Metabolic Biomarkers for Lifespan Extension and Cellular Stress in Saccharomyces cerevisiae during Calorie Restriction and Quercetin Treatment

Keywords: calorie restriction, longevity, metabolomics, quercetin, yeasts

Strain, growth medium, and growth conditions

S. cerevisiae strain D452-2 (MATa leu2 his3 ura3 can1) was used in this study. The strain was cultured in yeast peptone dextrose (YPD) media [1% yeast extract, 2% peptone (BD), and 2.0% glucose] in a total volume of 50 mL. The growth curve assay was performed in synthetic complete (SC) media containing 0.67% yeast nitrogen base without amino acids (BD), 0.079% complete supplement mixture (MP Biomedicals), and 2.0% glucose. The pH was adjusted to 7.00. For the inoculation, yeast cells were seeded in an incubator for 24 h at 300 rpm and 30°C and then precultured with fresh YPD media for a further 12 h. Growth stage analysis was conducted at 9, 12, 24, 72, and 180 h, and CR was implemented using YPD media containing 0.5% and 0.2% glucose. The yeast was pretreated with various concentrations of quercetin [0.05, 0.1, and 0.2 mg/50 mL dimethyl sulfoxide (DMSO)], for which the DMSO concentration was 250 μL/50 mL of culture in the final inoculation. Finally, the pre-cultured yeast cells were inoculated into 50 mL of YPD media at an initial optical density (OD) at 600 nm (OD₆₀₀) of 0.05 and incubated for 12 h at 300 rpm and 30°C. For all metabolomic analysis experiments, yeast cells were cultured in 10 individual flasks to obtain 10 biological replicates.

Growth curve assay

The yeast cells were seeded in 5 mL of YPD medium (2% glucose) and incubated at 300 rpm and 30°C for 24 h. The cells were then pre-cultured under the same conditions for a further 12 h. Finally, the cells were inoculated into 25 mL of YPD media containing 0.2%, 0.5%, or 2.0% glucose at an initial OD₆₀₀ of 0.05 and then incubated at 90 rpm and 30°C for 72 h (late stationary phase). Before transfer, the yeast cells were washed in fresh SC media. The yeast cells were transferred into fresh 2.0% glucose SC media for the growth assay. Growth was measured in triplicate at 90-min intervals and expressed as the OD₆₀₀.

CLS assay

CLS assays were performed via spot assays according to a protocol described previously (Smith et al., 2007) with some modifications. In brief, yeast cells were seeded in YPD media (1.0% yeast extract, 2.0% peptone, and 2.0% glucose) and incubated at 300 rpm and 30°C for 24 h. The cells were then precultured for 12 h in fresh YPD media. After washing at the aging or late-stationary phase, the yeast cells were transferred to fresh SC media under CR (0.2%, 0.5%, or 2.0% glucose concentration) and incubated for a further 72 h. These cultured yeast cells were labeled "day 0." For the spot assays, aliquots of culture were tenfold serial diluted in sterile water and spotted onto YPD agar plates. Plates were then incubated for 2 days, and the viability of the culture was determined.

Sample preparation for metabolite analysis

Densities for each cell, collected from each experimental condition, were adjusted to 20 values at an OD₆₀₀. Yeast pellets were washed five times with potassium phosphate buffer (K₂HPO₄/KH₂PO₄, pH 7.00). After quenching in liquid nitrogen, the resulting pellets were stored at −80°C until metabolite extraction.

¹H NMR spectroscopic analysis of the yeast extract

The yeast pellets were suspended in a 700 μL cold mixture of methanol-d₄ (CD₃OD) and 300 μL of deuterium water (D₂O) containing 0.05 wt% 3-(trimethylsilyl)-[2,2,3,3-²H₄]-propionic acid sodium salt (TSP) and stored at −80°C in a 1.5 mL Eppendorf tube. Before the assays, the suspension was transferred into 2 mL reinforced tubes with screw caps and O-rings (Omni International) with approximately 400 mg of acid-washed glass beads (0.5 mm, Omni International). The mixture was disrupted using an Omni Bead Ruptor 24 (Omni International). Bead beating was conducted for two cycles of 30 seconds at 6.0 m/s, with a pause of 10 seconds between cycles, and the mixture was then centrifuged at 18,000 g and 4°C for 15 min. Subsequently, 550 μL of the yeast extract supernatant was transferred into 5 mm NMR tubes and analyzed using a Bruker Avance 700 spectrometer (Bruker BioSpin) operating at a 700.40 MHz ¹H frequency and a temperature of 298 K. CD₃OD and trehalose were employed as the field-frequency lock and chemical shift reference (¹H, δ 5.17), respectively. One-dimensional (1D) nuclear Overhauser effect spectrometry (NOESY) pulse sequence with effective water suppression was then applied for the acquisition of the ¹H NMR spectrum of the yeast extract. Signal assignment for representative samples was facilitated via the use of two-dimensional (2D) total correlation spectroscopy (TOCSY) and heteronuclear single quantum correlation (HSQC).

NMR data processing and multivariate statistical analysis

The phase and baseline of the ¹H NMR spectrum were manually corrected in TOPSPIN software (version 3.2, Bruker BioSpin) and then converted to ASCII format. The ASCII format data were imported into MATLAB (R2010b, The Mathworks Inc.). All spectra were aligned using the interval-correlation-optimized shifting (icoshift) method (Savorani et al., 2010) and normalized using the probabilistic quotient normalization method (Dieterle et al., 2006). Regions corresponding to TSP (δ −0.5 to 0.5) and methanol (δ 3.30 to 3.37) were excluded prior to the normalizing step. For the multivariate statistical analysis, the resulting datasets were imported into SIMCA-P version 14 (Umetrics) and applied to a mean centering scaling method. Principal component analysis (PCA) was performed as an unsupervised pattern recognition method to obtain an overview of metabolite perturbation for each experimental condition (Palomino-Schätzlein et al., 2013). The orthogonal projections to latent structures-discriminant analysis (OPLS-DA) method, a supervised pattern recognition method (Seo et al., 2016), was performed in MATLAB to identify and highlight the metabolic differences between pairwise groups, the scripts for which were developed at Imperial College London (Savorani et al., 2010). The OPLS-DA models were evaluated for quality through their R²X and Q² scores (Tambellini, 2014). The R²X score represents the proportion of variance in the data, indicating the goodness of fit of the data, while the Q² score represents the proportion of variance in the predictable data, indicating the predictability of the data generated by the model (Seo et al., 2016).

