Abstract
Background
Microbial metabolic engineering increasingly depends on identifying robust non-conventional yeast chassis with favorable metabolic traits. Although Saccharomyces cerevisiae remains the main model for isoprenoid engineering, alternative yeasts may provide superior native precursor availability. Here, we report the first comparative metabolomic characterization of Saccharomycopsis fibuligera, focusing on the mevalonate and terpenoid backbone biosynthesis pathways.
Results
LC-MS profiling revealed elevated levels of acetyl-CoA, HMG-CoA, and MVA in S. fibuligera, suggesting strong native flux through the MVA pathway. The universal isoprenoid precursors IPP and DMAPP accumulated at substantially higher levels than in S. cerevisiae, together with enrichment of FPP and ergosterol abundance, indicating efficient channeling toward sterol biosynthesis. Conversely, upper glycolysis metabolites were reduced, while TCA cycle intermediates were enriched, supporting the proposed Crabtree-negative phenotype of S. fibuligera. Amino acid profiling also indicated enhanced nitrogen storage capacity.
Conclusions
These results position S. fibuligera as a metabolically favorable platform with high intrinsic MVA pathway activity and precursor availability for terpenoid production, highlighting its strong potential as an emerging microbial chassis for next‑generation terpenoid bioproduction.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12866-026-05393-x.
Keywords: Saccharomycopsis fibuligera, Saccharomyces cerevisiae, Bioengineering, Metabolomics, Mevalonate, Terpenoids, Crabtree, Metabolic engineering
Background
Microorganisms have been exploited for millennia to produce value-added products, primarily in the food sector [1, 2]. Over the past century, their application has expanded substantially, leading into a “fermentation revolution” with several advances in metabolic engineering and synthetic biology (such as CRISPR/Cas9 edition) that have transformed microorganisms into versatile platforms to produce high-value chemicals. Among microbial platforms, yeast, particularly Saccharomyces cerevisiae has played a central role, transitioning from traditional fermentation such as beer and bread production to the biosynthesis of complex high-valued metabolites, like the artemisinin acid, a precursor to the artemisinin used for the treatment of malaria [3–5]. These advances have been driven by the fast progress of metabolic engineering and synthetic biology [6].
The demand for higher titers and lower-cost production of these metabolites, along with innovations in metabolic engineering, has brought new yeasts with highly potential as new microbial platforms such as Yarrowia lipolytica and Komagatella phaffii (formerly Pichia pastoris) [7]. Y. lipolytica is well known for its lipid accumulation capacity, which makes it an excellent platform to produce lipid-derived metabolites such as carotenoids, terpenes and fatty acids [8]. In contrast, K. phaffi is mostly used for heterologous proteins expression due to its efficient secretion system, high cell-density cultivation, and human-like glycosylation patterns [9].
In this study, we want to introduce Saccharomycopsis fibuligera (formerly Endomycopsis fibuligera) as a promising new yeast chassis for metabolic engineering. S. fibuligera is a teleomorph ascomycetous found worldwide in starchy substrates. It is a dimorphic yeast (yeast and pseudohyphal form) with amylolytic activity and elevated excretion of highly active enzymes. Among these enzymes, the most studied are α-amylase, β-glucosidase and acidic proteases. S. fibuligera can utilize diverse carbon sources, including glucose, sucrose, cellobiose, trehalose and soluble starch [10, 11], making it suitable for different by-products production.
Prior to the metabolic engineering era, S. fibuligera was identified as the most natural producer of mevalonate (MVA) among 1006 screened microorganism strains, 268 of which were yeasts [12, 13]. In 1969 and 1992, the yeast was patented for MVA production via fermentation [14, 15]. Mevalonate is a key precursor in the biosynthesis of terpenes and steroids, many of which are of high industrial value [16]. The elevated endogenous levels of this metabolite in S. fibuligera suppose an active MVA pathway that could, potentially, serve as a backbone to produce high-valuable metabolites by metabolic engineering.
Given the lack of information on the metabolome of S. fibuligera, we set out to validate this hypothesis by applying liquid chromatography-mass spectrometry (LC-MS) to quantify the main intermediates in the MVA-pathway and terpenoid biosynthesis. Moreover, we compared the relative abundance of several amino acids and derivatives, as well as the key energy generation intermediates between S. fibuligera and S. cerevisiae.
