Molecular Characterization of Propolis-Resistant Saccharomyces cerevisiae Obtained by Evolutionary Engineering

Abstract

Propolis is a highly complex, resinous natural product collected by honeybees from tree leaves and buds and mixed with pollen and enzymes. Due to its antimicrobial properties, it has various medical and industrial applications. As a nonconventional strategy, the use of propolis was suggested to control contaminating yeast growth in ethanol fermentations, without significantly affecting the starter yeast of the fermentation, Saccharomyces cerevisiae. In this study, we have developed a highly propolis-resistant S. cerevisiae strain using evolutionary engineering. The evolved strain FD11 had a higher growth rate (µ_max = 0.21 h⁻¹) than the reference strain (µ_max = 0.17 h⁻¹) under propolis stress and showed cross-resistance against caffeine stress. Moreover, it had significantly lower reactive oxygen species levels and higher cell wall integrity than the reference strain. Comparative transcriptomic analysis results revealed that the genes involved in oxidoreductase activity, transmembrane transporter activity, unfolded protein binding and pleiotropic drug resistance were upregulated in FD11. Whole genome re-sequencing analysis revealed mutations in multiple genes including PDR1, encoding a transcription factor regulating pleiotropic drug response. The results imply the importance of pleiotropic drug response and cell wall integrity in propolis resistance and the potential of using propolis-resistant, robust yeast strains in industrial applications.

1. Introduction

Propolis is a resinous, sticky and dark-colored natural compound that is produced by honeybees by mixing their own waxes with the resins derived from plants. The meaning of the word propolis is “defense of the city”. Honeybees use propolis to build and repair their hives, because propolis forms a physical barrier against predators, moisture and wind, owing to its resinous and waxy nature [1]. The chemical composition of propolis is quite complex, as more than 300 compounds have been identified in propolis samples, including polyphenols, phenolic aldehydes, sesquiterpene quinines, coumarins, amino acids, steroids and inorganic compounds. The chemical composition may vary depending on the season and differences in bee species, vegetation and region [2].

Propolis has been used by humankind since ancient times, not only as an adhesive compound, to seal cracks and protect surfaces, but also for the treatment of fever, pain and wounds. It has been an important compound for traditional medicine and drug development [3,4]. It has various important biological and pharmacological characteristics such as antimicrobial, antitumor, antioxidant, anti-inflammatory activity, immunomodulatory, cytostatic and therapeutic activities [4]. Propolis has also been shown to have a high potential in wound healing and tissue regeneration. In skin wound healing, it can help reduce scar formation and healing time and accelerate tissue repair. Biofilm formation is an important issue that leads to impaired and delayed wound healing. It has been suggested that the antimicrobial activity of propolis and its ability to inhibit biofilm formation are the most important biological characteristics of propolis, which can inactivate diverse bacteria including Staphylococcus aureus, streptococci and some tuberculosis mycobacteria that are resistant to many antibiotics. Thus, to treat wound biofilms, propolis can be used as a suitable biomaterial [4]. The antimicrobial activity of propolis originates from flavonoids, aromatic acids and esters present in resin. Ferulic and caffeic acid also contribute to the antimicrobial activity of propolis. The antimicrobial effect of propolis is expressed with synergism between flavonoids, hydroxy acids and sesquiterpenes [5]. The antioxidant activity of propolis mainly results from its phenolic compounds and flavonoids [6]. With its wide range of biological and pharmacological activities and complex chemical composition, propolis presents a high potential for innovative advancements in medical and industrial fields. Thus, understanding the molecular mechanisms underlying cellular propolis response and resistance is crucial for its continuous use in industrial and therapeutic applications.

The yeast Saccharomyces cerevisiae is one of the most widely used microorganisms, not only for traditional biotechnological applications such as baking, brewing and distiller’s fermentations [7] but also for industrial bioethanol production [8]. It is also a commonly used eukaryotic model organism to understand the complex regulatory processes and pathways that exist in higher organisms [9], including antioxidant, apoptosis and aging pathways. Thus, studies with yeast as a model organism are crucial to understand the molecular mechanisms of oxidative stress and its consequences, including diverse human diseases [10,11]. Given a high degree of homology between the yeast and the human genome, yeast gene deletion mutants have also been successfully employed to understand the molecular basis of the antioxidant and anti-aging properties of natural compounds for ultimate human use [12].

Some studies in the literature have investigated the response of S. cerevisiae to propolis treatment. For example, Cigut et al. (2011) found that, when propolis was applied to yeast cells, their intracellular oxidation decreased. Changes were also observed at the mitochondrial proteome level, including antioxidant proteins and proteins related to ATP synthesis. The increase in antioxidant protein levels was associated with decreased intracellular oxidation [6]. Using S. cerevisiae as a eukaryotic model organism, de Sá et al. (2013) investigated the mechanisms of the antioxidant effects of propolis. It was reported that, when wild-type and antioxidant-deficient deletion strains of S. cerevisiae were pretreated with an alcoholic propolis extract, the levels of reactive oxygen species (ROS) generation and of lipid peroxidation reduced upon oxidative stress, except for the superoxide dismutase deletion strain sod1Δ. It was concluded that the significant antioxidant effect of propolis is related to its contribution to the protection of membrane lipids from oxidative (H₂O₂) stress; its activity in maintaining the redox status by scavenging ROS (in response to O₂^•− stress mediated by menadione); and its activation of Cu/Zn superoxide dismutase, a crucial antioxidant enzyme [13]. De Castro et al. (2011) showed that propolis can induce an apoptotic cell death response in S. cerevisiae, but increased exposure to propolis leads to an increase in the necrosis response. To shed light upon the key genes and pathways related to propolis sensitivity in S. cerevisiae, the full collection of approximately 4800 deletion strains of S. cerevisiae were also screened for propolis sensitivity. Consequently, 138 deletion strains with varying levels of propolis sensitivity were identified, compared to the wild-type strain [14]. To understand the molecular mechanisms of cell death caused by high propolis concentrations in S. cerevisiae, the transcriptomic response of a wild-type S. cerevisiae strain to propolis treatment was also investigated in a related study [15]. The results revealed that several eukaryotic pathways, particularly including those related to oxidative stress, the mitochondrial electron transport chain, the regulation of macroautophagy and vacuolar acidification, were affected by propolis treatment.

Apart from the studies that use S. cerevisiae as a eukaryotic model organism to investigate the molecular mechanisms of propolis response, the potential use of propolis to selectively target contaminating yeasts in ethanolic fermentations as a useful nonconventional strategy was suggested in a more recent study [16]. It was reported that propolis could strongly inhibit Dekkera bruxellensis, one of the most important contaminant yeasts of alcoholic fermentation processes, without substantially inhibiting S. cerevisiae, the starter yeast. Thus, the development of highly propolis-resistant S. cerevisiae strains may be industrially desirable to improve the efficiency of ethanolic fermentation processes.

Evolutionary engineering, also known as adaptive laboratory evolution (ALE), is a powerful strategy to improve industrially important microbial phenotypes with an unknown molecular basis [17,18,19]. It is based on nature’s “engineering” principle by mutation and selection and involves continuous evolution procedures, which include a systematic selection method that favors a desired microbial phenotype [17,20]. Evolutionary engineering has been widely used to improve microbial strains for biofuel and chemical production [8,21]. It has also been applied to improve the robustness or resistance of the yeast S. cerevisiae against diverse industrial stressors, including coniferyl aldehyde [22] and 2-phenylethanol [23].

The aim of this study was to develop a highly propolis-resistant and genetically stable S. cerevisiae strain using evolutionary engineering and to analyze the evolved strain at the physiological, transcriptomic and genomic levels, to shed light on the molecular basis of propolis resistance in S. cerevisiae. Considering that the previous studies on the molecular mechanisms of propolis response in S. cerevisiae focused on the response of wild-type strains or propolis-sensitive deletion mutants to propolis treatment [13,14,15], the molecular investigation of a highly propolis-resistant S. cerevisiae strain was performed for the first time in this study, and the potential use of propolis-resistant, robust yeast strains for industrial applications is discussed.

2. Materials and Methods

2.1. Yeast Strains, Growth and Storage Conditions

The S. cerevisiae haploid laboratory strain CEN.PK 113-7D (MATa, MAL2-8c, SUC2) was used as the reference strain, and it was kindly provided by Prof. Dr. Jean-Marie François and Dr. Laurent Benbadis (University of Toulouse, France). To increase the genetic diversity of the initial population for evolutionary selection experiments, chemical mutagenesis was applied to the reference strain using ethyl methanesulfonate (EMS) (Sigma-Aldrich, Hamburg, Germany), under conditions leading to a 10% survival rate upon EMS treatment, as described previously [24]. Propolis (from Kartal, Istanbul, Türkiye) was kindly provided by Prof. Dr. Oğuz Öztürk (Istanbul University, Türkiye), and it was diluted with ethanol/water (60:40 v/v), as described previously [25].

