT	AmpR, NAT1, Cas9	[19]
pMD19‑HHF2p	AmpR, 2 μm, HHF2 promoter	[20]
pMEL13	AmpR/KanMX, 2 μm, gRNA‑CAN1.Y	[19]
pMEL13-CUP9	AmpR/KanMX, 2 μm, gRNA‑CUP9	This study
pMEL13-ZNF1	AmpR/KanMX, 2 μm, gRNA‑ZNF1	This study
pMEL13-DAL1	AmpR/KanMX, 2 μm, gRNA‑DAL1	This study
pMEL13-IDP2	AmpR/KanMX, 2 μm, gRNA‑IDP2	This study
pMEL13-CTA1	AmpR/KanMX, 2 μm, gRNA‑CTA1	This study

The culture medium formulation was adopted from our previous study [15] to ensure experimental consistency and comparability. Specifically, YP medium (10 g/L yeast extract, 20 g/L peptone) supplemented with 20 g/L glucose (2% YPD) was used for cell growth. For yeast transformation, 2% YPD solidified with 20 g/L agar and supplemented with 50 µg/mL nourseothricin (NAT) and/or 100 µg/mL geneticin (G418) was employed for selection. E. coli transformants were selected on Luria-Bertani (LB) medium (5 g/L yeast extract, 10 g/L peptone, 10 g/L NaCl, pH 7.0) containing 100 µg/mL ampicillin (Amp), 100 µg/mL kanamycin (Kan), or 50 µg/mL NAT, as appropriate. For batch fermentation, cells were pre-cultivated in YP medium containing 50 g/L glucose (5% YPD). Fermentations were conducted under both non-stressed and salt-stressed conditions in YP medium containing 150 g/L glucose (15% YPD), with 1.25 M NaCl added for the salt-stressed condition.

Transcriptomic analysis

Batch fermentations were conducted using 15% YPD medium supplemented with 1.25 M NaCl. The growth and fermentation profiles of KF-7 and E-158 under these conditions have been reported previously [15, 17]. For transcriptomic analysis, cells were harvested at 48 h of fermentation, a time point corresponding to the mid-log phase when approximately half of the glucose had been consumed. Total RNA was extracted using the Yeast RNA Kit (Omega Bio-Tek, Norcross, USA) following the manufacturer’s instructions. The RNA-seq analysis was performed on an Illumina NovaSeq 6000 platform by Shanghai Majorbio Biopharm Technology Co., Ltd. (Shanghai, China). About 6 Gb of clean data for each sample were used to perform the transcriptional analysis.

The comparative transcriptomic analysis was performed as previously reported [5, 21]. Gene expression levels were quantified as transcripts per million (TPM). Differential expression analysis was conducted using DESeq2. Genes with an adjusted p-value < 0.05 and an absolute log₂ fold change (|log₂FC|) ≥ 1 were defined as differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the DEGs was conducted based on the KEGG database (http://www.genome.jp/kegg/), with a significance threshold of adjusted p-value < 0.05. Gene Ontology (GO) enrichment analysis of DEGs was carried out using the Metascape web server (https://metascape.org) with a significance cutoff of p < 0.005. Transcription factor (TF) analysis based on DEGs was performed using the YEASTRACT database (http://www.yeastract.com/).

Strains construction

Gene overexpression or deletion was performed using the CRISPR/Cas9 gene-editing system as described previously [22]. A specific guide RNA (gRNA) sequence (20 bp) for each gene was designed using CRISPOR (https://crispor.gi.ucsc.edu/). The phosphorylated forward primers, which contained the corresponding gRNA sequences, and the reverse primer (Additional file 1: Table S1) were synthesized by Tsingke Biotech Co., Ltd. (Beijing, China). These primers were used to amplify the pMEL13 plasmid by PCR. The resulting products were ligated using T4 DNA Ligase (Takara Bio Inc., Japan) to generate the gRNA plasmids. All plasmids were transformed into E. coli DH5α, and their sequences were verified by Sanger sequencing.

To overexpress genes, the native promoters were replaced with the HHF2 promoter. This promoter was chosen because its transcriptional level was approximately 1.6- to 40-fold higher than that of the target genes under salt stress and remained comparable between KF-7 and E-158 (Additional file 1: Table S2), enabling moderate and stable overexpression. For promoter replacement, repair fragments containing 60 bp homology arms were amplified from the pMD19-HHF2p [20] template using gene-specific primers. For gene deletion, repair fragments containing 60 bp of upstream and 60 bp of downstream homology arms (120 bp in total) were generated by primer annealing.