Statistical analysis

Statistical analysis was performed using IBM SPSS statistical software (version 21, IBM Corp.). Analysis of variance (ANOVA) and Duncan’s multiple range test were employed to determine the statistical significance of the differences in metabolite levels. The integral areas of metabolites identified from the ¹H NMR spectra corresponding to each metabolite were used for relative, quantitative comparisons. Differences with P-values of <0.05 were considered statistically significant.

¹H NMR spectroscopy for the identification of intracellular metabolites

To identify the intracellular metabolites in S. cerevisiae grown under various conditions, the representative ¹H NMR spectra from yeast cell extracts at different growth stages (9, 12, 24, 72, and 180 h) and under CR (0.2%, 0.5%, and 2% glucose) were given (Supplementary Fig. 1 and 2, respectively). In addition, the ¹H NMR spectra of each yeast cell extract following quercetin treatment (0.05, 0.1, 0.2 mg of quercetin) and DMSO only treatment were also provided in Fig. 1. The ¹H NMR spectra revealed the presence of amino acids (alanine, arginine, asparagine, aspartate, glutamate, glutamine, glycine, histidine, isoleucine, leucine, lysine, phenylalanine, proline, serine, threonine, tryptophan, valine, tyrosine), nucleotides/nucleotide derivatives [adenosine triphosphate (ATP), guanosine triphosphate (GTP), NAD⁺], uracil, orotate, carbohydrates/sugar derivatives (trehalose, lactate, ethanol), carboxylic acids/tricarboxylic acid (TCA) cycle intermediates (acetate, fumarate, succinate), choline compounds/membrane metabolites [choline, glycerophosphocholine (GPC)], and other specialized compounds (quercetin, thiamine) in the yeast cell extracts. Identification of these compounds was confirmed through 2D TOCSY and HSQC NMR (data not shown). To investigate the statistical changes in the levels of these intracellular metabolites during growth, CR, and quercetin treatment, multivariate statistical analysis was applied to the whole ¹H NMR spectra datasets obtained from the yeast cell extracts.

Multivariate statistical analysis of yeast intracellular metabolites and their growth condition dependencies

Cell growth was found to be slower under CR (Fig. 2A) and quercetin treatment (Fig. 2B), compared to the normal conditions or in the control with 2.0% glucose. Interestingly, DMSO treatment also resulted in a slower growth rate (Fig. 2B). The yeast spot assay revealed the prolonged survival of yeast cells during CR (Fig. 2C). However, no significant increases in the survival rate were observed for the yeast cells treated with quercetin (data not shown).

To elucidate the global metabolite patterns of the yeast cells across different growth stages, CR condition, and quercetin treatment, PCA and OPLS-DA models were generated with the ¹H NMR spectra data of the relevant yeast cells. These models revealed clear metabolic differentiation of the yeast cells according to growth stage, glucose concentration, and quercetin concentration (Fig. 2D-2F). In the PCA plot, the greatest metabolite changes were indicated at 72 and 180 h of incubation time, which were considered the stationary phase (Fig. 2D). The metabolic differentiation of the yeast cells grown under CR (0.5% and 0.2% glucose) from those grown the control condition (2.0% glucose) demonstrated that CR induces significant intracellular metabolite alterations (Fig. 2E).

To explore the influence of quercetin on anti-aging and longevity, DMSO-only-treated yeast cells were compared to those grown without DMSO. The results demonstrated that DMSO itself influences yeast cell metabolism (Fig. 2F). Although DMSO is commonly used to dissolve hydrophobic quercetin, the intracellular metabolites were found to be markedly affected by quercetin treatment in a concentration-dependent manner, as evidenced by the clear metabolic differentiations of the yeast cells treated with different concentrations of quercetin compared to both the control and DMSO-only-treated cells (Fig. 2F).

Identification of intracellular metabolites dependent on yeast cell growth

To identify the individual intracellular metabolites related to growth, OPLS-DA models were derived from the ¹H NMR spectra data of the yeast cell extracts, as shown in Fig. 3. The OPLS-DA score plots for the pairwise comparison showed a clear differentiation between yeast cells collected at 9 and 12 h (Fig. 3A), 12 and 24 h (Fig. 3B), 24 and 72 h (Fig. 3C), and 72 and 180 h (Fig. 3D). The fitness and predictability of these models were found to be good and high, as indicated by R²X values from 0.59 to 0.94 and Q² values from 0.92 to 0.99, respectively. The OPLS-DA loading plots showed that the intracellular metabolites changed at 12 h (Fig. 3E), 24 h (Fig. 3F), 72 h (Fig. 3G), and 180 h (Fig. 3H) compared with those at 9, 12, 24, and 72 h. The OPLS-DA loading plot (Fig. 3E) indicated that some intracellular metabolites were elevated at 12 h of growth compared to at 9 h of growth, while others were decreased at 12 h.