Unless otherwise stated, cultures were grown aerobically in an orbital shaker (Sartorius Certomat, Göttingen, Germany), at 30 °C and 150 rpm, using Yeast Minimal Medium (YMM) (2% (w/v) dextrose (Sigma-Aldrich, Hamburg, Germany), 0.67% (w/v) yeast nitrogen base without amino acids (Becton, Dickinson and Company, Sparks, MD, USA)) or Yeast Complex Medium (YPD) (1% (w/v) yeast extract (Merck, Darmstadt, Germany), 1% (w/v) peptone (Riedel-de Haen, Seelze, Germany), 2% (w/v) dextrose (Sigma-Aldrich, Hamburg, Germany)). For solid cultures, agar (BDDifco^TM, Franklin Lakes, NJ, USA) was added to the YMM and YPD media to a final concentration of 2% (w/v). Growth was monitored spectrophotometrically (Shimadzu UV-1700, Tokyo, Japan), based on optical density measurements at 600 nm (OD₆₀₀). Stock cultures were prepared in 30% (v/v) glycerol and stored at −80 °C.

2.2. Evolutionary Engineering Procedure

To obtain propolis-resistant S. cerevisiae strains, an evolutionary engineering selection strategy was performed, based on successive batch cultivation of the EMS-mutagenized initial culture under continuously applied and gradually increased propolis stress. For this purpose, first, the initial propolis concentration to be applied during the selection experiments was determined by inoculating the precultures of the reference strain and its EMS-mutagenized population into 10 mL YMM (control) and 10 mL YMM containing 60–650 µg/mL propolis in 50 mL culture tubes, to an initial OD₆₀₀ of 0.25 (approximately 3.5 × 10⁶ cells/mL). During growth at 30 °C and 150 rpm, the OD₆₀₀ values of the cultures were measured, and the survival of the cultures was calculated by dividing the “OD₆₀₀ of the culture under propolis stress” by the “OD₆₀₀ of the culture under control (non-stress) conditions”, at the 24th and 48th hour of cultivation.

The evolutionary engineering procedure was then applied as follows: the EMS-mutagenized initial population was inoculated into 10 mL YMM in 50 mL culture tubes to an initial OD₆₀₀ of 0.25 (approximately 3.5 × 10⁶ cells/mL) and incubated overnight at 30 °C and 150 rpm as a preculture. Two 50 mL-culture tubes that contained 10 mL YMM with and without 150 µg/mL propolis were inoculated with the same amount of the preculture and cultivated for 24 h. They were named as the first population of the propolis stress selection and its control. The first population was then transferred to fresh YMM containing 160 µg/mL propolis, as the second passage. The initial propolis stress level (150 µg/mL) was gradually increased by 10 µg/mL at each successive batch passage during selection, up to 710 µg/mL in 57 passages. Survival was determined for each passage by dividing the OD₆₀₀ value of the passage grown with propolis stress by that of the same culture grown under control conditions. Stock cultures were also prepared for each population (passage). The last (57th) population of the selection was diluted and plated on solid YMM, and twelve individual colonies were picked randomly from the last population culture for further analysis.

2.3. Estimation of Stress Resistance

The resistance of the mutant strains and the reference strain against propolis and other stress factors was estimated using both the semi-quantitative spot assay method and the quantitative Most Probable Number (MPN) method [26]. For the spot assay, individual mutant strains and the reference strain were inoculated into 10 mL YMM in 50 mL culture tubes at an initial OD₆₀₀ of 0.2 (approximately 2.8 × 10⁶ cells/mL) and incubated at 30 °C and 150 rpm. During the exponential growth phase of the cultures, at an OD₆₀₀ value of about 4.0 (approximately 5.6 × 10⁷ cells/mL), the cultures were centrifuged at 10,000× g for 3 min. Culture pellets were diluted from 10⁻¹ to 10⁻⁶ in YMM and spotted on solid YMM plates including 200–500 µg/mL propolis and control plates without propolis. To estimate cross-resistance against other stress factors by spot assay, the following stress factor concentrations were used in the YMM plates: 0.6–0.8 mM NiCl₂ (Merck, Darmstadt, Germany)_, 2.2 mM CoCl₂, (Fluka, Charlotte, NC, USA), 0.4 mM CuSO₄ (Sigma-Aldrich, Hamburg, Germany), 0.5 mM H₂O₂ (Merck, Darmstadt, Germany)_, 3.0 mM CrCl₃ (Acros Organics, Fair Lawn, NJ, USA), 10 mM ZnCl₂ (Carlo Erba, Milan, Italy)_, 1.0 M MgCl₂ (Merck, Darmstadt, Germany)_, 30–40 mM NH₄FeSO₄ (Merck, Darmstadt, Germany)_, 15 mM MnCl₂ (Merck, Darmstadt, Germany), 10% (v/v) ethanol (J.T Baker, Deventer, Netherlands), 12 mM AlCl₃ (Merck, Darmstadt, Germany)_, 1.0 M NaCl (Merck, Darmstadt, Germany)_, 150 µg/mL geneticin (Thermo Fisher, Waltham, MA, USA) and 10 mM caffeine (Merck, Darmstadt, Germany). All the plates, including the control YMM plates without any stress factors, were incubated at 30 °C for 72 h. All the spot assay experiments were performed in three biological replicates.

The MPN method was applied for the statistical estimation of viable cell numbers in stress-exposed cultures. Firstly, serial dilutions were applied in 96-well plates including 180 µL of YMM with 200 µg/mL, 500 µg/mL and 710 µg/mL propolis concentrations and without propolis (control). Dilutions were made in the range of 10⁻¹ to 10⁻⁸ for five parallel samples. MPN tables that were based on Poisson regression were used for quantification upon 96 h incubation [27]. The resistance to various stress types was defined as the percent survival rate, which was calculated according to Equation (1), as described previously [26].

Percent Survival Rate = [number of viable cells upon stress treatment/number of viable cells without any stress treatment] × 100

(1)

2.4. Physiological Analyses

The physiological analyses involved optical density (OD₆₀₀) and cell dry weight measurements to monitor cell growth, and the determination of cellular metabolite levels. Precultures of the mutant strain and the reference strain were grown overnight at 30 °C and 150 rpm, in 50 mL culture tubes containing 10 mL YMM. The cultures were then inoculated into 500 mL flasks containing 100 mL YMM with 200 µg/mL propolis and without propolis (control), at an initial OD₆₀₀ value of 0.25 (approximately 3.5 × 10⁶ cells/mL), and incubated at 30 °C and 150 rpm. OD₆₀₀ values were measured, and 2 mL samples were collected at specific time intervals for metabolite and cell dry weight analysis, as described previously [26]. For metabolite analysis, 1 mL of culture supernatants was centrifuged at 10,000× g for 5 min, and the supernatants were filtered through a 0.22 µm pore-size filter. Analysis of residual glucose, ethanol, acetate and glycerol was performed using HPLC (Shimadzu Series 10A HPLC, Shimadzu Co., Kyoto, Japan) at 60 °C, using 5 mM H₂SO₄ as the mobile phase, with a flow rate of 0.6 mL/min and an injection volume of 20 µL, as described previously [26]. An Aminex HPX-87H column (Bio-Rad Laboratories, Hercules, CA, USA) was also used. The intracellular trehalose and glycogen content was determined enzymatically, as described previously [26,28]. All physiological analysis experiments were performed in triplicate.

2.5. Determination of Intracellular Reactive Oxygen Species (ROS) Content

Intracellular ROS amounts were determined using fluorescent intensity measurements, as described previously [29]. The oxidant-sensitive probe 2′,7′-dichlorofluorescein diacetate (DCF-DA) (Sigma-Aldrich, Hamburg, Germany) was used to measure intracellular oxidation levels. Briefly, a 5 mM DCF-DA stock solution in ethanol was added to cultures at their mid-exponential phase of growth (2 × 10⁷ cells/mL) (to a final concentration of 10 µM) and incubated at 28 °C for 30 min in the dark, to allow probe uptake. Cultures were then harvested at 10,000× g for 5 min, washed twice with PBS and lysed by vortexing them with glass beads. The samples were then centrifuged at 10,000× g for 5 min, and the supernatants were collected in fresh microfuge tubes for fluorescence measurements (excitation wavelength: 504 nm, emission wavelength: 524 nm). The experiments were performed in triplicate.