Together, these results provide the first metabolomic comparison between these two yeasts with a particular focus on the MVA pathway, offering new insights into the metabolic potential of S. fibuligera as a chassis for terpenoid bioproduction.
Methods
Strains and media
S. cerevisiae strain S288C and S. fibuligera strain NRRL Y-2388 were obtained from ATCC (Manassas, VA, USA). Both strains were cultured in the same conditions. Both strains were inoculated into fresh yeast extract peptone dextrose (YPD) medium (10% yeast extract, 20% peptone and 10% dextrose). All culture compounds were obtained from Sigma-Aldrich (Burlington, MA, USA). All cultures were incubated at 30 °C 250 rpm for 16 h in 14 mL Nunc™ Round-Bottom tube obtained from Thermo Fisher (Waltham, MA, USA) with 5 mL YPD.
Dry weighting and metabolite extraction
For cell extraction and dry weighting 1,5 mL of each culture (n = 5) were collected in a 2 mL centrifuge tube and centrifugated at 5000 g for 5 min. For S. fibuligera cultures a centrifugation at 8000 g for 5 min was needed to fully pellet the pseudo mycelium part. Supernatant was discarded, and the tubes for dry weighting were freezing at -80 °C followed by lyophilization and weighting. Moreover, cells were counted using a Neubauer chamber. Dry weight and cell number are indicated in Supplementary Table S1.
Before metabolite extraction, internal standards were added to the samples to control the extraction procedure and metabolite recovery. Then, metabolites were extracted from pellets using water: methanol (1:1) + 0,1% medronic acid, selected to enhance recovery of polar intracellular metabolites and to minimize the degradation of labile phosphorylated compounds. Cells were lysed by 3 cycles of freezing 1 min in liquid nitrogen and thawing in an ultrasonic bath for 2 min. Samples were kept in ice during the process to avoid metabolite degradation and enzymatic activity. Finally, samples were centrifuged at 15000x g for 10 min at 4 °C and the supernatant was transferred into chromatographic vials.
LC-MS/MS
Metabolomics analysis was carried out according to the methodology developed by Lopez-Barbera et al. [17]. Briefly, samples were injected into an UHPLC system equipped with a Poroshell 120 HILIC-Z column, 2.7 μm, 2.1 × 150 mm (Agilent Technologies, Palo Alto, CA, USA). Triple quadrupole mass spectrometer was used to obtain the relative quantification of metabolites, working in positive and negative ionization mode and acquiring data in multiple reaction monitoring (MRM) mode. Labeled internal standards were used to correct signal drift, matrix effect and sample preparation variability. Fragmentation pattern, retention time, collision energy and polarity for each metabolite are detailed in Supplementary Table S2.
Values for each metabolite were calculated using the internal standard response ratio to correct signal drift, metabolite extraction and recovery, and technical errors during sample manipulation. Results are shown in Supplementary Table S3.
Statistical analysis
Before statistical analysis, internal standard response ratio for each metabolite was normalized by dry mass to obtain comparable results. Statistically significant metabolites were assessed by performing the Mann-Whitney non-parametric test (p-value < 0.05) in Prism 9.5 (GraphPad, Boston, MA, USA). Fold-change and p-value for each metabolite is shown in Supplementary Table S3.
Results and discussion
Synthetic biology mainly focuses on the central pathway of interest. Nonetheless, during metabolic engineering, the fluxes of metabolic pathways can change substantially, leading to a “metabolic burden” that can compromise cell survival or limit culture growth [18]. Thus, it is essential to consider the broader context of cellular metabolism [19]. Isoprenoid production is dependent on the acetyl-CoA pool in the cell. Thus, glycolysis, energy generation in mitochondria, and other accessory pathways are important components to consider in the analysis. Alongside acting as a precursor in isoprenoid production, acetyl-CoA can be drained into the TCA cycle to produce energy and reducing agents, which are then utilized in the electron transfer chain (ETC) to increase energy production. In addition, several amino acid precursors are derived from, or feed into, the TCA cycle, linking nitrogen metabolism to central carbon metabolism [20].
