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. 2025 Oct 22;417(29):6529–6537. doi: 10.1007/s00216-025-06153-y

Optimized method for analyzing volatile compounds in edible yeast using headspace SPME-GC-MS

Nho-Eul Song 1, Jeonghyun Yun 1, Sunhee Kang 1, Jang-Eun Lee 1,2,✉
PMCID: PMC12641049  PMID: 41123668

Abstract

Volatile compounds produced by edible yeasts play a critical role in food flavor and consumer perception. This study aimed to evaluate how different yeast preparation methods influence the detection of volatile compounds using gas chromatography-mass spectrometry (GC-MS) coupled with headspace solid-phase microextraction (HS-SPME). Saccharomyces cerevisiae was prepared using four methods—broth culture, agar culture, supernatant, and yeast cell pellet—and volatile profiles were compared with non-polar (DB-5), mid-polar (DB-17), and polar (VF-WAX) GC columns. The supernatant consistently exhibited the greatest diversity and abundant volatile compounds, whereas agar cultures and cell pellets led to fewer volatiles. Principal component analysis (PCA) demonstrated distinct clustering of volatile profiles according to the preparation method, with major compounds such as hexanoic acid ethyl ester and phenylethyl alcohol contributing to group separation. Additionally, the effect of salting-out agents (NaCl and H2NaPO4) on volatiles extraction efficiency was examined, showing that NaCl led to increased levels of alcohols, while H2NaPO4 enhanced acid extraction. These findings underscore the importance of optimizing sample preparation conditions, column polarity, and extraction parameters for accurate and reproducible analysis of yeast-derived volatiles. The results provide practical insights into targeted flavor profiling and the development of yeast-derived flavor applications in the food and fermentation processes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00216-025-06153-y.

Keywords: Saccharomyces cerevisiae, Culture, Volatile compounds, GC column, GC-MS

Introduction

Volatile compounds produced by microorganisms, particularly edible yeasts, play a crucial role in the food industry by enhancing quality and consumer acceptance through improved flavor profiles. Gas chromatography-mass spectrometry (GC-MS) has been widely used as an analytical technique for detecting volatile compounds derived from yeast and fermented foods. However, optimization of the analytical workflow, including yeast culture method and volatile compounds extraction, is necessary to ensure accurate and reproducible results. Several analytical factors, such as culture media, growth conditions, sample preparation, and extraction methods, strongly influence the metabolite profiles detected by GC-MS [1].

Previous studies have employed various cultivation methods to analyze volatile microbial compounds. For instance, Tan et al. [2] optimized the cultivation time of Saprochaete suavelens and demonstrated that agar slant media in crimped vials is an effective approach for profiling volatile yeast metabolites. Similarly, Yalage Don et al. [3] demonstrated the identification of volatile compounds produced by Aureobasidium pullulans grown on agar plates and evaluated their antifungal properties against microbial pathogens. A commonly employed method for analyzing microbial volatile compounds is obtaining the supernatant from a broth culture through centrifugation [4–7]. This protocol ensures a more consistent sample by minimizing the variability related to cell density, growth phase, and metabolic activity.

Although microbial culture methods are crucial factors for the analysis of volatile compounds, few studies have examined the impact of different culture methods on volatile compound production. In this study, four different yeast preparation methods—broth media containing cells, agar culture, cell-free supernatant of the media, and yeast pellet—were compared for yeast volatile compound profiling using headspace solid-phase microextraction (SPME) GC-MS to develop the most effective approach for maximizing the detection and reproducibility of yeast-derived volatile compounds. These findings will contribute to the development of analytical methodologies for food and fermentation research, ensuring more accurate characterization of yeast metabolites and providing a better understanding of yeast flavor profiles and their applications in the food industry.