2.6. Lyticase Sensitivity Assay

The lyticase sensitivity assay was performed, as described previously [30], with slight modifications. Briefly, overnight precultures of the mutant strain and the reference strain were inoculated into 20 mL YMM in 100 mL Erlenmeyer flasks to an initial OD₆₀₀ of 0.2 (approximately 2.8 × 10⁶ cells/mL), both in the presence and absence of 200 µg/mL propolis stress. They were incubated at 30 °C, 150 rpm until the stationary phase of growth. The cultures were then harvested (10,000× g, 5 min), and 0.9 OD₆₀₀/mL of cells was resuspended in 10 mL of 10 mM Tris/HCl buffer (pH 7.4), supplemented with 40 mM β-mercaptoethanol. After the incubation of the samples at 25 °C for 30 min, lyticase (2 U/mL) was added, and the cell lysis was monitored by measuring the decrease in absorbance during incubation at 30 °C and 150 rpm. The assay was performed as three biological replicates. The measured OD₆₀₀ values were divided by the initial OD₆₀₀ value of the cultures, and the ratio was multiplied by 100 to calculate the lyticase resistance.

2.7. Whole Genome Transcriptomic Analysis

An Agilent yeast DNA microarray system (Agilent Technologies, Santa Clara, CA, USA) was used for the whole genome transcriptomic analysis, as described previously [26]. Total RNA was isolated from the mutant strain and the reference strain cultures when they were grown until the mid-exponential phase (2 × 10⁷ cells/mL) in 2% (w/v) YMM in 100 mL Erlenmeyer flasks at 30 °C and 150 rpm. An RNeasy Mini Kit (Qiagen, German Town, MD, USA) was used for RNA isolation. RNA concentrations were then measured using a UV–Vis spectrophotometer (NanoDrop 2000, Thermo Fisher Scientific, Waltham, MA, USA), and the RNA integrity number (RIN) was determined using an Agilent 2100 BioAnalyzer and the Agilent RNA 6000 Nano Assay Kit (Agilent Technologies, Santa Clara, CA, USA). RNA samples with RIN values higher than 8 were used for microarray analysis. A One-Color Microarray-Based Gene Expression Analysis Kit (Low-Input Quick Amp Labeling; Agilent Technologies, Santa Clara, CA, USA) was used for the synthesis of cDNA and then the Cy3-labeled cRNA, using the T7 RNA Polymerase Blend as labeled with cyanine 3 (Cy3). As the internal controls for the microarray experiment, an Agilent RNA Spike-In Kit (Agilent Technologies, Santa Clara, CA, USA) was used. An Absolutely RNA Nanoprep Kit (Agilent Technologies, Santa Clara, CA, USA) was used to purify the Cy3-labeled samples. The samples were then hybridized on a Yeast (V2) Gene Expression Microarray, 8 × 15 arrays (G4813A; Agilent Technologies, Design ID: 016322) upon incubation in the hybridization chamber of a hybridization oven (Agilent Technologies, Santa Clara, CA, USA) at 65 °C for 17 h. Following hybridization, Agilent C Scanners scanned the microarray slides, which were washed according to the manufacturer’s instructions. Agilent GeneSpring GX Software (v 14.5) (Agilent Technologies, Santa Clara, CA, USA) was used to analyze the primary data. Quantile Normalization was used for the normalization of the signals. Using the Bonferroni Family-Wise Error Rate (FWER) correction, statistical significance was determined. For significantly different gene expression data, corrected p values of less than 0.05 were accepted. Three biological replicates were used for microarray analysis. Differentially expressed genes (by at least a two-fold change) with a p value < 0.05 were categorized based on their function, using the FunCat database [31]. The microarray work described in this study is fully MIAME-compliant, and the microarray data have been deposited in the Gene Expression Omnibus Database under the accession number GSE280996. (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE280996) (accessed on 15 December 2024).

2.8. Whole Genome Re-Sequencing Analysis

For the whole genome re-sequencing analysis, the mutant strain and the reference strain were grown overnight, using 100 mL of YPD in 500 mL shake flasks at 30 °C, 150 rpm. Prior to sequencing, genomic DNA was isolated from both strains, using the MasterPure™ DNA Purification Kit (Epicentre, Bethlehem, PA, USA), according to the manufacturer’s instructions. The quantification and quality assessment of the isolated DNA samples were made by UV–Vis spectrophotometry (NanoDrop 2000, Thermo Fisher Scientific, Waltham, MA, USA). Genomic DNA libraries were then prepared with 100 ng purified DNA, using the Ion Xpress Plus Fragment Library Kit and Ion 540™ Chip Kit (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s protocol. The Ion 540™ Chip had a read length of up to 200 bp, generating 60–80 million reads. DNA samples of the mutant strain (FD11) and the reference strain were then sequenced on the Ion S5 Next-Generation Sequencing Platform (Thermo Fisher Scientific, Waltham, MA, USA) and the coupled automated library prep platform Ion Chef (Thermo Fisher Scientific, Waltham, MA, USA). Raw data were deposited in the NCBI Sequence Read Archive (SRA) database under BioProject PRJNA 1165934. Fast QC (v.0.11.5) software (Babraham Bioinformatics) was used for checking the quality of the raw data reads. Adapter sequences/low-quality reads were trimmed using Trimmomatic (v.0.32) software [32]. Bowtie2 (v.2.4.5) [33] was used to align the reads in each input sample to the reference genome sequence of S. cerevisiae CEN.PK 113-7D (GCA_000269885.1) [34]. SAMtools (v.1.15.1) [35] were applied to process the data and calculate genotype likelihoods, and BCFtools (v.1.15.1) were used to call variants [35]. VCFtools (v.v.1.16) [36] and custom shell commands were applied to compare variants found in the reference and mutant strains. In addition, SnpEff (4.3p) [37] and SIFT 4G (v2.4) [38] were used to assess where the variants were found in relation to the annotated genes and their potential impact on the expression and function of the affected gene products.

2.9. Statistical Analysis

In this study, all experiments were performed in at least three biological replicates (n ≥ 3). Statistical significances (p < 0.05) were determined by Student’s t-test (two-way, unpaired) on R software using the “stats” package (v.4.3.1) [39], except for the MPN analysis and whole genome re-sequencing and transcriptomic analyses.

3. Results

3.1. Selection of Propolis-Resistant Mutant Strains by Evolutionary Engineering

Prior to the evolutionary engineering procedure, the reference strain and the EMS-mutagenized initial population were grown in YMM containing 60–650 µg/mL propolis, to determine the initial propolis concentration to be used in the evolutionary selection experiments. The propolis concentration that reduced the growth of both the EMS-mutagenized initial population and the reference strain by 50% was determined as 150 µg/mL, and that propolis concentration was chosen as the initial propolis stress level for the evolutionary engineering experiments. The propolis concentration was gradually increased from 150 µg/mL to 710 µg/mL during 57 successive batch passages, and the 57th passage that could survive 710 µg/mL propolis stress was chosen as the last population (LP) of the selection, as the survival rate of the 57th population decreased to 0.3 at 710 µg/mL propolis stress. The last population was spread on solid YMM agar plates, and twelve individual mutant colonies were randomly picked and named as FD1-FD12. The propolis resistance of the mutant colonies was determined, first using a semi-quantitative spot assay, in the presence of 300 µg/mL propolis stress. The results revealed that all the mutant strains were highly resistant to 300 µg/mL propolis stress, which completely inhibited the growth of the reference strain (Figure 1). As FD7, FD8, FD10, FD11 and FD12 seemed to have a better survival than the other mutant strains at 500 µg/mL propolis stress ), those strains were chosen for the quantification of their propolis resistance by the MPN method.

The MPN method was then applied for the quantitative estimation of propolis resistance. For this purpose, 200, 500 and 710 µg/mL propolis concentrations were chosen for the stress resistance estimation of individual mutant strains, the reference strain (905) and the last population. According to the MPN results, all mutant strains and the last population exhibited higher survival rates compared to the reference strain. Among all the individual mutant strains tested, the FD11 strain showed the highest survival rate at 200 µg/mL and 710 µg/mL propolis concentrations (Figure 2), and it was chosen as the propolis-resistant, evolved strain for further analysis. The genetic stability of FD11 was also verified upon 10 repetitive batch cultivations in nonselective medium (YMM). No decrease in propolis resistance was observed throughout repeated cultivations in nonselective medium, indicating the genetic stability of FD11.