Yeast transformation was performed using the lithium acetate method as previously described [22]. The Cas9-NAT plasmid (500 ng) was first transformed into KF7 to generate the KF7Cas9 strain. Then, the gRNA plasmids and their corresponding repair fragments were co-transformed into KF7Cas9. For each transformation, approximately 500 ng of plasmids and 1.5–2.5 µg of repair fragments were used. Transformants were selected on 2% YPD plates supplemented with NAT and G418. Correct clones were verified by colony PCR and Sanger sequencing. Finally, the Cas9-NAT and gRNA plasmids were removed from the verified transformants following the method described by Mans et al. [19].

Batch fermentation

The fermentation conditions were adopted from our previous study [15] to ensure experimental consistency and comparability. Specifically, yeast cells were pre-cultured aerobically at 30 °C with shaking at 160 rpm for 16 h in 5% YPD medium. The cells were then harvested and inoculated into 100 mL of 15% YPD medium containing 1.25 M NaCl, at an initial cell density of 0.5 g dry cell weight (DCW)/L. Fermentation was carried out in a 300 mL Erlenmeyer flask sealed with a cotton plug. The process was performed at 35 ℃ in a water bath with agitation at 200 rpm for 96 h. Samples were collected every 24 h to determine DCW and the concentrations of glucose, ethanol, and glycerol. All fermentation experiments were conducted in biological triplicates.

Analytical methods

The fermentation broth was centrifuged at 8000 × g for 2 min, and the resulting cell pellets were used to determine the DCW as previously described [23]. The supernatant was filtered through a 0.22 μm membrane and appropriately diluted to determine the concentrations of the components, as previously described [20]. Concentrations of glucose and glycerol were quantified using high-performance liquid chromatography (HPLC; Shimadzu, Kyoto, Japan) equipped with a RID-10 A refractive index detector and an Aminex HPX-87 H column (Bio-Rad, Hercules, CA, USA). Ethanol concentration was determined by gas chromatography (GC 2010 Pro, Shimadzu, Japan) with a flame ionization detector (FID). Ethanol yields were calculated based on the amount of glucose consumed. All data are presented as the mean ± standard deviation. Statistical significance was determined using an independent samples t-test.

Results and discussion

Comparative transcriptomic profiling identifies multi-faceted responses in E-158 under salt stress

Under non-stress conditions (0 M NaCl), KF-7 and E-158 exhibited comparable fermentation performance, with no significant differences observed between the two strains (Additional file 2: Fig. S1). However, under high-salt stress (1.25 M NaCl), E-158 demonstrated a clear tolerance advantage over KF-7, achieving a 36% increase in ethanol production [15]. These results suggest that the distinct transcriptional profiles of E-158 under salt stress are likely linked to adaptive responses rather than inherent physiological differences. To explore the genetic basis underlying this enhanced tolerance, a comparative transcriptomic analysis was conducted between the two strains.

The analysis revealed 403 DEGs, of which 112 were upregulated and 291 were downregulated (Additional file 1: Table S3). Upregulated DEGs were significantly enriched in seven KEGG pathways, including tryptophan metabolism, peroxisome, fatty acid degradation, and biosynthesis of unsaturated fatty acids (Fig. 1a), while downregulated DEGs were enriched in six pathways, such as glycolysis/gluconeogenesis, pentose phosphate pathway (PPP), sulfur metabolism, and ribosome (Fig. 1b). The overall KEGG enrichment profile closely resembled that of the downregulated genes. Furthermore, GO enrichment analysis identified 231 terms, which were primarily associated with four functional categories: RNA-DNA processing and cyclin, metabolism and energy, cell wall and plasma, as well as ion and nutrient transport (Fig. 2, Additional file 1: Table S4).

Fig. 1.

KEGG enrichment analysis of upregulated a and downregulated b DEGs between E-158 and KF-7 under 1.25 M NaCl stress. The gene ratio indicates the number of DEGs involved in each KEGG pathway to the number of total DEGs

Fig. 2.