As shown in the OPLS-DA loading plots, marked changes were observed in the levels of diverse intracellular metabolites in aging yeast cells. For example, the levels of valine, leucine, isoleucine, GPC, choline, orotate, tyrosine, and phenylalanine were elevated in the cells incubated for 12 h compared with those incubated for 9 h. In contrast, the levels of ethanol, acetate, glutamine, glutamate, thiamine, aspartate, lysine, glycerol, trehalose, glycine, ATP, uracil, fumarate, histidine, and NAD⁺ were reduced in the yeast cells incubated for 12 h (Fig. 3E). In the yeast cells incubated for 24 h, the elevated levels of ethanol, threonine, acetate, proline, GPC, glycine, glycerol, ATP, orotate, fumarate and histidine, and the reduced levels of valine, leucine, isoleucine, lactate, glutamate, glutamine, thiamine, asparagine, serine, trehalose, phenylalanine and tyrosine were observed, compared to those in the yeast cells incubated for 12 h (Fig. 3F). Although the levels of intracellular metabolites were reduced at 72 h compared with those at 24 h, valine, leucine, isoleucine, ethanol, choline, trehalose, and fumarate levels were elevated in the yeast cells incubated for 72 h (Fig. 3G). In particular, marked elevations of trehalose and ethanol were noted in the yeast cells incubated for 72 h. In addition, a smaller number of intracellular metabolites were different in the cells incubated for 72-180 h (Fig. 3H).

Supplementary Fig. 3 shows the relative and quantitative changes in the individual intracellular metabolites during yeast cell growth. These changes were calculated on the basis of the integral area of the ¹H NMR spectra corresponding to each metabolite. Yeast cells primarily metabolize glucose, simultaneously releasing ethanol. When glucose availability is limited, yeast cells undergo a diauxic shift, which is characterized by a decreased or slowed growth rate and a shift in metabolism from glycolysis to aerobic ethanol utilization (Herman, 2002). We also observed these metabolic behaviors, which are common for yeast cells, in the current study, as indicated by the highest amounts of ethanol at 72 h, followed by a marked decrease at 180 h (Supplementary Fig. 3A). This large amount of intracellular ethanol can lead to oxidative damage due to the accumulation of ROS (Landolfo et al., 2008). However, all living cells, including yeasts, exhibit a molecular response to adverse environmental conditions such as oxidative stress, osmotic stress, heat shock, and starvation (Mager and Ferreira, 1993; Hounsa et al., 1998). In particular, trehalose serves as a general protector against harmful metabolic activities, helping to preserve cell structure and function as it accumulates under stress conditions and at the beginning of the stationary growth phase (Wiemken, 1990). Therefore, the large amounts of intracellular trehalose observed at 72 h was likely the result of cellular stressors such as aging and ethanol toxicity (Supplementary Fig. 3Q).

The glycerol level showed a tendency to decrease during the incubation period (Supplementary Fig. 3C), indicating that glycerol was utilized as a carbon source during glucose deficiency (Scanes et al., 1998). Most amino acids exhibited a gradual reduction during the late or stationary growth stage compared with the early growth stage. Interestingly, however, branched chain amino acids (BCAAs), such as leucine, isoleucine, and valine, increased during this time (Supplementary Fig. 3). On complex media, the generation time for wild-type yeast is estimated to be approximately 80 minutes (Breitenbach et al., 2011), meaning that the 11th generation corresponds to the early stationary stage in the current study. Although the levels of BCAAs, with the exception of leucine, were not significantly altered during the exponential and early stationary phases, they are important amino acids during chronological aging (Alvers et al., 2009). BCAAs play an essential role in CLS through the general amino acid control pathway, which regulates cellular amino acid homeostasis (Hinnebusch, 2005).

The proline levels in wild-type yeast cells have been reported to decrease during the stationary stage compared to the exponential stage (Takagi et al., 2005). In the current study, the lowest levels of proline were observed in the late-stationary stage (after 180 hours of cultivation) (Supplementary Fig. 3X), consistent with the results of a previous study (Houtkooper et al., 2011). Proline within the cells helps protect yeast from various stressors, including freezing, desiccation, and ROS (Takagi et al., 2016). Previous research has also shown that proline enhances yeast cell viability under ethanol stress (Takagi et al., 2005). Consequently, the reduced proline levels in the yeast cells cultured for longer than 24 h may reflect their inability to endure the stress associated with aging.

CLS assay and perturbation of intracellular metabolites by CR

Before the ¹H NMR spectroscopic analysis, a spot assay was conducted to investigate the impact of different glucose concentrations (0.2%, 0.5%, and 2.0%) on the CLS of yeast cells (Supplementary Fig. 4). On the indicated days, aliquots of the yeast cultures were subjected to 10-fold serial dilution, and then spotted onto YPD agar plates containing 2.0% glucose. The results revealed significant variations in the viabilities of the yeast cells across different glucose concentrations. Notably, the CR conditions (0.2% and 0.5% glucose) significantly prolonged the lifespan of wild-type yeast cells compared with the control glucose concentration of 2.0%. After day 13, yeast cells growing with 2.0% glucose had disappeared from the spots that were diluted 1,000-fold, whereas cells grown under CR conditions (0.2% and 0.5% glucose) were found to still be viable. On day 27, there were only subtle differences in viability between the two CR conditions, but no viable yeast cells remained in the 2.0% glucose concentration at any dilution level (Supplementary Fig. 4). Subsequently, a ¹H NMR-based metabolomic analysis of the yeast cell extracts was conducted to identify the metabolites associated with normal and CR conditions.