3.2. Cross-Resistance and Sensitivities of the Propolis-Resistant, Evolved Strain FD11 to Other Stress Factors

Cross-resistance tests were applied to the propolis-resistant, evolved strain FD11 to determine its potential resistance against other stress factors. Ther cross-resistance results obtained with the spot assay showed that FD11 was highly cross-resistant against 10 mM caffeine and 0.8 mM NiCl₂ stress, and slightly cross-resistant against 150 µg/mL geneticin stress, but more sensitive to 10% (v/v) ethanol stress than the reference strain. FD11 showed no significant cross-resistance or sensitivity against the other stressors tested (Figure 3). The observed cross-resistance of FD11 to caffeine and NiCl₂ stresses was confirmed by the MPN assay (Figure 4).

3.3. Growth Physiology and Metabolite Profiles of the Propolis-Resistant, Evolved Strain FD11

The growth physiology of FD11 and the reference strain was investigated both in the presence and absence of 200 µg/mL propolis stress. The growth curves of FD11 and the reference strain cultures are shown in Figure 5. It was observed that under nonstress conditions, the growth curves of both FD11 and the reference strain were almost identical, indicating that the evolved strain had no growth impairment. In addition, the applied propolis stress level (200 µg/mL) was significantly less inhibitory for FD11, compared to the reference strain (Figure 5): the reference strain had a significantly longer lag phase than FD11 under 200 µg/mL propolis stress conditions. Moreover, the maximum specific growth rate of FD11 (0.21 h⁻¹) was higher than that of the reference strain (0.17 h⁻¹) in the presence of propolis stress.

The glucose consumption data of the cultures were in line with their growth profiles, where the reference strain had a significantly slower glucose consumption compared to FD11 in the presence of 200 µg/mL propolis stress, indicating that the reference strain was strongly inhibited, unlike FD11 (Figure 6a). Under control conditions, the glycerol production profiles of the reference strain and FD11 were similar. However, in the presence of propolis stress, although FD11 and the reference strain had similar glycerol production profiles during the first 10 h of cultivation, FD11 apparently began to consume glycerol during the later hours of cultivation, whereas the reference strain continued to produce glycerol further (Figure 6b). The acetate production profiles of FD11 and the reference strain were also similar under control conditions, where acetate was produced during the early hours of cultivation and was consumed starting from about the 16th h of cultivation. Under propolis stress, FD11 produced higher levels of acetate than the reference strain during the early phases of growth, but the acetate levels did not change significantly after about the 16th h of cultivation. The reference strain, however, produced acetate throughout its cultivation and reached the highest acetate level at the end of its cultivation (30th h), among all cultures tested (Figure 6c). In the absence of propolis stress, FD11 produced more ethanol than the reference strain, and the ethanol levels seemed to decrease slightly after about the 16th h of cultivation. In the presence of propolis stress, both FD11 and the reference strain reached significantly higher final ethanol levels, compared to control conditions. The produced ethanol was not consumed by the cultures in the presence of propolis stress. Moreover, the reference strain had the highest ethanol level at the end of the cultivation (30th h) among all cultures tested (Figure 6d).

The storage carbohydrate (trehalose and glycogen) production of FD11 and the reference strain was also investigated, both in the absence and presence of 200 µg/mL propolis stress. The results revealed that, at the end of the cultivation (30th h), FD11 grown in the presence of propolis stress had the highest trehalose and glycogen accumulation (mg glucose equivalents/mg cell dry weight), compared to the other cultures tested. FD11 also had higher trehalose and glycogen content than the reference strain, under both control and propolis stress conditions. In addition, the presence of propolis stress increased the trehalose and glycogen content of both FD11 and the reference strain, although this increase was more pronounced in FD11 (Figure 7).

3.4. Intracellular ROS Levels

Intracellular ROS levels of FD11 and the reference strain were determined both in the presence and absence of propolis, using fluorescence intensity measurements. The presence of propolis decreased the ROS levels of both FD11 and the reference strain by 27 and 20%, respectively. However, the ROS levels of the propolis-resistant, evolved strain FD11 were only about 0.69-fold and 0.76-fold those of the reference strain, in the presence and absence of propolis stress, respectively (Figure 8).

3.5. Cell Wall Integrity of FD11

To test if cell wall remodeling is also implicated in propolis resistance, we treated the propolis-resistant, evolved strain FD11 and the reference strain with lyticase, a cell wall-degrading enzymatic cocktail [30]. The lyticase sensitivity assay results revealed that the presence of propolis increased the lyticase resistance or cell wall integrity of both FD11 and the reference strain. Moreover, the propolis-resistant, evolved strain FD11 had higher lyticase resistance than the reference strain, both in the presence and absence of propolis (Figure 9).

3.6. Comparative Whole Genome Transcriptomic Analysis of FD11

Transcriptomic changes in the propolis-resistant strain FD11 were determined using DNA microarray technology. The results revealed that 5092 genes were differentially expressed in FD11 compared to the reference strain: 2513 genes were upregulated and 2579 genes were downregulated. Among the genes with at least a two-fold expression change, 182 Open Reading Frames (ORFs) were upregulated and 239 ORFs were downregulated (corrected p < 0.05) in the propolis-resistant FD11 strain, compared to the reference strain.

The FunCat database [31] was used to categorize the functional classes of the upregulated and downregulated genes of FD11 and to assess their biological significance. The FunCat analysis results indicated that the genes with at least a two-fold upregulation were mainly enriched in the “Metabolism/Energy/Cellular Transport/Protein Fate (folding, modification)” category, including oxidoreductase activity, transmembrane transporter activity, unfolded protein binding, enzyme regulator activity and kinase activity (

Table 1. Main functional categories of at least two-fold upregulated genes in the propolis-resistant, evolved strain FD11 compared to the reference strain, according to FunCat analysis results.

	Functional Category	Count a	% b	Fold Enrichment c	p-Value
Metabolism	Oxidoreductase Activity	25	14.2	3.0	2.74 × 10−4
	Ion Binding	6	3.4	1.6	1.10 × 10−11
Cellular Transport	Transmembrane Transporter Activity	15	8.5	1.6	2.56 × 10−10
Protein Fate	Unfolded Protein Binding	9	5.1	4.7	7.10 × 10−11
Energy Metabolism	Kinase Activity	7	4.0	1.3	2.92 × 10−10
	Glycosyltransferase Activity	6	3.4	2.3	7.00 × 10−12
Transport and Catabolism	Enzyme Regulator Activity	7	4.0	1.2	3.00 × 10−12
Cell Cycle	Transferase Activity	6	3.4	1.2	7.90 × 10−11

^a Number of query genes found in each functional category. ^b Percentage of the involved genes among the total genes in the query. ^c Ratio of frequencies of the query and the reference gene set.

and

Table 2. Detailed functional categories with at least two-fold enriched upregulated genes in the propolis-resistant evolved strain FD11 compared to the reference strain, according to FunCat analysis results.