In this article we present a metabolic comparison of only one strain per species (S. cerevisiae S288C and S. fibuligera NRRL Y-2388). Thus, the results should be interpreted as strain-specific rather than fully representative of each species. These strains were selected because they are well-characterized reference strains with good traceability across collections, facilitating reproducibility and interpretation. Nevertheless, strain-to-strain metabolic variability is well documented in yeasts, and future works including multiple isolates from each species will be necessary to determine how broadly the observed metabolic features apply across species-level diversity.”
Mevalonate pathway and terpenoid backbone biosynthesis pathway
The MVA pathway is ubiquitous in fungi [21], and has been widely engineered in S. cerevisiae to increase isoprenoid production [22–24]. However, in synthetic biology, the selection of microbial chassis is as important as the subsequent modifications [25]. For this purpose, we decided to compare the relative abundance of intermediates in the MVA pathway between S. fibuligera NRRL Y-2388 strain and the commonly used S. cerevisiae S288C strain.
Figure 1 shows the relative differences observed between S. fibuligera and S. cerevisiae in the main intermediates in MVA pathway and terpenoid biosynthesis (for exact numerical values, refers to Additional File 1, Table S3). Acetyl-CoA, the main precursor of MVA pathway [26] was detected at a 2.75-fold higher concentration in S. fibuligera compared with S. cerevisiae. This result is expected as previous studies about S. fibuligera and its ethanol production suggested the possibility of being a Crabtree-negative yeast or at least likely [27–29]. Therefore, more pyruvate can, virtually, be converted into acetyl-CoA for the TCA cycle than in S. cerevisiae.
Fig. 1.
Mevalonate pathway and terpenoid backbone biosynthesis pathway, indicating the fold-change (log2) in S. fibuligera respect S. cerevisiae of measured metabolites. Acetyl coenzyme A (acetyl-CoA), hydroxymethylglutaryl-CoA (HMG-CoA), mevalonate 5-phosphate (mevalonate-5P), mevalonate 5-pyrophosphate (mevalonate-5PP), isopentenyl pyrophosphate (IPP), dimethylallyl pyrophosphate (DMAPP), geranyl pyrophosphate (GPP), farnesyl pyrophosphate (FPP), geranylgeranyl pyrophosphate (GGPP)
The next important step in the pathway is the formation of 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) and its further reduction to MVA. Both metabolites were detected at a higher level in S. fibuligera, with 5.11-fold and 12.89-fold increases, respectively. This observation is consistent with previous reports describing elevated MVA production in S. fibuligera compared to other fungi, including S. cerevisiae and Yarrowia lipolytica, attributed to higher HMG-CoA reductase activity and lower mevalonate kinase activity [12]. In agreement with this hypothesis, mevalonate-5-phosphate (MVA-5P) was detected at 0.15-fold in S. fibuligera relative to S. cerevisiae. Despite this lower abundance of MVA-5P, downstream metabolites did not appear to be reduced, as the levels of dimethylallyl pyrophosphate (DMAPP) and its isomer isopentenyl pyrophosphate (IPP) were 11.92-fold higher in S. fibuligera. This may reflect a redistribution within the downstream pathway, where decreased MVA-5P levels could be associated with increased formation of DMAPP and IPP.
Considering that IPP and DMAPP are the main building blocks of isoprenoid biosynthesis [30], this elevated abundance suggests a strong potential of S. fibuligera for terpenoids bioproduction.
Further down in the terpenoid biosynthetic pathway, the combination of IPP and DMAPP enables yeast to produce a wide variety of terpenoids, which are classified according to the number of isoprene units and the corresponding precursor metabolites [30]. The main precursors are geranyl pyrophosphate (GPP), farnesyl pyrophosphate (FPP) and geranylgeranyl pyrophosphate (GGPP). GPP is formed by condensing DMAPP with IPP and is the precursor to monoterpenoids. FPP is formed by condensing GPP with IPP and is the precursor to sesquiterpenoids and triterpenoids. GGPP is formed by adding IPP to FPP and is the precursor of the rest of terpenoids [31, 32].
The conversion of IPP + DMAPP into GPP and the conversion of GPP + IPP into FPP are catalyzed by the same enzyme, the farnesyl diphosphate synthase (FPPS, encoded by gene ERG20) [33]. In S. cerevisiae GPP is rapidly converted into FPP (Chang et al., 2006), which is used for ubiquinone formation, ergosterol biosynthesis and protein prenylation. However, because the measured concentrations in S. fibuligera relative to S. cerevisiae of GPP and FPP were 0.24-fold and 49.9-fold, respectively, (Fig. 1), we can hypothesize a metabolic flux favoring the conversion of GPP into FPP in a higher extent in S. fibuligera compared to S. cerevisiae, suggesting a higher activity of FPPS in this conversion.