Materials and methods

Chemicals and reagents

Sodium phosphate monobasic (H2NaPO4, > 99.0%) was purchased from Sigma-Aldrich (St. Louis, MO, USA). Water (LC-MS grade) was purchased from Merck (Kenilworth, NJ, USA). NaCl (99.5% purity) was purchased from Samchun (Seongnam-si, Gyeonggi-do, South Korea). Fiber-coated 50/30 mm divinylbenzene/carboxen on polydimethylsiloxane (DVB/CAR/PDMS), 20-mL headspace vials, and caps with PTFE/silicone septa were acquired from Supelco (Bellefonte, PA, USA). Yeast malt (YM) medium (Difco, Becton, Dickinson and Company, Franklin Lakes, NJ, USA) was used for yeast culture.

Yeast strain and sample preparation

Four types of yeast samples were prepared to optimize volatile compound analysis: broth culture, agar culture, supernatant, and yeast pellet (Fig. 1). Saccharomyces cerevisiae strain Rey 4–7 was pre-cultured in 4 mL of YM broth at 28 °C for 24 h. For broth and agar culture samples, 10 μL of the pre-culture was inoculated into 3 mL of YM broth or spread onto 3 mL of slanted YM agar, respectively, each contained in a 20-mL SPME vial. The broth and agar cultures were incubated at 28 °C for 28 h, cooled at 4 °C for 2 h, and analyzed directly by GC-MS. For supernatant and yeast pellet samples, 10 μL of the pre-culture was inoculated into 4 mL of YM broth and incubated under the same conditions. After cooling at 4 °C for 2 h, the culture was centrifuged at 4000 rpm for 5 min at 4 °C. A 3-mL aliquot of the supernatant was transferred into a 20-mL SPME vial for GC analysis. The cell pellet was washed twice with phosphate-buffered saline (PBS) and resuspended in 4 mL of fresh PBS, and 3 mL of the suspension was transferred into a 20-mL SPME vial for GC analysis.

Fig. 1.

Fig. 1

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Four methods for yeast sample preparation

Extraction using headspace SPME and GC-MS/MS analysis

To optimize analytical conditions, the effects of different salting-out agents and column polarities were investigated. Two salting-out agents (H2NaPO4 and NaCl) were tested at concentrations of 2, 5, 10, 20, 30, 35, and 40% (w/v) using supernatant samples analyzed with a VF-WAX column. Based on preliminary results, 35% (w/v) H2NaPO4 was confirmed as the most effective salting-out agent (Fig. 2; Supplementary Figs. 1–5). To enhance extraction efficiency, 3 mL of liquid samples (broth culture, supernatant, and yeast pellet) was supplemented with 35% H2NaPO4 and incubated at 40 °C for 10 min using a Triplus RSH Autosampler (Thermo Fisher Scientific Inc., West Palm Beach, FL, USA), while agar culture samples were pretreated under the same conditions without the addition of a salting-out agent. Volatile compounds were then extracted for 30 min using a 50/30 um DVB/CAR/PDMS fiber, followed by injection into the GC injector port at 220 °C for 2 min in splitless mode (TRACE 1310, Thermo Fisher Scientific Inc., West Palm Beach, FL, USA). The SPME fiber was preconditioned for 3 min before extraction and postconditioned for 5 min after injection to prevent sample carryover.

Fig. 2.

Fig. 2

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Effect of salting-out optimization on yeast volatile compound distribution

To assess the effect of column polarity on volatile compound separation, three columns with different polarities were compared: DB-5 ms (non-polar), DB-17 (mid-polar), and VF-WAX (polar) (60 m × 0.32 mm × 0.25 µm; Agilent Technologies, Santa Clara, CA, USA). The initial oven temperature was held at 50 °C for 2 min, ramped at 3 °C/min to 185 °C, then at 20 °C/min to 230 °C (polar) or 280 °C (mid-polar and the non-polar), and then held for 7 min. Helium (99.999%) was used as a carrier gas at a flow rate of 1.0 mL/min. Mass spectra were obtained using a triple quadrupole GC-MS/MS system (TSQ 9000, Thermo Fisher Scientific Inc., West Palm Beach, FL, USA) in full-scan mode, covering a mass range of 35 to 400 m/z. Compounds were identified using Free Style software (ver. 1.3; Thermo Fisher Scientific, Waltham, MA, USA) with Wiley (ver. 11) and the NIST (ver. 17) libraries, with a reverse search index threshold of ≥ 700.