	Systematic Name	Gene Name	Fold Change	Description [40]
Oxidoreductase activity	Q0045	COX1	2.616	Subunit of complex IV of the mitochondrial respiratory chain
	Q0105	COB	2.008	Cytochrome B, mitochondrially encoded subunit of ubiquinol-Cytochrome C reductase
	YAL061W	BDH2	6.207	Putative oxidoreductase
	YBL064C	PRX1	2.037	Mitochondrial thioredoxin peroxidase
	YBR026C	ETR1	2.349	enoyl-[acyl-carrier-protein] reductase activity
	YBR046C	ZTA1	2.318	RNA-binding NADPH/quinone reductase
	YCL033C	MXR2	2.393	Mitochondrial methionine sulfoxide reductase
	YCL035C	GRX1	2.696	Bifunctional glutathione peroxidase and glutathione transferase
	YDR453C	TSA2	2.436	Stress-inducible cytoplasmic thioredoxin peroxidase
	YEL039C	CYC7	5.632	Electron carrier, facilitates electron transfer from ubiquinol to Cytochrome C
	YEL070W	DSF1	2.021	Mannitol dehydrogenase
	YGR088W	CTT1	3.229	Cytoplasmic catalase
	YGR209C	TRX2	3.071	Cytoplasmic thioredoxin isoenzyme
	YHR053C	CUP1-1	3.532	Copper- and cadmium-binding protein
	YHR055C	CUP1-2	3.498	Copper- and cadmium-binding protein
	YHR104W	GRE3	2.887	Aldose reductase
	YIL111W	COX5B	3.574	Subunit Vb of Cytochrome C oxidase
	YIL155C	GUT2	2.385	Glycerol-3-phosphate dehydrogenase
	YML054C	CYB2	2.955	L-lactate dehydrogenase (Cytochrome B2)
	YMR169C	ALD3	3.672	Cytoplasmic aldehyde dehydrogenase
	YMR256C	COX7	2.615	Subunit VII of Cytochrome C oxidase (Complex IV)
	YOR120W	GCY1	3.475	Glycerol dehydrogenase [NAD(P)+] and aldose reductase
	YOR374W	ALD4	4.244	Mitochondrial aldehyde dehydrogenase
	YPL061W	ALD6	2.887	Cytosolic aldehyde dehydrogenase
	YPL171C	OYE3	2.291	NADPH dehydrogenase
Transmembrane transporter activity	Q0045	COX1	2.616	Subunit of complex IV of the mitochondrial respiratory chain
	Q0105	COB	2.008	Cytochrome B, mitochondrially encoded subunit of ubiquinol-Cytochrome C reductase
	YDR011W	SNQ2	2.859	Plasma membrane ATP-binding cassette (ABC) transporter
	YDR342C	HXT7	5.222	Glucose transporter
	YDR343C	HXT6	5.218	Hexose transmembrane transporter
	YDR406W	PDR15	2.723	Plasma membrane ATP-binding cassette (ABC) transporter
	YGR243W	MPC3	4.698	Highly conserved subunit of the mitochondrial pyruvate carrier (MPC)
	YGR281W	YOR1	2.011	Plasma membrane ATP-binding cassette (ABC) transporter
	YGR289C	MAL11	3.795	High-affinity maltose transporter (alpha-glucoside transporter)
	YIL111W	COX5B	3.574	Subunit Vb of Cytochrome C oxidase
	YLL055W	YCT1	2.301	High-affinity cysteine-specific transporter
	YMR011W	HXT2	3.631	Hexose transmembrane transporter
	YMR256C	COX7	2.615	Subunit VII of Cytochrome C oxidase (Complex IV)
	YNR002C	ATO2	2.153	Plasma membrane ammonium transporter
	YDR011W	SNQ2	2.859	Plasma membrane ATP-binding cassette (ABC) transporter
	YOR153W	PDR5	3.497	Plasma membrane ATP-binding cassette (ABC) transporter
Unfolded protein binding	YAL005C	SSA1	2.267	ATPase involved in protein folding
	YBR072W	HSP26	5.664	Small heat shock protein with chaperone activity
	YDR171W	HSP42	3.145	Compartment-specific sequestrase chaperone
	YER103W	SSA4	3.895	Heat shock protein that is highly induced upon stress
	YLL026W	HSP104	2.796	Adenosine-binding protein chaperone
	YLR216C	CPR6	2.945	Peptidyl-prolyl cis-trans isomerase
	YNL077W	APJ1	2.718	Chaperone and ATPase activator
	YOR020C	HSP10	2.266	Mitochondrial matrix co-chaperonin
	YPL240C	HSP82	3.478	Unfolded protein-binding ATPase (chaperone)
Enzyme regulator activity	YFR017C	IGD1	3.552	Cytoplasmic enzyme inhibitor
	YLR178C	TFS1	2.398	Phospholipid-binding peptidase inhibitor
	YLR423C	ATG17	2.652	Subunit of the Atg1 signaling complex
	YNL015W	PBI2	2.900	Cytosolic inhibitor of vacuolar proteinase B (PRB1)
	YOR173W	DCS2	3.541	A protein involved in the deadenylation-dependent decapping of nuclear-transcribed mRNA and cellular response to starvation
	YOR178C	GAC1	3.209	Regulatory subunit of the Glc7p protein phosphatase type 1 complex
	YPL111W	CAR1	2.833	Manganese- and zinc-binding arginase
Kinase activity	YCL040W	GLK1	2.624	Glucokinase
	YCR091W	KIN82	2.149	Putative serine/threonine protein kinase
	YDL079C	MRK1	3.005	Glycogen synthase kinase 3 (GSK-3) homolog
	YDR516C	EMI2	4.018	Cytoplasmic protein implicated in sporulation and transcription regulation
	YFR053C	HXK1	6.549	Hexokinase isoenzyme 1
	YGR194C	XKS1	2.156	Cytoplasmic xylulokinase
	YMR291W	TDA1	2.022	Protein serine/threonine kinase
Ion binding	YGR205W	TDA10	2.346	ATP-binding protein of unknown function
	YHR053C	CUP1-1	3.532	Copper- and cadmium-binding protein
	YHR055C	CUP1-2	3.498	Copper- and cadmium-binding protein
	YLL026W	HSP104	2.796	Adenosine-binding protein chaperone
	YMR017W	SPO20	2.072	SNAP receptor subunit of the SNARE complex
	YPL111W	CAR1	2.833	Manganese- and zinc binding arginase
Transferase activity	YDL008W	APC11	2.050	Ubiquitin transferase
	YGL087C	MMS2	2.315	A subunit of the ubiquitin conjugating enzyme complex
	YGR043C	NQM1	2.709	Nuclear transaldolase
	YIL097W	FYV10	2.190	Subunit of GID complex
	YOR285W	RDL1	2.160	Thiosulfate sulfurtransferase
	YOR347C	PYK2	2.225	Pyruvate kinase

). According to the FunCat analysis results, the genes with at least a two-fold downregulation were mainly enriched in the “Protein Synthesis/Cell Cycle and DNA Processing/Transcription” category, including RNA binding, mRNA binding, methyltransferase activity, rRNA binding, transmembrane transporter activity, helicase activity, nucleotidyltransferase activity and DNA binding (

Table 3. Main functional categories of at least two-fold downregulated genes in the propolis-resistant, evolved strain FD11 compared to the reference strain, according to FunCat analysis results.

	Functional Category	Count a	% b	Fold Enrichment c	p-Value
Genetic Information Processing	RNA Binding	32	13.8	3.0	3.11 × 10−11
	mRNA Binding	30	12.9	4.6	3.21 × 10−11
	rRNA Binding	19	8.2	4.4	1.40 × 10−11
	DNA Binding	10	4.3	0.7	5.31 × 10−13
	Methyltransferase Activity	22	9.5	6.8	1.72 × 10−10
	Helicase Activity	15	6.5	4.9	4.32 × 10−14
Signaling and Cellular Processes	Transmembrane Transporter Activity	17	7.3	1.4	1.05 × 10−10
Transcription	Nucleotidyltransferase Activity	11	4.7	2.5	2.75 × 10−12

^a Number of query genes found in each functional category. ^b Percentage of the involved genes among the total genes in the query. ^c Ratio of frequencies of the query and the reference gene set.

and

Table 4. Detailed functional categories with at least two-fold enriched downregulated genes in the propolis-resistant, evolved strain.