Comparison of the intracellular metabolite levels in yeast cells grown under different glucose concentrations (0.2%, 0.5%, and 2.0%) was conducted to explore the metabolic mechanisms related to lifespan extension induced by CR. The yeast cells grown in 0.2% and 0.5% glucose were found to be metabolically different from those grown in 2.0% glucose (Fig. 4A and 4B). The levels of valine, isoleucine, leucine, alanine, lysine, glutamate, glutamine, proline, asparagine, choline, trehalose, GTP, fumarate, tyrosine, phenylalanine, and tryptophan, were found to be higher in the yeast cells grown with 0.5% glucose than in those grown with 2.0% glucose. In contrast, the levels of ethanol, lactate, threonine, acetate, aspartate, GPC, glycine, glycerol, serine, glycerol, arginine, uracil, and orotate were lower in the yeast cells grown under 0.2% glucose than in those grown under 2.0% glucose (Fig. 4E). Meanwhile, the levels of valine, leucine, glutamate, proline, choline, asparagine, trehalose, GTP, fumarate, and tryptophan were higher in the yeast cells grown in 0.2% glucose than in those grown in 2.0% glucose (Fig. 4D). Furthermore, the levels of ethanol, lactate, threonine, acetate, thiamine, aspartate, GPC, glycine, glycerol, serine, ATP, uracil, orotate, and histidine were decreased in the 0.2%-glucose-treated cells. As the yeast cells cultured with either 0.5% and 0.2% glucose were also clearly differentiated metabolically (Fig. 4C), the intracellular metabolites that differed between these two conditions were identified via an OPLS-DA loading plot (Fig. 4F), which revealed that higher lactate, alanine, lysine, proline, choline, trehalose, and uracil levels were observed in the yeast cells grown with 0.2% glucose compared with those grown with 0.5% glucose. Meanwhile, the levels of valine, isoleucine, leucine, threonine, glutamine, glutamate, thiamine, aspartate, asparagine, GPC, serine, ATP, tyrosine, histidine, phenylalanine, and tryptophan were lower in the yeast cells grown under 0.2% glucose (Fig. 4F).

The relative levels of individual metabolites in yeast cells grown under different glucose concentrations are shown in Supplementary Fig. 5. Generally, sufficient glucose levels lead to increased ethanol production during fermentation. However, yeast undergoes a metabolic shift from fermentation to respiration when glucose is limited, with the carbon source being directed into the TCA cycle in the mitochondria (Lin et al., 2002). This metabolic shift during CR was indicated by the large reduction in the intracellular ethanol levels in the yeast cells grown at 0.5% and 0.2% glucose (Supplementary Fig. 5A).

Trehalose accumulates in yeast under conditions of glucose limitation or when external supplies are scarce (Lillie and Pringle, 1980). Wiemken (1990) suggested that trehalose does not primarily function as a reserve carbohydrate in yeasts but, rather, as a highly efficient protective agent to maintain the structural integrity of the cytoplasm under conditions of stress. The increased levels of trehalose observed in the yeast cells grown at 0.5% and 0.2% glucose compared to those grown at 2.0% glucose was likely due to this glucose limitation (Supplementary Fig. 5Q). Trehalose also contributes to yeast longevity by protecting cells from protein aggregation, which can lead to oxidative carbonylation due to intracellular ROS accumulation. In addition, the aging process influences the levels of trehalose (Goldberg et al., 2009; Kyryakov et al., 2012). Therefore, trehalose should be viewed as an important metabolite for enduring cellular stress, potentially contributing to the extension of CLS.

Proline is recognized as a key metabolite that plays a crucial role in cellular signaling pathways during stress conditions. In S. cerevisiae, proline is used as an energy source when the nutritional environment changes (Pallotta, 2014). Studies in C. elegans have shown that proline supplementation can lead to lifespan extension (Zarse et al., 2012). In addition, proline contributes electrons that are used to produce ROS and can enter the electron transport chain (ETC) to generate ATP, aiding survival under nutritional stress (Phang et al., 2010). In the current study, the proline levels increased as the glucose concentration decreased (Supplementary Fig. 5X), suggesting that the upregulation of proline in yeast cells during CR might contribute to their extended lifespan.

Variation of intracellular metabolites induced by quercetin treatment

Similar to CR, the lifespan extension effects of the antioxidants such as quercetin and resveratrol have been reported in yeast cells (Howitz et al., 2003; Belinha et al., 2007). For instance, quercetin has been shown to extend the CLS by approximately 60% by reducing oxidative stress, a significant factor influencing longevity (Belinha et al., 2007). However, direct evidence of lifespan extension through quercetin treatment in the spot assay was not observed in the current study. This may be due to the different pathways involved in lifespan extension between CR and quercetin treatments, as indicated in previous studies (Suchankova et al., 2009).

As shown in Fig. 5A and 5E, significant perturbations of the intracellular metabolite levels in the yeast cells treated with DMSO only, which was used to dissolve the hydrophobic quercetin compound, were observed. The syntheses of ethanol and trehalose were markedly reduced and elevated, respectively, in the DMSO-treated yeast cells compared with control cells (Fig. 5E). In the yeast cells treated with 0.05 and 0.2 mg of quercetin, the changes in the intracellular metabolite levels were found to be similar (Fig. 5B, 5C, 5F, and 5G). The levels of ethanol, proline, aspartate, uracil, fumarate, and histidine were increased in the yeast cells treated with quercetin compared with those in the yeast cells treated with DMSO only, whereas the levels of trehalose, BCAAs, alanine, acetate, glutamine, glutamate, thiamine, asparagine, choline, ATP, NAD⁺ and orotate were decreased when quercetin was treated. Compared with the intracellular metabolite levels between yeast cells treated with 0.05 and 0.2 mg of quercetin (Fig. 5D), quercetin, BCAAs, proline, aspartate, uracil, fumarate, and phenylalanine were increased in the yeast cells treated with 0.2 mg of quercetin (Fig. 5H). Meanwhile, the lactate, threonine, lysine, acetate, arginine, glutamate, glutamine, thiamine, asparagine, ATP, NAD⁺, and orotate levels were decreased in the yeast cells treated with 0.2 mg of quercetin. The relative, quantitative changes in intracellular metabolites of the yeast cells treated with DMSO only and those treated with 0.05 mg and 0.2 mg of quercetin are shown in Supplementary Fig. 6. The levels of intracellular quercetin were increased in a concentration-dependent manner (Supplementary Fig. 6W).