Network of enriched GO terms for all DEGs. Edges connect GO terms with a similarity score greater than 0.3, where the edge thickness corresponds to the degree of similarity. The size of each node is proportional to the number of genes enriched in the corresponding GO terms

Metabolic reprogramming

E-158 showed regulation in carbon metabolism related pathways such as glycolysis, PPP, galactose metabolism, and starch metabolism under high-salt stress. Compared to KF-7, E-158 exhibited significant downregulation of HXT1 and HXT3, while HXT7, HXT8 and HXT14 were significantly upregulated (Fig. 3). Among them, HXT1 and HXT3 encode low-affinity glucose transporters, whereas HXT7 encodes a high-affinity transporter. The apparent induction of the high-affinity transporter may be attributed to the lower residual glucose resulting from E-158’s superior glucose consumption rate over KF-7, as evidenced by a 52.6% reduction in residual glucose at 48 h [15]. In addition, HXK1 and GLK1, which encode hexose/glucose kinases for converting glucose to glucose-6-phosphate (G6P), were also upregulated. Besides serving as a substrate for glycolysis, G6P is a key precursor for the synthesis of cell wall polysaccharides [24] and stress molecules [25], which may contribute to stress resistance.

Fig. 3.

Transcriptional alterations in metabolic pathways between E‑158 and KF‑7 under high salt stress. Red indicates upregulation; Blue indicates downregulation. S, C, and N represent sulfur, carbon, and nitrogen metabolism, respectively

The repression of the PPP, a primary source of NADPH for biosynthesis [26], is expected to reduce intracellular NADPH levels. This effect may be partially compensated by the upregulation of IDP2, which encodes a cytosolic NADP⁺-dependent isocitrate dehydrogenase capable of generating NADPH. Meanwhile, the downregulation of aldehyde dehydrogenase genes (ALD3 and ALD6) may have multiple effects on cellular metabolism. On the one hand, reduced ALD3/6 activity may limit the conversion of acetaldehyde to acetate, thereby mitigating acetate-associated stress under high-salt conditions. On the other hand, it may also decrease NADPH generation via ALD6 and shift carbon flux from acetate toward ethanol.

Genes involved in sulfate assimilation and sulfur amino acid metabolism were markedly downregulated (Fig. 3). Sulfate is the principal sulfur source for the synthesis of cysteine and methionine, which serve as precursors for protein biosynthesis and glutathione production [27]. The downregulation of these genes may therefore reflect a metabolic strategy to suppress sulfur amino acid biosynthesis under salt stress. Similarly, ribosomal genes (RDN58-1/2, RDN37-1/2, RPS22A/B, RPL22A/B) were also significantly repressed, suggesting a global reduction in protein synthesis.

Tryptophan metabolism-related genes were significantly upregulated in E-158. TRP1 participates in tryptophan biosynthesis, while BNA1 and BNA4 function in de novo NAD biosynthesis through the kynurenine pathway, suggesting that E-158 may enhance NAD production to generate more energy under salt stress.

The upregulation of allantoin catabolism genes (DAL1, DAL3, DAL4, DUR1,2) in E-158 suggested an adaptive nitrogen reallocation strategy under high-salt stress (Fig. 3). Although the YP medium provided abundant amino acids as nitrogen sources, osmotic stress increased the cellular demand for nitrogen to support stress-responsive protein synthesis and osmoprotectant production. Allantoin catabolism, as part of the purine degradation pathway, generates ammonia that can be rapidly converted into various nitrogenous compounds to meet these enhanced demands [28]. Therefore, the induction of these genes may reflect enhanced mobilization and reutilization of nitrogen from purine degradation, improving nitrogen flux efficiency under stress conditions rather than indicating nitrogen limitation per se.

Enhancement of peroxisomes and mitochondria

In the E-158 strain, the expression of YGR168C is significantly up-regulated. This gene encodes a peroxisomal membrane protein that regulates peroxisome abundance. As the primary site for fatty acid metabolism [29, 30], peroxisomes harbor fatty acid β-oxidation that generates acetyl-CoA and reducing equivalents such as NADH. Compared to KF-7, genes involved in long-chain fatty acid transport (FAT3) and β-oxidation (POX1, POT1, ECI1, CTA1) were upregulated in E-158 (Fig. 4). Additionally, YIL057C (RGI2), a known regulator of lipid oxidation-related genes [31], showed increased expression as well. Furthermore, catalase encoded by CTA1 contributes to the scavenging of reactive oxygen species (ROS) generated under oxidative stress [32]. The coordinated up-regulation of these genes suggests that E-158 may contain more abundant and metabolically active peroxisomes, which likely plays an important role in its response to salt stress.