	Systematic Name	Gene Name	Fold Change	Description [40]
RNA binding	YBR247C	ENP1	−3.027	Small nucleolar RNA (snoRNA)-binding protein
	YDL051W	LHP1	−2.180	RNA-binding protein
	YDL148C	NOP14	−2.259	Nucleolar protein
	YDR449C	UTP6	−2.155	Nucleolar U3-snoRNA-binding protein
	YEL026W	SNU13	−2.880	RNA-binding protein
	YER006W	NUG1	−2.651	GTPase that associates with nuclear 60S pre-ribosomes
	YGR128C	UTP8	−2.509	Nucleolar protein
	YGR159C	NSR1	−4.794	Nuclear localization sequence (NLS)-binding protein
	YHR040W	BCD1	−2.687	Essential protein required for the accumulation of box C/D sno RNA
	YHR148W	IMP3	−2.772	Component of the SSU processome
	YHR196W	UTP9	−2.299	Nucleolar protein
	YIL091C	UTP25	−2.473	Protein that binds both rRNA and U3 snoRNA
	YJL010C	NOP9	−2.400	Essential subunit of U3-containing 90S preribosome
	YJL033W	HCA4	−3.048	DEAD box RNA helicase
	YJL050W	MTR4	−2.710	ATP-dependent 3′-5’ RNA helicase
	YJL109C	UTP10	−2.492	Nucleolar protein
	YKR081C	RPF2	−3.273	Protein involved in maturation of LSU-ribosomal RNA (rRNA)
	YLR129W	DIP2	−2.244	Nucleolar snoRNA-binding protein
	YLR222C	UTP13	−2.452	Nucleolar protein
	YMR229C	RRP5	−2.668	RNA-binding protein
	YMR290C	HAS1	−3.365	ATP-dependent RNA helicase
	YNL075W	IMP4	−3.464	Component of the SSU processome
	YNL112W	DBP2	−5.448	ATP-dependent RNA helicase of the DEAD-box protein family
	YNL132W	KRE33	−2.814	rRNA cytidine N-acetyltransferase
	YNL175C	NOP13	−2.421	Putative RNA-binding protein
	YNR054C	ESF2	−2.860	Essential nucleolar protein
	YOL041C	NOP12	−2.453	Putative RNA-binding protein
	YOR359W	VTS1	−2.280	Flap-structured DNA-binding and RNA-binding protein
	YPL126W	NAN1	−2.033	U3 snoRNA-binding protein
	YPL217C	BMS1	−2.479	GTPase- and U3 snoRNA-binding protein
	YPR137W	RRP9	−2.698	Subunit of small ribosomal subunit processome
mRNA binding	YBR079C	RPG1	−3.514	eIF3a subunit of the eukaryotic translation initiation factor 3
	YCR057C	PWP2	−2.707	Nucleolar mRNA-binding protein
	YDR496C	PUF6	−2.999	Pumilio-homology domain protein
	YER006W	NUG1	−2.651	GTPase that associates with nuclear 60S pre-ribosomes
	YFL023W	BUD27	−2.047	Cytoplasmic protein
	YGL099W	LSG1	−2.255	Putative GTPase involved in 60S ribosomal subunit biogenesis
	YGR103W	NOP7	−2.748	Component of several different pre-ribosomal particles
	YGR159C	NSR1	−4.794	Nuclear localization sequence-binding protein
	YHR216W	IMD2	−2.186	Inosine monophosphate dehydrogenase
	YJL010C	NOP9	−2.400	Essential subunit of U3-containing 90S preribosome
	YJL050W	MTR4	−2.710	ATP-dependent 3′-5′ RNA helicase
	YKL172W	EBP2	−2.768	Protein required for 25S rRNA maturation and 60S ribosomal subunit assembly
	YLL011W	SOF1	−2.500	Protein required for biogenesis of 40S (small) ribosomal subunit
	YLR175W	CBF5	−2.605	Pseudouridine synthase catalytic subunit of box H/ACA snoRNPs
	YLR197W	NOP56	−2.500	Essential evolutionarily conserved nucleolar protein
	YLR276C	DBP9	−3.084	ATP-dependent DNA, RNA and DNA/RNA helicase
	YLR401C	DUS3	−2.610	tRNA dihydrouridine synthase
	YLR432W	IMD3	−2.006	Inosine monophosphate dehydrogenase
	YML056C	IMD4	−3.336	Inosine monophosphate dehydrogenase
	YMR229C	RRP5	−2.668	RNA-binding protein
	YNL002C	RLP7	−3.010	Nucleolar protein similar to large ribosomal subunit L7 proteins
	YNL112W	DBP2	−5.448	ATP-dependent RNA helicase
	YOR091W	TMA46	−2.374	Protein of unknown function that associates with translating ribosomes
	YOR310C	NOP58	−2.490	Protein involved in producing mature rRNAs and snoRNAs
	YPL012W	RRP12	−3.048	Protein required for export of the ribosomal subunits
	YPL043W	NOP4	−2.670	RNA-binding protein
	YPL126W	NAN1	−2.033	U3 snoRNA-binding protein
	YPL217C	BMS1	−2.479	GTPase- and U3 snoRNA-binding protein
	YPL226W	NEW1	−2.281	Translation termination and ribosome biogenesis factor
	YPR112C	MRD1	−3.112	Essential conserved small ribosomal subunit (40s) synthesis factor
Methyltransferase activity	YBR034C	HMT1	−3.823	Nuclear protein-arginine omega-N methyltransferase
	YBR061C	TRM7	−2.125	tRNA methyltransferase
	YBR141C	BMT2	−2.671	Nucleolar S-adenosylmethionine-dependent rRNA methyltransferase
	YBR271W	EFM2	−2.714	S-adenosylmethionine-dependent lysine methyltransferase
	YCL054W	SPB1	−2.447	rRNA methyltransferase
	YCR047C	BUD23	−2.648	rRNA (guanine) methyltransferase
	YDL014W	NOP1	−3.168	A histone–glutamine methyltransferase
	YDR083W	RRP8	−3.097	rRNA methyltransferase
	YDR120C	TRM1	−2.659	tRNA methyltransferase
	YDR165W	TRM82	−2.028	Noncatalytic subunit of a tRNA methyltransferase complex
	YDR465C	RMT2	−3.107	Arginine N5 methyltransferase
	YHR070W	TRM5	−2.236	tRNA methyltransferase
	YIL064W	EFM4	−2.400	S-adenosylmethionine-dependent lysine methyltransferase
	YIL096C	BMT5	−3.240	Nucleolar S-adenosylmethionine-dependent rRNA (uridine-N3-)-methyltransferase
	YLR186W	EMG1	−2.218	Ribosomal RNA (rRNA) (pseudouridine) methyltransferase
	YML014W	TRM9	−2.083	tRNA (uracil) methyltransferase
	YNL024C	EFM6	−2.044	Putative S-adenosylmethionine-dependent methyltransferase
	YNL061W	NOP2	−2.765	Ribosomal RNA (rRNA) (cytosine-C5-)-methyltransferase
	YNL062C	GCD10	−3.403	Subunit of tRNA (1-methyladenosine) methyltransferase
	YOL124C	TRM11	−2.267	tRNA (guanine-N2-)-methyltransferase subunit of cytoplasmic tRNA (m2G10) methyltransferase complex
	YOL125W	TRM13	−2.726	2′-O-methyltransferase
	YPL030W	TRM44	−2.648	tRNA(Ser) Um(44) 2′-O-methyltransferase
rRNA binding	YGR103W	NOP7	−2.748	Component of several different pre-ribosomal particles
	YHR052W	CIC1	−3.264	Protein that binds to the rRNA of the large ribosomal subunit and proteasome
	YHR170W	NMD3	−3.065	Protein involved in nuclear export of the large ribosomal subunit
	YIL091C	UTP25	−2.473	Protein that binds both rRNA and U3 snoRNA
	YKL009W	MRT4	−2.350	Protein involved in mRNA turnover and ribosome
	YKR081C	RPF2	−3.273	Protein involved in maturation of LSU-ribosomal RNA (rRNA)
	YMR049C	ERB1	−2.861	Constituent of 66S pre-ribosomal particles
	YMR229C	RRP5	−2.668	RNA-binding protein involved in 18S and 5.8S rRNA synthesis
	YNL002C	RLP7	−3.010	Nucleolar protein similar to large ribosomal subunit L7 proteins
	YNL075W	IMP4	−3.464	Component of the SSU processome
	YNR053C	NOG2	−3.452	Putative GTPase
	YOL041C	NOP12	−2.453	Nucleolar protein involved in pre-25S rRNA processing
	YOL077C	BRX1	−3.224	Nucleolar protein
	YOR004W	UTP23	−3.014	Component of the small subunit processome
	YOR056C	NOB1	−2.231	Small ribosomal subunit rRNA-binding endonuclease
	YOR145C	PNO1	−3.423	Nucleolar unfolded protein-binding subunit of the 90S preribosome
	YPL043W	NOP4	−2.670	Nucleolar protein
	YPL146C	NOP53	−2.236	Nucleolar protein
	YPR112C	MRD1	−3.112	Essential conserved small ribosomal subunit (40s) synthesis factor
Transmembrane transporter activity	YBR021W	FUR4	−2.311	Plasma membrane-localized uracil permease
	YBR291C	CTP1	−2.103	Mitochondrial tricarboxylic acid transporter
	YER056C	FCY2	−3.495	Purine–cytosine permease
	YER145C	FTR1	−2.395	High-affinity iron transporter of the plasma membrane
	YGL255W	ZRT1	−4.732	High-affinity zinc uptake transmembrane transporter of the plasma membrane
	YGR055W	MUP1	−2.726	High-affinity methionine permease
	YGR065C	VHT1	−2.547	High-affinity plasma membrane H+-biotin (vitamin H) symporter
	YJL198W	PHO90	−2.001	Low-affinity phosphate transporter
	YML116W	ATR1	−2.431	Borate efflux transmembrane transporter
	YML123C	PHO84	−4.766	Inorganic phosphate transmembrane transporter
	YMR241W	YHM2	−2.469	DNA-binding tricarboxylate secondary active transmembrane transporter
	YMR319C	FET4	−2.122	Low-affinity Fe(II) transporter of the plasma membrane
	YNL065W	AQR1	−3.280	Drug and monocarboxylic acid transmembrane transporter
	YNL142W	MEP2	−2.054	Ammonium transmembrane transporter
	YNR017W	TIM23	−2.025	Mitochondrion targeting sequence-binding protein transmembrane transporter
	YPL274W	SAM3	−3.202	High-affinity S-adenosylmethionine permease

).