The elevated trehalose levels in the yeast cells treated with DMSO demonstrated that DMSO acted as a stressful stimulus, which consequently led to a reduction in ethanol production (Supplementary Fig. 6F). Previous studies have indicated that DMSO induces oxidative stress in yeast cells, resulting in hydrogen-peroxide-mediated cell death (Kwak et al., 2010; Sadowska-Bartosz et al., 2013). In response to this oxidative stress, yeast cells accumulate trehalose as a protective mechanism (Herdeiro et al., 2006). Therefore, it is important to consider the effects of DMSO on metabolic changes. In the current study, we compared the intracellular metabolites of quercetin-treated yeast cells with those of DMSO-treated cells, as quercetin is dissolved by DMSO. The elevated levels of intracellular trehalose, which resulted from DMSO-induced cellular stress, were restored to normal levels in all quercetin-treated yeast cells (Supplementary Fig. 6A). DMSO-induced reductions in yeast cell viability and decreases in yeast CLS have been reported previously (Belinha et al., 2007). In addition, we observed that the intracellular ethanol levels were normalized when quercetin was administered to the yeast cells (Supplementary Fig. 6F). These findings suggest that quercetin offers protective effects against DMSO-induced cellular stress, as reported previously by Belinha et al. (2007). In fact, the quercetin concentrations ranged from 3.3 to 13.0 μM in the current study, which were less than 32.5 μM in the previous report (Belinha et al., 2007). Nevertheless, quercetin exhibited significant effects that are associated with cellular stress and longevity.

Fig. 6 highlights the intracellular metabolites associated with energy metabolism, cellular stress, and longevity in yeast cells. Proline levels are known to decrease with age in various tissues and organisms, such as in the plasma and muscle of aged mice (Uchitomi et al., 2019), as well as in yeast cells (Mukai et al., 2019). Proline supplements have been shown to extend the lifespan of yeast (Mukai et al., 2019; Nishimura et al., 2021). Recently, Choudhury et al. (2024) reported that senescent cells exhibit diminished proline biosynthesis, but which proline supplementation rejuvenates their impaired mitochondrial function. This includes including improvements in mitophagy and a reversal of aging hallmarks, such as DNA damage and reduced expression of senescence-associated β-galactosidase in senescent mesenchymal stem cells (MSCs). Other studies have specifically highlighted the impact of proline on the mitochondrial ETC and longevity in both yeast and MSCs (Nishimura et al., 2021; Choudhury et al., 2024). These studies have confirmed that exogenous proline supplementation contributes to the extension of the lifespan of yeast and MSC cells. In the current study, endogenous or intracellular trehalose levels were consistently increased in response to cellular stress induced by aging, CR, and DMSO treatment in yeast cells (Fig. 6G-6I). Interestingly, while intracellular proline levels were shown to decline with aging (Fig. 6J), they markedly increased during CR and quercetin treatments (Fig. 6K and 6L). This suggests that CR and quercetin may share metabolic pathways that promote lifespan extension in yeast cells by enhancing intracellular proline synthesis (Fig. 6N). Notably, the increase in proline synthesis observed with the quercetin treatments may contribute to the extension of lifespan in yeast without inducing cellular stress, as the intracellular trehalose levels remained stable in the quercetin-treated yeast cells (Fig. 6I). Although the current study does not provide direct metabolic evidence linking quercetin treatments to lifespan extension, several findings suggested its potential role in lifespan extension. These included a low growth rate, similar to that seen with CR, the alleviation of DMSO-induced cellular stress, and an increase in intracellular proline. Together, these results indicate that quercetin may improve mitochondrial function by reducing ROS and DNA damage, as well as enhancing mitophagy and ETC activities, ultimately contributing to lifespan extension (Fig. 6O). In conclusion, of the noted variations in the diverse intracellular metabolites in the present study, a marked increase in intracellular trehalose levels indicates a metabolic response to cellular stresses caused by aging, glucose depletion or CR, and DMSO treatments. Indeed, the upregulation of proline synthesis in yeast cells during the CR and quercetin treatments highlights that these two interventions share metabolic pathways related to lifespan extension, which decline with age. The current study provides valuable biomarkers for assessing the effects of diets or food-derived bioactive components in aging research.