Statistical analysis

Data were scaled to unit variance (UV), and principal component analysis (PCA) was conducted using SIMCA-P software (version 17.0; Umetrics, Umeå, Sweden). A heatmap was generated using Python (version 3.11.8) with the min-max normalized (–1 to 1) dataset for each volatile compound to compare the relative abundance. Hierarchical clustering (Ward’s method, Euclidean distance) was applied only to the samples, and a dendrogram was overlaid. The heatmap used the “RdYlGn_r” colormap, where high values present red and low values green. The bar graphs were generated using GraphPad Prism (version 10.3.1, GraphPad Software, Boston, MA, USA).

Results

Optimization of salting-out agent for yeast volatile compound analysis

Preliminary tests demonstrated that increasing the concentrations of NaCl and H2NaPO4 enhanced peak intensities; however, precipitation occurred above 35%, leading to the selection of 35% as the final concentration (Figs. S1–S5). Figure 2 illustrates the distribution of volatile compounds under two salting-out conditions (35% H2NaPO4 and 35% NaCl), categorized into esters, alcohols, acids, ketones, and aldehydes. Overall, alcohols were the dominant volatile class across all tested salting-out conditions, exhibiting notably higher peak areas than those of the other classes. Specifically, NaCl (35%) treatment resulted in a higher relative abundance of alcohols compared to 35% H2NaPO4, indicating that this condition enhances alcohol recovery. Similarly, ester compounds showed considerable peak intensities under both H2NaPO4 (35%) and NaCl (35%) conditions, highlighting these salts’ efficacy for ester extraction. Lenti et al. [8] evaluated the use of salting-out agents to enhance extraction efficiency, with H2NaPO4 notably increasing method sensitivity compared to extractions performed without salt. By contrast, acids were moderately abundant, with a higher extraction observed under H2NaPO4 (35%) than NaCl (35%). Ketones and aldehydes showed comparatively lower levels across both conditions, with minimal differences among treatments, indicating the limited influence of salting-out optimization on these compound classes. These findings indicate that the choice of salt type and concentration during salting-out extraction substantially influences the recovery and distribution profiles of yeast-derived volatile compounds, particularly favoring alcohol and ester enrichment. Thus, careful optimization of the salting-out conditions is essential for selectively enhancing specific volatile classes and facilitating targeted aroma profiling in yeast-related food and beverage applications.

Effects of sample preparation methods on yeast volatile compounds

The volatile compounds produced by S. cerevisiae using different sample preparation approaches were identified using SPME coupled with GC-MS. As shown in Fig. 3, distinct differences in volatile compound profiles were observed depending on the sample preparation method. The supernatant exhibited the richest and most diverse volatile compound profile, indicating that many volatiles were released into the extracellular environment. Volatile compounds with relatively low molecular weights such as benzaldehyde, acetic acid octyl ester, and 2-octanone were abundant in the supernatant. Broth cultures also contained a relatively broad range of volatile compounds due to the favorable liquid conditions that enhance metabolite solubility and extraction efficiency [9, 10]. Notably, some volatile compounds, such as ethanol, 1-butanol, 3-methyl-1-butanol, hexanoic acid ethyl ester, octanoic acid ethyl ester, decanoic acid ethyl ester, and octanoic acid, were significantly higher in the broth culture.

Fig. 3.

Fig. 3

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Heatmap analysis of yeast volatile compounds produced using four different sample preparation methods

By contrast, both the yeast pellet fractions and agar cultures contained notably fewer volatile compounds, possibly because of limited diffusion from solid matrices or challenges in extracting intracellularly retained compounds [11]. The yeast cell pellet showed unique detection of certain compounds like isobutyl acetate, which were not observed in other sample types. In the agar culture, only selective volatile components such as butanoic acid 2-methyl ethyl ester, acetoin, acetic acid, propanoic acid, propanoic acid 2-methyl, ethyl acetate, and phenylethyl alcohol were efficiently analyzed.