Fig. 4.

Representation of peroxisome and mitochondria enhancement in E‑158 under high salt stress. Red indicates upregulation

In contrast, mitochondrial transcriptional responses were relatively limited. Only a small subset of genes associated with mitochondrial gene expression and maintenance, including MRPL10, MRX3, and PET54, were significantly upregulated. Specifically, MRPL10 encodes a component of the mitochondrial ribosomal large subunit, MRX3 is involved in mitochondrial organization, and PET54 regulates the translation of mitochondrially encoded genes. Meanwhile, genes encoding the canonical pyruvate dehydrogenase complex (PDA1, PDB1, LAT1, and LPD1) showed no significant changes, and tricarboxylic acid (TCA) cycle genes were not broadly induced. This expression pattern suggests that mitochondrial adaptation to salt stress primarily occurs through functional adjustments of existing components rather than large-scale transcriptional activation of central metabolic pathways, thereby acting in coordination with the enhanced peroxisomal activity.

Overall, such coordination likely reflects a redistribution of carbon flux and reducing power, as enhanced peroxisomal β-oxidation increases the generation of acetyl-CoA and NADH, while mitochondrial pathways remain largely transcriptionally stable, consistent with previous findings [33].

Maintenance of ionic homeostasis

Maintaining intracellular ion homeostasis is critical for yeast survival under high-salt stress. In response, strain E-158 exhibits a coordinated transcriptional reprogramming of ion transport system. Key genes for sodium export, including the sodium pumps (ENA1, ENA5) and their transcriptional regulator CRZ1, were upregulated. Concurrently, genes encoding the housekeeping proton pump PMA1 and its regulator PMP2 were downregulated. This shift implies a strategic reallocation of cellular energy, diverting energetic resources from the energy-intensive activity of Pma1 to the crucial sodium export mediated by Ena1 and Ena5. Consistent with established salt-tolerance mechanisms [5, 17], this strategy optimizes energy utilization by prioritizing essential ion homeostasis over general metabolic processes.

Furthermore, E-158 exhibited significant upregulation of genes involved in iron transport (ARN2, SIT1) and zinc homeostasis (IZH2/3/4). Both iron and zinc are essential micronutrients that function as cofactors of critical cellular processes. Iron is a key cofactor for catalase (CAT), superoxide dismutase (SOD), ribonucleotide reductase (RNR), cytochromes, and iron-sulfur cluster proteins [34]. Zinc also serves as a cofactor for SOD and CAT, in addition to regulating lipid metabolism, including the biosynthesis of phosphatidylinositol and sphingolipids [35, 36]. The concerted upregulation of these genes likely ensures an adequate supply of trace elements to support vital functions, such as ROS scavenging, respiration, DNA synthesis, and lipid metabolism, under salt stress.

Adjustment of cell biogenesis

Genes involved in cell wall organization, such as TIR3 and PAU24 (encoding mannoproteins), NCW2 (encoding a GPI-anchored protein involved in cell wall remodeling) and KNH1 (involved in β-1,6-glucan synthesis), were significantly upregulated. Conversely, expression of genes encoding structural cell wall proteins, including PIR3, CWP2, SED1, PST1, YGP1, and EXG2, was strongly repressed, suggesting a reduction in cell wall rigidity. Collectively, these transcriptional shifts point to an active remodeling of the cell wall by E-158 to enhance its resilience under high-salt stress.

A group of genes critical for meiosis and sporulation were significantly upregulated in E-158, including NDT80 (a meiosis- specific transcription factor), RIM4 (required for pre-meiotic DNA replication and recombination), AMA1 (a meiosis-specific activator of the anaphase-promoting complex/cyclosome), SMK1 (essential for spore wall assembly), AQY1 (a spore-specific aquaporin), BEM4 (involved in cell polarity), and CRR1/SPS1/SPS2 (involved in spore membrane formation). This coordinated induction suggests that sporulation-related pathways are more active in E-158 under salt stress conditions.