• 1.Alam MM, Meerza D, Naseem I. Protective effect of quercetin on hyperglycemia, oxidative stress and DNA damage in alloxan induced type 2 diabetic mice. Life Sci. 2014. 109:8-14. https://doi.org/10.1016/j.lfs.201406005 10.1016/j.lfs.201406005 [DOI] [PubMed]
• 2.Alía M, Mateos R, Ramos S, Lecumberri E, Bravo L, Goya L. Influence of quercetin and rutin on growth and antioxidant defense system of a human hepatoma cell line (HepG2). Eur J Nutr. 2006. 45:19-28. https://doi.org/10.1007/s00394-005-0558-7 10.1007/s00394-005-0558-7 [DOI] [PubMed]
• 3.Alvers AL, Fishwick LK, Wood MS, Hu D, Chung HS, Dunn WA Jr, et al. Autophagy and amino acid homeostasis are required for chronological longevity in Saccharomyces cerevisiae. Aging Cell. 2009. 8:353-369. https://doi.org/10.1111/j.1474-9726.2009.00469.x 10.1111/j.1474-9726.2009.00469.x [DOI] [PMC free article] [PubMed]
• 4.Anderson RM, Bitterman KJ, Wood JG, Medvedik O, Sinclair DA. Nicotinamide and PNC1 govern lifespan extension by calorie restriction in Saccharomyces cerevisiae. Nature. 2003. 423:181-185. https://doi.org/10.1038/nature01578 10.1038/nature01578 [DOI] [PMC free article] [PubMed]
• 5.Belinha I, Amorim MA, Rodrigues P, de Freitas V, Moradas-Ferreira P, Mateus N, et al. Quercetin increases oxidative stress resistance and longevity in Saccharomyces cerevisiae. J Agric Food Chem. 2007. 55:2446-2451. https://doi.org/10.1021/jf063302e 10.1021/jf063302e [DOI] [PubMed]
• 6.Breitenbach M, Laun P, Jazwinski SM. Introduction. In: Breitenbach M, Jazwinski S, Laun P, editors. Aging Research in Yeast. Springer. 2011. p 1-12. 10.1007/978-94-007-2561-4_1 [DOI] [PubMed]
• 7.Chen YF, Wu CY, Kao CH, Tsai TF. Longevity and lifespan control in mammals: Lessons from the mouse. Ageing Res Rev. 2010. 9 Suppl 1:S28-S35. https://doi.org/10.1016/j.arr.201007003 10.1016/j.arr.201007003 [DOI] [PubMed]
• 8.Choudhury D, Rong N, Senthil Kumar HV, Swedick S, Samuel RZ, Mehrotra P, et al. Proline restores mitochondrial function and reverses aging hallmarks in senescent cells. Cell Rep. 2024. 43:113738. https://doi.org/10.1016/j.celrep.2024.113738 10.1016/j.celrep.2024.113738 [DOI] [PubMed]
• 9.Dieterle F, Ross A, Schlotterbeck G, Senn H. Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in ¹H NMR metabonomics. Anal Chem. 2006. 78:4281-4290. https://doi.org/10.1021/ac051632c 10.1021/ac051632c [DOI] [PubMed]
• 10.Fontana L, Partridge L, Longo VD. Extending healthy life span-from yeast to humans. Science. 2010. 328:321-326. https://doi.org/10.1126/science.1172539 10.1126/science.1172539 [DOI] [PMC free article] [PubMed]
• 11.Goldberg AA, Bourque SD, Kyryakov P, Gregg C, Boukh-Viner T, Beach A, et al. Effect of calorie restriction on the metabolic history of chronologically aging yeast. Exp Gerontol. 2009. 44:555-571. https://doi.org/10.1016/j.exger.200906001 10.1016/j.exger.200906001 [DOI] [PubMed]
• 12.Guarente L, Picard F. Calorie restriction-the SIR2 connection. Cell. 2005. 120:473-482. https://doi.org/10.1016/j.cell.2005年01月02日9 10.1016/j.cell.2005年01月02日9 [DOI] [PubMed]
• 13.Hamilton B, Dong Y, Shindo M, Liu W, Odell I, Ruvkun G, et al. A systematic RNAi screen for longevity genes in C. elegans. Genes Dev. 2005. 19:1544-1555. https://doi.org/10.1101/gad.1308205 10.1101/gad.1308205 [DOI] [PMC free article] [PubMed]
• 14.Herdeiro RS, Pereira MD, Panek AD, Eleutherio EC. Trehalose protects Saccharomyces cerevisiae from lipid peroxidation during oxidative stress. Biochim Biophys Acta. 2006. 1760:340-346. https://doi.org/10.1016/j.bbagen.2006年01月01日0 10.1016/j.bbagen.2006年01月01日0 [DOI] [PubMed]
• 15.Herman PK. Stationary phase in yeast. Curr Opin Microbiol. 2002. 5:602-607. https://doi.org/10.1016/s1369-5274(02)00377-6 10.1016/S1369-5274(02)00377-6 [DOI] [PubMed]
• 16.Hinnebusch AG. Translational regulation of GCN4 and the general amino acid control of yeast. Annu Rev Microbiol. 2005;59: 407-450. https://doi.org/10.1146/annurev.micro.59.031805.133833 10.1146/annurev.micro.59.031805.133833 [DOI] [PubMed]
• 17.Hounsa CG, Brandt EV, Thevelein J, Hohmann S, Prior BA. Role of trehalose in survival of Saccharomyces cerevisiae under osmotic stress. Microbiology. 1998. 144:671-680. https://doi.org/10.1099/00221287-144-3-671 10.1099/00221287-144-3-671 [DOI] [PubMed]
• 18.Houtkooper RH, Argmann C, Houten SM, Cantó C, Jeninga EH, Andreux PA, et al. The metabolic footprint of aging in mice. Sci Rep. 2011. 1:134. https://doi.org/10.1038/srep00134 10.1038/srep00134 [DOI] [PMC free article] [PubMed]
• 19.Howitz KT, Bitterman KJ, Cohen HY, Lamming DW, Lavu S, Wood JG, et al. Small molecule activators of sirtuins extend Saccharomyces cerevisiae lifespan. Nature. 2003. 425:191-196. https://doi.org/10.1038/nature01960 10.1038/nature01960 [DOI] [PubMed]
• 20.Kaeberlein M. Longevity and aging in budding yeast. In: Conn PM, editor. Handbook of Models for Human Aging. Academic Press. 2006. p 207-217. 10.1016/B978-012369391-4/50019-9 [DOI]