It was found that 10% of the genes in the “Oxidoreductase Activity” functional category were upregulated in FD11. Many of these genes were related to mitochondrial function, including COX1 and COB, which encode subunits of the mitochondrial respiratory chain complex; CYC7, encoding an electron carrier that facilitates electron transfer from ubiquinol to Cytochrome C; and COX5B and COX7, which encode subunits of Cytochrome C oxidase; as well as PRX1 and MXR2, coding for mitochondrial enzymes. Within the “Transmembrane Transporter Activity” category, 5% of the genes were upregulated in FD11, including PDR5, PDR15, SNQ2 and YOR1, which encode plasma membrane ATP-binding cassette (ABC) transporters. In addition, 15% of the genes in the “Unfolded Protein Binding” category were upregulated, including the chaperone-encoding genes, such as HSP26, HSP42, SSA4, HSP104, HSP10 and HSP82 (Table 2).

Within the “RNA Binding” functional category, 11% of the genes were downregulated in FD11. Many of these genes encode RNA-binding proteins, including LHP1, SNU13 and RRP5. Regarding the “mRNA Binding” category, 17% of the genes were downregulated in FD11, including PWP2, BUD27 and NOP7. Moreover, 5% of the genes in the “Transmembrane Transporter Activity” category were downregulated, including transmembrane transporters such as PHO90, ATR1, PHO84, FTR1 and FET4, which encode diverse transmembrane transporters (Table 4).

3.7. Comparative Whole Genome Analysis of FD11

A comparative whole genome analysis was performed with the propolis-resistant, evolved strain FD11 and the reference strain. The whole genome re-sequencing of the propolis-resistant, evolved strain FD11 generated 10.2 million reads and a 168× mean depth coverage. A total of 350 single-nucleotide polymorphisms (SNPs) were found in FD11 compared to the reference strain, after alignment. The majority of the SNPs were transition substitutions (236), and the remaining were transversion substitutions (114), the typical mutation type observed in EMS mutagenesis [22]. The evolved strain had 185 nonsynonymous and 165 synonymous mutations. The most relevant missense mutations that seemed to be related to propolis resistance were selected based on the comparative transcriptomic analysis results of FD11. Mutations in genes related to the main functional categories of differentially expressed genes in the evolved strain, such as oxidoreductase activity, transmembrane transport, and pleiotropic drug resistance were selected as the potential mutations most likely related to propolis resistance, and they are listed in

Table 5. Selected missense mutations in FD11—compared to the reference strain—that are possibly related to propolis resistance.

Gene Name	Genetic Change	Amino Acid Substitution	Description [40]
PHO11	c.270 A>G	T90A	One of three repressible acid phosphatases; glycoprotein that is transported to the cell surface by the secretory pathway
PHO11	c.288 A>G	S96G	One of three repressible acid phosphatases; glycoprotein that is transported to the cell surface by the secretory pathway
UTP20	c.6385 G>A	M2129I	Component of the small-subunit (SSU) processome; the SSU processome is involved in the biogenesis of the 18S rRNA
COX9	c.77 C>A	G26V	Subunit VIIa of Cytochrome C oxidase (Complex IV); Complex IV is the terminal member of the mitochondrial inner membrane electron transport chain
ENA5	c.2950 C>T	R984K	Protein with similarity to P-type ATPase sodium pumps; member of the Na+ efflux ATPase family
CPR5	c.20 A>G	S7P	Peptidyl-prolyl cis-trans isomerase (cyclophilin) of the ER; catalyzes the cis–trans isomerization of peptide bonds
TRS120	c.397 G>A	T133I	Component of transport protein particle (TRAPP) complex II; TRAPPII is a multimeric guanine nucleotide-exchange factor for the GTPase Ypt1p, regulating intra-Golgi and endosome–Golgi traffic
HXT13	c.800 G>A	A267V	Putative transmembrane polyol transporter; supports growth on and uptake of mannitol and sorbitol
FCY22	c.1376 A>G	N459S	Putative purine–cytosine permease; very similar to Fcy2p but cannot substitute for its function
PDR1	c.3030 A>C	N1010K	Transcription factor that regulates the pleiotropic drug response
SNF6	c.941 G>A	E314K	Subunit of the SWI/SNF chromatin remodeling complex; involved in transcriptional regulation
HSP150	c.597 G>A	V199I	O-mannosylated heat shock protein
SPT8	c.205 C>A	E69D	Subunit of the SAGA transcriptional regulatory complex; not present in SAGA-like complex SLIK/SALSA
SPT8	c.202 C>A	Q68H	Subunit of the SAGA transcriptional regulatory complex; not present in SAGA-like complex SLIK/SALSA
NOP56	c.888 A>T	M296L	Essential evolutionarily conserved nucleolar protein; component of the box C/D snoRNP complexes that direct 2′-O-methylation of pre-rRNA during its maturation
TMA23	c.434 T>A	L145M	Nucleolar protein implicated in ribosome biogenesis; deletion extends chronological lifespan
RRP6	c.86 C>G	D29E	Nuclear exosome exonuclease component; has 3′-5′ exonuclease activity that is regulated by Lrp1p; involved in RNA processing, maturation, surveillance, degradation, tethering and export
RRP6	c.1904 C>T	T635I	Nuclear exosome exonuclease component; has 3′-5′ exonuclease activity that is regulated by Lrp1p; involved in RNA processing, maturation, surveillance, degradation, tethering and export
MPC54	c.1024 T>G	K342Q	Component of the meiotic outer plaque; a membrane-organizing center that is assembled on the cytoplasmic face of the spindle pole body during meiosis II and triggers the formation of the prospore membrane; potential Cdc28p substrate
SNU66	c.626 T>A	I209F	Component of the U4/U6.U5 snRNP complex; involved in pre-mRNA splicing via the spliceosome
PDR10	c.4679 A>C	K1560Q	ATP-binding cassette (ABC) transporter; multidrug transporter involved in the pleiotropic drug resistance network; regulated by Pdr1p and Pdr3p

. The full list of mutations that were found in FD11 are listed in Supplementary Table S1.

4. Discussion

In this study, a highly propolis-resistant and genetically stable S. cerevisiae strain (FD11) was obtained by evolutionary engineering, using systematic batch selection applied with gradually increased propolis levels. The evolved strain FD11 could resist up to 710 µg/mL of propolis, where the reference strain was strongly inhibited at propolis levels exceeding 150 µg/mL. Comparative transcriptomic analyses results of FD11 and the reference strain revealed that the upregulated genes in FD11 were mainly enriched in transmembrane transporter activity, oxidoreductase activity and unfolded protein binding.

Within the functional category of transmembrane transporter activity, many of the upregulated genes in FD11 were encoding plasma membrane ATP-binding cassette (ABC) transporters, such as PDR5, PDR15, SNQ2 and YOR1. In addition, two SNPs were detected in the PDR1 and PDR10 genes of FD11. An amino acid substitution (N1010K) was observed in the PDR1 gene, changing asparagine to lysine at position 1010. The second SNP identified in FD11 was located in the PDR10 gene, substituting lysine with glutamine at position 1560 (K1560Q) (Table 5). Many ABC transporters that are involved in drug efflux and resistance are encoded by pleiotropic drug resistance (PDR) genes in S. cerevisiae. PDR proteins were first discovered in bacteria as high-affinity importers with an ability to confer multidrug (MDR) resistance in cancer cells [41]. PDR5 encodes an ABC transporter involved in the resistance to multiple drugs, by enabling drug removal from the cell. The ABC transporter Pdr5 from S. cerevisiae has become a well-known and widely studied model for PDR proteins, since its discovery more than 30 years ago. Pdr5 has been reported to transport a wide variety of chemicals, including azoles, ionophores, antibiotics and other xenobiotics [42]. Pdr15p is known as an ATPase-coupled transmembrane transporter of the cell periphery and is involved in the response to xenobiotics [43]. SNQ2 encodes a plasma membrane ABC transporter and has a role in multidrug resistance and resistance to singlet oxygen species. According to previous reports, SNQ2 is upregulated when S. cerevisiae is exposed to caffeine [30], propolis [15] and coniferyl aldehyde [44]. Our propolis-resistant strain FD11 showed cross-resistance to caffeine stress. Moreover, a caffeine-resistant, evolved S. cerevisiae strain was also highly resistant to propolis and coniferyl aldehyde stresses [45]. Similarly, a coniferyl aldehyde-resistant, evolved S. cerevisiae strain was also cross-resistant to propolis and caffeine stresses [22]. Thus, resistance to propolis, caffeine and coniferyl aldehyde stress may have a common molecular basis that may include SNQ2.