We further examined the transcriptional behavior of key components of the HOG and CWI pathways, which are central regulators of osmotic stress adaptation in yeast. Most genes in these pathways did not exhibit significant transcriptional changes, whereas a small number showed significant downregulation (Additional file 1: Table S5). This suggests that the enhanced salt tolerance of E-158 relative to KF-7 may not rely primarily on transcriptional regulation of these core signaling pathways.

Regulation of key TFs

Under high-salt stress, 18 TFs were differentially expressed in E-158: eight upregulated (ACA1, CUP9, ZNF1, CRZ1, YGR067C, MIT1, RDR1, NDT80) and ten downregulated (CIN5, SWI5, MSS11, NRG2, ROX1, TOS4, TOS8, IME1, CYC8, TYE7) (Additional file 1: Table S6). Several of these TFs are associated with salt tolerance. For instance, CRZ1 overexpression has been shown to enhance salt tolerance in yeast [5, 17], and ZNF1 deletion increases salt sensitivity [37], while its overexpression confers osmotic stress resistance [38]. It is therefore reasonable to speculate that the upregulation of CRZ1 and ZNF1 critically contributes to salt resistance in E-158. However, some TFs whose upregulation is typically linked to salt tolerance were downregulated in E-158. These include CIN5, whose overexpression is known to improve salt tolerance [39], and ROX1, whose loss of function leads to dysregulated ergosterol biosynthesis, resulting in toxic Na⁺ accumulation and increased salt sensitivity [40]. Their downregulation in E-158 suggests that the strain may employ a distinct regulatory strategy, prioritizing the modulation of a specific subset of TFs to fine-tune its adaptation response.

Additionally, CUP9, a transcriptional repressor of peptide transport, was upregulated. Given the nitrogen-limited intracellular environment indicated by earlier GO analysis, this upregulation implies a physiological role beyond its canonical function. Notably, CUP9 mutants exhibit copper sensitivity [41], supporting it potential involvement in metal ion homeostasis. Thus, it is hypothesized that CUP9 may help regulate ion balance under high-salt conditions, contributing to E-158’s tolerance.

Taken together, the transcriptional features identified in this study highlight both previously reported stress adaptation strategies in yeast and potential new contributors to salt tolerance (Additional file 1: Table S7). In E-158, salt tolerance is associated with coordinated transcriptional reprogramming involving central carbon metabolism, nitrogen reallocation, mitochondrial and peroxisomal functions, redox homeostasis, ion transport, and cell wall-related processes (Fig. 5). While these patterns likely contribute to the enhanced adaptability of E-158 under osmotic stress, further studies under non-stressed conditions are needed to distinguish intrinsic strain-specific characteristics from stress-induced responses.

Fig. 5.

A schematic diagram illustrating the transcriptional responses associated with salt tolerance in E-158 under 1.25 M NaCl. Red indicates upregulation; Blue indicates downregulation. S, C, and N represent sulfur, carbon, and nitrogen metabolism, respectively

Identification of genes contributing to salt tolerance

Comparative transcriptomic analysis suggested that specific functional genes and TFs contribute to salt tolerance. Candidates such as DAL1 (nitrogen metabolism), IDP2 (energy production and NADPH synthesis), CTA1 (ROS detoxification), along with the TFs CUP9 and ZNF1, were all significantly upregulated and expressed at relatively high levels in E-158 (Additional file 1: Table S2). For functional validation, the TFs were subjected to both overexpression and knockout, and the functional genes were overexpressed in the parental strain KF-7.

After 96 h of fermentation under 1.25 M NaCl, all engineered strains exhibited superior performance to the parental strain KF-7 (Fig. 6; Table 2). Interestingly, both overexpression and knockout of the TFs CUP9 and ZNF1 led to improved fermentation under high salt stress (Fig. 6a-b). This enhancement in the knockout strains may be linked to the complexity of the regulatory network, which could involve compensatory mechanisms. The superior effect of CUP9 overexpression over that of ZNF1 indicates a more prominent positive regulatory function for CUP9 in salt tolerance. The newly identified function of CUP9 in this study warrants further investigation.

Fig. 6.

Fermentation performance of engineered strains under 1.25 M NaCl. Data are averages of biological triplicates (error bars represent SD)

Table 2.