• 21.Kamei Y, Tamura T, Yoshida R, Ohta S, Fukusaki E, Mukai Y. GABA metabolism pathway genes, UGA1 and GAD1, regulate replicative lifespan in Saccharomyces cerevisiae. Biochem Biophys Res Commun. 2011. 407:185-190. https://doi.org/10.1016/j.bbrc.2011年02月13日6 10.1016/j.bbrc.2011年02月13日6 [DOI] [PubMed]
• 22.Kenyon CJ. The genetics of ageing. Nature. 2010. 464:504-512. https://doi.org/10.1038/nature08980 10.1038/nature08980 [DOI] [PubMed]
• 23.Kim HJ, Mun JS, Oh SH, Kim JH. Antioxidant and longevity-related properties of the ethyl acetate fraction of Cnidium officinale Makino in Caenorhabditis elegans. Prev Nutr Food Sci. 2024. 29:311-320. https://doi.org/10.3746/pnf.2024293.311 10.3746/pnf.2024293.311 [DOI] [PMC free article] [PubMed]
• 24.Koubova J, Guarente L. How does calorie restriction work? Genes Dev. 2003. 17:313-321. https://doi.org/10.1101/gad.1052903 10.1101/gad.1052903 [DOI] [PubMed]
• 25.Kwak GH, Choi SH, Kim HY. Dimethyl sulfoxide elevates hydrogen peroxide-mediated cell death in Saccharomyces cerevisiae by inhibiting the antioxidant function of methionine sulfoxide reductase A. BMB Rep. 2010. 43:622-628. https://doi.org/10.5483/bmbrep.2010439.622 10.5483/BMBRep.2010439.622 [DOI] [PubMed]
• 26.Kyryakov P, Beach A, Richard VR, Burstein MT, Leonov A, Levy S, et al. Caloric restriction extends yeast chronological lifespan by altering a pattern of age-related changes in trehalose concentration. Front Physiol. 2012. 3:256. https://doi.org/10.3389/fphys.2012.00256 10.3389/fphys.2012.00256 [DOI] [PMC free article] [PubMed]
• 27.Landolfo S, Politi H, Angelozzi D, Mannazzu I. ROS accumulation and oxidative damage to cell structures in Saccharomyces cerevisiae wine strains during fermentation of high-sugar-containing medium. Biochim Biophys Acta. 2008. 1780:892-898. https://doi.org/10.1016/j.bbagen.200803008 10.1016/j.bbagen.200803008 [DOI] [PubMed]
• 28.Lillie SH, Pringle JR. Reserve carbohydrate metabolism in Saccharomyces cerevisiae: responses to nutrient limitation. J Bacteriol. 1980. 143:1384-1394. https://doi.org/10.1128/jb.143.3.1384-1394.1980 10.1128/jb.143.3.1384-1394.1980 [DOI] [PMC free article] [PubMed]
• 29.Lin SJ, Ford E, Haigis M, Liszt G, Guarente L. Calorie restriction extends yeast life span by lowering the level of NADH. Genes Dev. 2004. 18:12-16. https://doi.org/10.1101/gad.1164804 10.1101/gad.1164804 [DOI] [PMC free article] [PubMed]
• 30.Lin SJ, Kaeberlein M, Andalis AA, Sturtz LA, Defossez PA, Culotta VC, et al. Calorie restriction extends Saccharomyces cerevisiae lifespan by increasing respiration. Nature. 2002. 418: 344-348. https://doi.org/10.1038/nature00829 10.1038/nature00829 [DOI] [PubMed]
• 31.Mager WH, Ferreira PM. Stress response of yeast. Biochem J. 1993. 290:1-13. https://doi.org/10.1042/bj2900001 10.1042/bj2900001 [DOI] [PMC free article] [PubMed]
• 32.Mukai Y, Kamei Y, Liu X, Jiang S, Sugimoto Y, Mat Nanyan NSB, et al. Proline metabolism regulates replicative lifespan in the yeast Saccharomyces cerevisiae. Microb Cell. 2019. 6:482-490. https://doi.org/10.15698/mic2019.10.694 10.15698/mic2019.10.694 [DOI] [PMC free article] [PubMed]
• 33.Nicholson JK, Lindon JC. Metabonomics. Nature. 2008. 455: 1054-1056. https://doi.org/10.1038/4551054a 10.1038/4551054a [DOI] [PubMed]
• 34.Nicholson JK, Wilson ID. Understanding 'global' systems biology: Metabonomics and the continuum of metabolism. Nat Rev Drug Discov. 2003. 2:668-676. https://doi.org/10.1038/nrd1157 10.1038/nrd1157 [DOI] [PubMed]
• 35.Nishimura A, Yoshikawa Y, Ichikawa K, Takemoto T, Tanahashi R, Takagi H. Longevity regulation by proline oxidation in yeast. Microorganisms. 2021. 9:1650. https://doi.org/10.3390/microorganisms9081650 10.3390/microorganisms9081650 [DOI] [PMC free article] [PubMed]
• 36.Özyurt H, Çevik Ö, Özgen Z, Özden AS, Çadırcı S, Elmas MA, et al. Quercetin protects radiation-induced DNA damage and apoptosis in kidney and bladder tissues of rats. Free Radic Res. 2014. 48:1247-1255. https://doi.org/10.3109/10715762.2014.945925 10.3109/10715762.2014.945925 [DOI] [PubMed]
• 37.Pallotta ML. L-Proline uptake in Saccharomyces cerevisiae mitochondria can contribute to bioenergetics during nutrient stress as alternative mitochondrial fuel. World J Microbiol Biotechnol. 2014. 30:19-31. https://doi.org/10.1007/s11274-013-1415-0 10.1007/s11274-013-1415-0 [DOI] [PubMed]
• 38.Palomino-Schätzlein M, Molina-Navarro MM, Tormos-Pérez M, Rodríguez-Navarro S, Pineda-Lucena A. Optimised protocols for the metabolic profiling of S. cerevisiae by ¹H-NMR and HRMAS spectroscopy. Anal Bioanal Chem. 2013. 405:8431-8441. https://doi.org/10.1007/s00216-013-7271-9 10.1007/s00216-013-7271-9 [DOI] [PubMed]