These findings highlight the critical influence of sample preparation methods on the extraction efficiency and detectability of yeast-derived volatile compounds. The observed differences in volatile compound profiles likely result from varying extraction efficiencies rather than biological variation in yeast metabolism. Among the tested methods, agar culture required the most time for sample preparation and processing, but produced the lowest number of detectable volatile aroma compounds, indicating that it is a less efficient method for comprehensive volatilome analysis. Based on the broad spectrum of detected volatile compounds and superior extraction capability, the supernatant was considered to be advantageous for volatile compound analysis of yeast.

To the best of our knowledge, this is the first study to demonstrate that the composition and abundance of volatile compounds extracted from yeasts are substantially affected by the sample preparation methods employed. According to previous studies, broth culture is advantageous for real-time VOC analysis and metabolic kinetic tracking during liquid cultivation ([12, 13]) and agar culture is advantageous for observing the diffusion and interaction of VOCs and can be used for biological control research [14, 15].

Influence of GC column polarity on volatile compound detection

Heatmaps illustrating the volatile compound profiles of yeast obtained from four different culture methods were analyzed by GC with columns of varying polarities: (A) non-polar (DB-5), (B) mid-polar (DB-17), and (C) polar (VF-WAX). Color intensities in the heatmaps represent the relative abundance of each compound, with red indicating higher abundance and green indicating lower abundance. As shown in Fig. 3, the number and types of volatile compounds detected varied significantly across the columns, reflecting their differential selectivity toward various chemical classes.

The VF-WAX column, which is based on polyethylene glycol and exhibits strong polarity, selectively enhances the detection of polar volatiles, including short-chain organic acids and alcohols. Polar columns are commonly employed in the analysis of alcoholic beverages such as liquor [16], spirits [17], and alcoholic beverages [18]. As shown in Fig. 3C, VF-WAX showed a strong affinity for alcohols, with ethanol, 3-methyl-1-butanol, and phenylethyl alcohol consistently detected at high intensities. In addition, short-chain organic acids such as acetic acid, butanoic acid, and propanoic acid were more prominently detected on the VF-WAX column than on the other columns. The carbonyl compounds acetone and acetoin were detected specifically on the VF-WAX column, indicating column-specific selectivity for these volatile metabolites.

The DB-5 column (5% phenyl-methylpolysiloxane) enables the effective separation of non-polar and semi-polar compounds and is commonly employed in the analysis of alcoholic beverages such as wine [19] and beer [20]. This column enabled high-resolution detection of esters and alcohols, such as isoamyl acetate, ethyl hexanoate, and phenylethyl alcohol. Owing to its low polarity, DB-5 shows enhanced sensitivity to hydrocarbons and branched-chain esters. Figure 3A indicates that DB-5 provided the broadest coverage of yeast volatiles, capturing both fusel alcohols and medium-chain esters. Among alcohols, 1-hexanol, 1-heptanol, and 1-octanol were detected exclusively on this column. In addition, pentyl butanoate and 4-methylpentanoic acid ethyl ester were clearly identified. DB-5 served as a versatile platform for balanced detection of higher alcohols and fatty acid ethyl esters.

The DB-17 column, with intermediate polarity owing to its 50% phenyl-methylpolysiloxane composition, provided a balanced profile, capturing both non-polar and moderately polar compounds. Esters and ketones, including ethyl butyrate and 2-heptanone, were effectively separated [21], making DB-17 suitable for compositional profiling when complex mixtures were analyzed. The DB-17 column was useful for the analysis of volatile compounds, including phenols, furans, and sulfur compounds [22, 23]. As shown in Fig. 3B, compounds including 2-heptanone, 2-tetradecanone, 2-methyl-3-heptanone, and 2-methyl-4-octanone, which are classified as medium- to long-chain methyl ketones, were selectively detected on the DB-17 column. In addition, the DB-17 column exhibited stronger responses for short-chain esters such as ethyl propanoate, ethyl heptanoate, and 3-methylbutyl octanoate, but its contribution overlapped substantially with VF-WAX and DB-5. Major yeast metabolites were consistently detected on both polar and non-polar columns, with complementary detection profiles providing comprehensive metabolite coverage. Therefore, the combined use of VF-WAX and DB-5 ensures comprehensive profiling while minimizing redundancy and analytical complexity.