Fermentation performance of engineered strains under 1.25 M NaCl

Strains	Glucose consumption (g/L)	Improvement	Ethanol production (g/L)	Improvement	Ethanol yield (g/g consumed glucose)
KF-7	75.07 ± 0.17	-	23.57 ± 0.83	-	0.31 ± 0.01
E-158	131.02 ± 1.37*	74.53%	42.12 ± 1.01*	78.69%	0.32 ± 0.00
KF7-ΔCUP9	81.64 ± 6.45	8.75%	26.19 ± 2.20	11.13%	0.32 ± 0.00
KF7-ΔZNF1	81.12 ± 2.60	8.06%	26.43 ± 0.51	12.10%	0.33 ± 0.00
KF7-ZNF1	84.48 ± 11.38	12.54%	28.12 ± 4.09	19.31%	0.33 ± 0.00
KF7-IDP2	88.47 ± 3.45*	17.86%	29.06 ± 1.80*	23.28%	0.33 ± 0.01
KF7-CUP9	93.57 ± 2.06*	24.65%	31.03 ± 1.11*	31.62%	0.33 ± 0.00
KF7-DAL1	93.86 ± 3.01*	25.03%	31.49 ± 1.22*	33.57%	0.34 ± 0.00
KF7-CTA1	101.37 ± 4.69*	35.04%	34.34 ± 2.05*	45.66%	0.34 ± 0.00

All data were calculated based on 96 h of fermentation. Values indicate mean ± standard deviation of biological triplicates. Differences were considered statistically significant (*p < 0.05) relative to the parental strain KF-7

The rank order of improvement in fermentation performance conferred by gene overexpression was as follows: ZNF1 < IDP2 < CUP9 < DAL1 < CTA1. Overexpression of the functional genes IDP2, DAL1, and CTA1 all contributed to enhanced salt tolerance. The beneficial effect of IDP2 overexpression is likely attributed to its role in promoting NADPH synthesis, thereby strengthening the cellular antioxidant defense system [42, 43]. The enzyme encoded by DAL1 catalyzes the first step of allantoin degradation. Its overexpression is expected to increase ammonia supply, thereby providing the cell with a sufficient nitrogen source. However, to our knowledge, a direct link between DAL1 and stress tolerance has not been established in previous studies. Notably, the CTA1-overexpressing strain KF7-CTA1 exhibited the best performance among all engineered strains. It consumed 101.37 ± 4.69 g/L glucose and produced 34.34 ± 2.05 g/L ethanol, representing increases of 35.04% and 45.66%, respectively, compared with KF7 (Table 2). These findings strongly suggest that elevated intracellular ROS levels under high-salt conditions pose a major threat to cellular function. The enhanced catalase activity resulting from CTA1 overexpression effectively alleviates this oxidative stress, thereby protecting the cells and sustaining their metabolic activity.

While the overexpression of individual genes improved salt tolerance, the engineered strains did not surpass the performance of E-158, underscoring the complexity of this polygenic trait. A future synergistic approach combining multiple genetic perturbations may achieve a more complete phenotype. Overall, this work offers candidate targets for further validation and rational strain engineering in diverse yeast strains under high-salinity fermentation conditions.

Conclusion

This study employed comparative transcriptomic analysis to characterize molecular features associated with the salt-tolerant phenotype of S. cerevisiae E-158. Distinct transcriptional patterns were identified under high-salt conditions, indicating broad cellular adjustments in the tolerant strain. Functional validation in the KF-7 background demonstrated that two TFs (CUP9 and ZNF1) and three functional genes (IDP2, DAL1, and CTA1) significantly contribute to salt tolerance, with CTA1 overexpression conferring the most pronounced improvement. To our knowledge, this study provides initial functional evidence supporting the involvement of CUP9, DAL1, IDP2, and CTA1 in salt stress-associated responses in yeast. Collectively, these findings expand our understanding of transcriptional adaptations linked to salt tolerance and suggest potential genetic targets for further evaluation in efforts to improve yeast salt tolerance.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

MT L and L W performed experiments and analyzed data. MT L, CY X and YQ T designed the work. MT L wrote the main manuscript. CY X, M G and YQ T revised the manuscript and acquired financial support. All authors read and approved of the final manuscript.

Funding

This study was financially supported by the National Natural Science Foundation of China (52300169).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. The raw sequence data can be accessed in the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/) through the SRA accession number PRJNA642097.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.