• 39.Phang JM, Liu W, Zabirnyk O. Proline metabolism and microenvironmental stress. Annu Rev Nutr. 2010. 30:441-463. https://doi.org/10.1146/annurev.nutr.012809.104638 10.1146/annurev.nutr.012809.104638 [DOI] [PMC free article] [PubMed]
• 40.Pietsch K, Saul N, Chakrabarti S, Stürzenbaum SR, Menzel R, Steinberg CE. Hormetins, antioxidants and prooxidants: defining quercetin-, caffeic acid- and rosmarinic acid-mediated life extension in C. elegans. Biogerontology. 2011. 12:329-347. https://doi.org/10.1007/s10522-011-9334-7 10.1007/s10522-011-9334-7 [DOI] [PubMed]
• 41.Sadowska-Bartosz I, Pączka A, Mołoń M, Bartosz G. Dimethyl sulfoxide induces oxidative stress in the yeast Saccharomyces cerevisiae. FEMS Yeast Res. 2013. 13:820-830. https://doi.org/10.1111/1567-1364.12091 10.1111/1567-1364.12091 [DOI] [PubMed]
• 42.Savorani F, Tomasi G, Engelsen SB. icoshift: A versatile tool for the rapid alignment of 1D NMR spectra. J Magn Reson. 2010. 202:190-202. https://doi.org/10.1016/j.jmr.2009年11月01日2 10.1016/j.jmr.2009年11月01日2 [DOI] [PubMed]
• 43.Scalbert A, Williamson G. Dietary intake and bioavailability of polyphenols. J Nutr. 2000. 130:2073S-2085S. https://doi.org/10.1093/jn/130.8.2073s 10.1093/jn/130.8.2073S [DOI] [PubMed]
• 44.Scanes KT, Hohrnann S, Prior BA. Glycerol production by the yeast Saccharomyces cerevisiae and its relevance to wine: A review. S Afr J Enol Vitic. 1998. 19:17-24. https://doi.org/10.21548/19-1-2239 10.21548/19-1-2239 [DOI]
• 45.Seo SH, Park SE, Yoo SA, Lee KI, Na CS, Son HS. Metabolite profiling of Makgeolli for the understanding of yeast fermentation characteristics during fermentation and aging. Process Biochem. 2016. 51:1363-1373. https://doi.org/10.1016/j.procbio.201608005 10.1016/j.procbio.201608005 [DOI]
• 46.Smith DL Jr, McClure JM, Matecic M, Smith JS. Calorie restriction extends the chronological lifespan of Saccharomyces cerevisiae independently of the Sirtuins. Aging Cell. 2007. 6:649-662. https://doi.org/10.1111/j.1474-9726.2007.00326.x 10.1111/j.1474-9726.2007.00326.x [DOI] [PubMed]
• 47.Smith DL Jr, Nagy TR, Allison DB. Calorie restriction: what recent results suggest for the future of ageing research. Eur J Clin Invest. 2010. 40:440-450. https://doi.org/10.1111/j.1365-2362.2010.02276.x 10.1111/j.1365-2362.2010.02276.x [DOI] [PMC free article] [PubMed]
• 48.Suchankova G, Nelson LE, Gerhart-Hines Z, Kelly M, Gauthier MS, Saha AK, et al. Concurrent regulation of AMP-activated protein kinase and SIRT1 in mammalian cells. Biochem Biophys Res Commun. 2009. 378:836-841. https://doi.org/10.1016/j.bbrc.2008年11月13日0 10.1016/j.bbrc.2008年11月13日0 [DOI] [PMC free article] [PubMed]
• 49.Takagi H, Taguchi J, Kaino T. Proline accumulation protects Saccharomyces cerevisiae cells in stationary phase from ethanol stress by reducing reactive oxygen species levels. Yeast. 2016; 33:355-363. https://doi.org/10.1002/yea.3154 10.1002/yea.3154 [DOI] [PubMed]
• 50.Takagi H, Takaoka M, Kawaguchi A, Kubo Y. Effect of L-proline on sake brewing and ethanol stress in Saccharomyces cerevisiae. Appl Environ Microbiol. 2005. 71:8656-8662. https://doi.org/10.1128/aem.71.12.8656-8662.2005 10.1128/AEM.71.12.8656-8662.2005 [DOI] [PMC free article] [PubMed]
• 51.Tambellini NP. Metabolomic and lipidomic profiling of the effect of edelfosine treatment on Saccharomyces cerevisiae. Master's thesis. University of Calgary. 2014.
• 52.Tissenbaum HA, Guarente L. Increased dosage of a sir-2 gene extends lifespan in Caenorhabditis elegans. Nature. 2001. 410: 227-230. https://doi.org/10.1038/35065638 10.1038/35065638 [DOI] [PubMed]
• 53.Uchitomi R, Hatazawa Y, Senoo N, Yoshioka K, Fujita M, Shimizu T, et al. Metabolomic analysis of skeletal muscle in aged mice. Sci Rep. 2019. 9:10425. https://doi.org/10.1038/s41598-019-46929-8 10.1038/s41598-019-46929-8 [DOI] [PMC free article] [PubMed]
• 54.Wiemken A. Trehalose in yeast, stress protectant rather than reserve carbohydrate. Antonie Van Leeuwenhoek. 1990. 58: 209-217. https://doi.org/10.1007/bf00548935 10.1007/BF00548935 [DOI] [PubMed]
• 55.Wilson MA, Shukitt-Hale B, Kalt W, Ingram DK, Joseph JA, Wolkow CA. Blueberry polyphenols increase lifespan and thermotolerance in Caenorhabditis elegans. Aging Cell. 2006. 5:59-68. https://doi.org/10.1111/j.1474-9726.2006.00192.x 10.1111/j.1474-9726.2006.00192.x [DOI] [PMC free article] [PubMed]
• 56.Zarse K, Schmeisser S, Groth M, Priebe S, Beuster G, Kuhlow D, et al. Impaired insulin/IGF1 signaling extends life span by promoting mitochondrial L-proline catabolism to induce a transient ROS signal. Cell Metab. 2012. 15:451-465. https://doi.org/10.1016/j.cmet.2012年02月01日3 10.1016/j.cmet.2012年02月01日3 [DOI] [PMC free article] [PubMed]
• 57.Zheng X, Chen T, Zhao A, Wang X, Xie G, Huang F, et al. The brain metabolome of male rats across the lifespan. Sci Rep. 2016. 6:24125. https://doi.org/10.1038/srep24125 10.1038/srep24125 [DOI] [PMC free article] [PubMed]

Supplementary Materials