These findings highlight the importance of selecting appropriate GC column polarity for characterizing the volatile compounds of yeast and provide methodological guidance for targeted analysis in yeast-derived volatile compounds.

Major volatile compounds in different yeast preparation methods

Figure 4 shows the peak areas of selected key volatile compounds from yeast samples prepared using four different methods (supernatant, agar culture, broth culture, and yeast pellet), as analyzed using two different GC columns: non-polar (DB-5; A–D) and polar (VF-WAX; E–H).

Fig. 4.

Fig. 4

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Peak area of major volatile compounds from four yeast sample preparation methods, analyzed using non-polar (A–D) and polar (E–H) columns

In both the non-polar DB-5 and polar VF-WAX column analyses, similar patterns were observed, but the detection intensities of the major compounds by preparation methods were different. Among the four major compounds, hexanoic acid ethyl ester (Fig. 4A and E) was detected in all culture methods. However, the detection intensities were higher in the supernatant and broth than in the agar culture and yeast pellet. The peak areas obtained from the broth cultures using the polar column exhibited considerable variation (Fig. 4E). Phenylethyl alcohol (Fig. 4B and F) was also detected in all sample preparation methods but was significantly more abundant in the agar culture. Acetic acid 2-ethylhexyl ester (Fig. 4C and G) exhibited the highest abundance in the yeast pellet, was present at moderate levels in both the supernatant and broth cultures, and was only minimally detected in the agar culture. The yeast pellet analyzed using the non-polar column showed high variability in peak areas (Fig. 4C). Hexanoic acid ethyl ester was primarily detected in the supernatant and broth cultures, with relatively low levels observed in agar cultures and yeast cells, owing to its efficient biosynthesis and membrane permeability. By contrast, phenylethyl alcohol and acetic acid 2-ethylhexyl ester were found in both the intracellular and extracellular fractions, but exhibited limited extracellular presence, suggesting strong cell association and restricted diffusion. This differential distribution reflects the compounds’ lipophilicity and membrane transport dynamics, emphasizing the need to consider both intracellular production and extracellular secretion when profiling yeast-derived volatile compounds.

Benzaldehyde, a secondary metabolite derived from phenylalanine via the Ehrlich pathway and formed through the oxidation of phenylacetaldehyde, was exclusively detected in the supernatant but not in the broth culture (Figs. 3H and 4D). This absence is likely due to its volatile and hydrophobic characteristics, which facilitate its rapid diffusion from yeast cells into the extracellular medium. A comparison of the detection intensities revealed that hexanoic acid ethyl ester, phenylethyl alcohol, and acetic acid 2-ethylhexyl ester exhibited greater responses on the non-polar column than on the polar column, whereas acetic acid 2-ethylhexyl ester was undetectable on the polar column. By contrast, benzaldehyde showed a higher detection intensity on the polar column.

Overall, the two columns provided comparable and consistent results, emphasizing the importance of sample preparation methods for the distribution of volatile compounds. Among the four yeast preparation methods evaluated, the supernatant consistently exhibited the greatest variety of detected compounds across the two column types. These results highlighted the selective presence of specific volatiles in different yeast culture fractions, which are essential for targeted aroma profile development in yeast-derived applications.