PDR1 encodes a transcription factor that regulates the expression of PDR genes. Increased levels of pleiotropic drug genes allow the efflux of drugs from the cell and survival in the presence of drugs. Pdr1p and Pdr3p positively control the expression of target genes that are involved in multidrug resistance, such as PDR5, SNQ2 and YOR1 [46]. Thus, the observed SNP in the PDR1 gene of FD11 might have upregulated the PDR5, SNQ2 and YOR1 genes and significantly contributed to the propolis resistance of FD11. Interestingly, amino acid substitutions (C862Y) and (V819D) were also observed in the PDR1 gene of coniferyl aldehyde- and caffeine-resistant, evolved S. cerevisiae strains, respectively [22,45], implying that pleiotropic drug resistance genes regulated by PDR1 could play a key role in the response and resistance to these antioxidative molecules. The PDR10 gene also encodes an ABC transporter participating in double-strand break repair via sister chromatid exchange and localizing in the plasma membrane of S. cerevisiae. PDR10 also has a role in lipid metabolism, with the exportation of lipid precursors from the cell for lipid homeostasis [47,48]. The SNP in the PDR10 gene may also contribute to the observed propolis resistance in FD11, along with the other PDR genes.

Within the functional category of oxidoreductase activity, many of the upregulated genes in FD11 were related to mitochondrial function and Cytochrome C activity, such as COX1, COB, CYC7, COX5B, COX7, PRX1 and MXR2. Cytochrome C is a mitochondrial protein that is involved in the respiratory chain and is also known to function as an activator of caspase-9 in the mammalian apoptosis pathway [49]. COX5B encodes subunit Vb of Cytochrome C oxidase, which is the terminal member of the mitochondrial inner membrane electron transport chain. It provides Cytochrome C oxidase activity and electron transport to oxygen [50,51]. COX7 encodes subunit VII of Cytochrome C oxidase (Complex IV, which is the terminal member of the mitochondrial inner membrane electron transport chain). COX9 codes for a subunit of Complex IV of the mitochondrial respiratory chain and transfers electrons from Cytochrome C to oxygen in the terminal reaction of the electron transport chain [52]. Interestingly, an SNP was found in the COX9 gene of FD11, which resulted in an amino acid substitution (G26V), changing glycine to valine (Table 5). The main function of Cytochrome C oxidase is the transfer of electrons from Cytochrome C to molecular oxygen during cellular respiration [53]. Cytochrome C is a peripheral protein of the mitochondrial inner membrane, which has a function as an electron carrier between Complex III and Complex IV in the mitochondrial electron transport chain. The releasing of Cytochrome C to cytosol initiates apoptosis, with the activation of the caspases [54]. Thus, the inhibition of Cytochrome C oxidase and Cytochrome C result in the release of Cytochrome C to cytosol and induce apoptosis. De Castro et al. (2011) also showed that Cytochrome C is involved in propolis-induced cell death in S. cerevisiae [14]. Moreover, the deletion of genes involved in the mitochondrial electron transport chain was shown to increase the sensitivity of S. cerevisiae to propolis, based on yeast deletion library screening [14]. It is important to note that significantly lower ROS levels were observed in the evolved strain FD11 compared to the reference strain, both in the presence and absence of propolis stress. The upregulation of many genes related to mitochondrial function, such as COX1, COB, PRX1, MXR2, CYC7, COX5B, COX7, COX1, COB and MPC3, and genes encoding catalase (CTT1), glutathione-dependent disulfide oxidoreductase (GRX1), and stress-inducible cytoplasmic thioredoxin peroxidase (TSA2), along with the observed SNP in the COX9 gene, may play a role in the propolis resistance and decreased ROS levels of FD11.

According to the transcriptomic analysis results, within the functional category of unfolded protein binding, many upregulated genes in FD11 were chaperone-encoding genes, such as HSP26, HSP42, SSA4, HSP104, HSP10 and HSP82. In addition, an SNP was found in the HSP150 gene of FD11 at the position c.597 G>A, changing valine to isoleucine (Table 5). Heat shock proteins (HSPs) are evolutionarily conserved proteins and have a wide range of cellular functions such as protein degradation, protein folding and stress response. Stress response is initiated at the early levels of cellular stress by the HSP protein family. Moreover, HSP proteins have an important role in the regulation of apoptosis mechanisms and the protection of cells from undergoing apoptosis [55]. The overexpression of HSP genes increases resistance to stress-induced cell damage and apoptosis. HSPs inhibit apoptotic mechanisms and complexes like caspases [56]. The upregulation of several HSP genes and the SNP in the HSP105 gene of the evolved strain FD11 may also be associated with its high propolis resistance.

In a previous study on the transcriptomic response of a wild-type S. cerevisiae strain to propolis stress, it was shown that propolis most prominently affects pathways related to oxidative stress, the mitochondrial electron transport chain, vacuolar acidification, the regulation of the macroautophagy associated with protein targeting to vacuoles, the cellular response to starvation, and the negative regulation of transcription from RNA polymerase II promoter [15]. De Castro et al. (2011) also showed that vacuolar acidification and the translocation of Atg8p to the vacuoles were induced by propolis, as one of the characteristics of autophagy [14]. The vacuole is crucial to maintain cellular homeostasis, including the regulation of intracellular pH and the degradation of proteins and organelles by autophagy. Interestingly, ATG8 and ATG17 genes were upregulated in the evolved strain FD11. ATG8 encodes a ubiquitin-like protein conjugated to phosphatidylethanolamine (PE), which has a function in membrane fusion and autophagosome formation. It binds to the Atg1p-Atg13p complex and triggers its vacuolar degradation [57]. ATG17 codes for a subunit of the Atg1 signaling complex, kinase activator and scaffold protein that is involved in autophagic vacuole assembly [58]. Moreover, a synonymous mutation was also found in the ATG1 gene of FD11 (Supplementary Table S1). The potential role of synonymous mutations in adaptive laboratory evolution should also be considered [59].

When wild-type S. cerevisiae was exposed to propolis, genes related to the cell cycle, chromosome distribution and chromatin silencing were downregulated. This reduction was explained with the activation of transcriptional checkpoint controls involved in the S- and M-phase by propolis, which is crucial for DNA replication and proper chromosome segregation [15]. Various genes in the RNA- and mRNA-binding category were also downregulated in the propolis-resistant, evolved strain FD11.

Our transcriptomic results are generally in line with the previously reported results [15], indicating that there are similarities between the transcriptomic response of the wild-type yeast cells to propolis stress and the response of the propolis-resistant S. cerevisiae cells in the absence of propolis stress, implying that the evolved strain shows a (propolis) stress response even in the absence of the stressor (propolis), as observed previously for other stress-resistant, evolved yeast strains [22,23].

The cell wall-perturbing enzyme lyticase is generally used to evaluate the cell wall integrity of the yeast cells against environmental stress [30]. Increased cell wall integrity is a frequently observed common change in evolutionary engineered, stress-resistant strains [23,39]. Our previous research to evolve yeast strains resistant to diverse stressors such as coniferyl aldehyde [22], 2-phenylethanol [23] and caffeine [45] indicated that resistance to these diverse stresses is associated with cell wall remodeling. Similarly, the propolis-resistant, evolved strain FD11 also had increased cell wall integrity compared to the reference strain, both in the presence and absence of propolis stress. Propolis also increased the lyticase resistance of the reference strain. This could be due to the sticky and waxy nature of the propolis, which may protect the yeast cell wall against the lytic effect of the enzyme. In line with this increased cell wall integrity, transcriptomic and genomic changes were also observed in FD11 regarding cell wall-related genes: DAN4, which encodes a cell wall mannoprotein, had multiple nonsynonymous and synonymous mutations in FD11. SED1, encoding a major stress-induced structural GPI–cell wall glycoprotein, and SPI1, encoding a cell wall protein involved in the response to acidic pH, were upregulated, whereas TIR2, encoding a cell wall mannoprotein, was downregulated in FD11. Thus, changes in the cell wall structure may also play an important role in propolis resistance. Detailed functional analyses of the identified gene mutations are necessary, using reverse engineering and CRISPR/Cas9 genome editing methods to clarify how these genes and their related pathways specifically contribute to propolis resistance mechanisms in S. cerevisiae.

5. Conclusions

In this study, a highly propolis-resistant and genetically stable S. cerevisiae strain (FD11) was obtained for the first time by evolutionary engineering. The evolved strain had decreased ROS levels and increased cell wall integrity. Genomic and transcriptomic analyses of the evolved strain revealed the importance of mitochondrial activity, pleiotropic drug resistance (PDR) genes and cell wall integrity in propolis resistance. Future studies such as genome editing and reverse engineering will help clarify the exact roles of the observed gene mutations in the propolis resistance of the evolved strain. With their increased ethanol production, these propolis-resistant and robust S. cerevisiae strains may have a potential for industrial applications such as alcoholic fermentation, where propolis may be used as a control agent against the growth of contaminating yeasts. However, the ethanol tolerance of propolis-resistant strains should also be improved by further evolutionary engineering strategies. The potential risk of propolis resistance development in contaminating microorganisms upon continuous exposure to propolis should also be evaluated for potential industrial applications.