Volatile compound profiles under different yeast preparation methods

Figure 5 illustrates the PCA of yeast-derived volatile compounds analyzed using non-polar (Fig. 5A and B) and polar (Fig. 5C and D) GC columns. PCA score plots (Fig. 5A and C) differentiated yeast volatile profiles based on the preparation methods (supernatant, broth culture, agar culture, and yeast pellet). In the PCA score plot derived from the non-polar column (Fig. 5A), PC1 and PC2 accounted for 71.1% and 14.9% of the total variance, respectively, clearly segregating the volatile profiles according to the preparation method. The supernatant and broth culture samples formed a distinct cluster. However, the close clustering of both samples suggested limitations in discriminating between the two preparation methods. The agar culture and yeast pellet also formed distinct clusters, indicating unique volatile profiles under each preparation condition. The corresponding loading scatter plot (Fig. 5B) identifies the major volatile compounds responsible for this differentiation. Phenylethyl alcohol and 3-methyl-1-butanol were the primary volatiles contributing to the separation along PC1. By contrast, octanoic acid ethyl ester notably influenced the separation along PC2.

Fig. 5.

Fig. 5

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PCA score (A, C) and loading scatter (B, D) plots generated from yeast volatile compounds analyzed using non-polar (A, B) and polar (C, D) columns. The goodness of fit (R2X) and prediction ability (Q2) of the PCA models were 0.887 and 0.822 for the non-polar column (A, B), and 0.935 and 0.828 for the polar column (C, D), respectively

The PCA score plot obtained from the polar column analysis (Fig. 5C) showed clear distinctions between the preparation methods, with PC1 and PC2 explaining 42.2% and 31.1% of the total variance, respectively. Supernatant samples were again distinctly separated from the yeast pellet, agar culture, and broth culture, reflecting notable differences in volatile compound profiles. The loading scatter plot of the polar column (Fig. 5D) revealed that the compounds contributed most significantly to the separation. Compounds such as ethyl 9-decenoate and acetic acid 2-ethylhexyl ester, which primarily contribute to PC2, were grouped as components predominantly detected in the yeast pellet. By contrast, phenylethyl alcohol, propanoic acid derivatives, and 1-butanol isomers were the major contributors to PC1 and were characterized as compounds mainly associated with agar culture. Overall, the PCA findings indicate that the yeast preparation method considerably influenced the volatile profiles of the yeast. Furthermore, the polarity of the GC column was effective in differentiating these volatiles, providing meaningful insights into the optimization of yeast-derived flavor profiles for specific applications.

Conclusion

Using GC-MS with non-polar, mid-polar, and polar columns, we profiled volatile compounds produced by S. cerevisiae cultivated as supernatant, broth, agar, and cell fractions. Our results showed that the supernatant exhibited the greatest diversity of volatile compounds, whereas the agar cultures and cell fractions led to fewer compounds, likely due to some volatiles remaining inside the cells or not diffusing easily onto the agar. Major compounds, including hexanoic acid ethyl ester, phenylethyl alcohol, and acetic acid 2-ethylhexyl ester, were detected at higher levels on the non-polar column, whereas benzaldehyde was more abundant on the polar column. The PCA results demonstrated distinct clustering of samples depending on the culture methods. We also evaluated different salts for salting-out extraction and observed that NaCl (35%) improved alcohol recovery, whereas H2NaPO4 (35%) enhanced acid extraction. These results indicate that changing the salt type and concentration can selectively enhance certain volatile compounds’ extraction efficiency. Overall, our findings demonstrated how the sample preparation method, column polarity, and extraction choice affect the detection of yeast-derived volatiles. These results can guide future studies and applications aimed at designing or customizing yeast-based flavors.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (PDF 538 KB) (538.6KB, pdf)

Acknowledgements

This research was supported by the Main Research Program of the Korea Food Research Institute (E0252802-01) funded by the Ministry of Science and ICT.

Author contribution

Nho-Eul Song: writing—original draft. Jeonghyun Yun: formal analysis, visualization. Sunhee Kang: resources, validation. Jang-Eun Lee: writing—review and editing, supervision.

Data availability

Data will be made available on request.

Declarations

Conflict of interest

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

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Supplementary Materials

Supplementary Material 1 (PDF 538 KB) (538.6KB, pdf)

Data Availability Statement

Data will be made available on request.

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