The Crabtree effect in S. cerevisiae results in the preferential conversion of glucose into ethanol even under aerobic conditions, reducing the flux through the TCA cycle and oxidative phosphorylation. This may result in the downregulation of the ETC, leading to a reduction of ubiquinone and, thus, higher concentration of GGPP [34]. However, S. fibuligera as a Crabtree-negative yeast, primarily relies on the TCA and ETC for energy generation, suggesting that lower concentrations of GGPP could be expected. Indeed, GGPP concentration in S. fibuligera was 0.16-fold relative to S. cerevisiae. In addition, concentration of ergosterol, a sterol derived from the triterpene squalene, was 4.7-fold higher, indicating an increase in sterol production from the pool of FPP (also increased as stated above) (Fig. 1).
Thus, the metabolic flux favoring the production of sterols suggests that S. fibuligera may represent a promising chassis for terpenoid production, especially for those derived from FPP, such as sesquiterpenoids and triterpenoids. Although, a priori, monoterpenoid and diterpenoid production seem not enhanced in the wild-type strain of S. fibuligera, with the optimal engineering design (such as inhibiting the production of FPP and/or enhancing the production of GPP) it could be a potential chassis for other terpenoids production due to the higher pool of precursors.
Energy generation and amino acid metabolism
Figure 2 shows the relative differences observed in the comparison between S. fibuligera and S. cerevisiae in metabolites associated with energy generation and amino acid metabolism (for exact numerical values, refer to Additional File 1, Table S3). Pyruvate, the final product of glycolysis, is a key metabolite that serves as the starting point for fermentation, a precursor for several amino acids, and an intermediate in coenzyme A biosynthesis [35]. Pyruvate was found at lower levels in S. fibuligera (0.56-fold relative to S. cerevisiae). In contrast, as mentioned previously, acetyl-CoA was present at higher levels (2.75-fold), as well as coenzyme A (3.80-fold). Further downstream in the TCA cycle, citrate was also detected at higher levels (4.89-fold) in S. fibuligera compared with S. cerevisiae. This high levels of citrate may reflect the Crabtree-negative metabolic phenotype proposed for S. fibuligera, in opposition to S. cerevisiae. Thus, S. fibuligera can be experiencing a drain of acetyl-CoA into the TCA and into its more active MVA pathway, explaining the lower concentration of pyruvate, as its conversion into acetyl-CoA is actively enhanced.
Fig. 2.
Energy generation and other accessory metabolic pathways such as amino acid metabolism, indicating the fold-change (log2) in S. fibuligera respect S. cerevisiae of measured metabolites
As mentioned before, some amino acid precursors are also obtained from, or used in, the TCA cycle. Amino acids also play a central role in cellular metabolism, acting as building blocks of proteins, precursors of nitrogen-containing compounds such as nucleotides, and potential sources of energy. In our study amino acids which are directly connected to the TCA cycle were detected at similar or lower levels in S. fibuligera compared with S. cerevisiae. For example, serine, which can be converted into pyruvate, showed a 0.78-fold change, while glutamate, which can be converted into α-ketoglutarate, was detected at 0.60-fold. Despite the lower abundance of glutamate, higher levels of proline (1.27-fold), arginine (1.86-fold), glutamine (6.33-fold), tryptophan (2-fold) and tyrosine (1.51-fold) were observed in S. fibuligera, which may be related to nitrogen storage or NAD+ biosynthesis [36–39]. This increase could also be linked to a greater availability of α-ketoglutarate, consistent with a more active TCA cycle in presence of a weak Crabtree effect. In contrast, lower concentrations of the branched-chain amino acids leucine and isoleucine were detected (0.81-fold and 0.63-fold, respectively), which may reflect their utilization in pathways contributing to acetyl-CoA production.
These results provide the first metabolomic insight into the central metabolism of S. fibuligera, highlighting metabolic features that may support its use as a chassis for terpenoid biosynthesis and future metabolic engineering strategies.
Conclusions
This study provides the first comprehensive metabolomic insight into S. fibuligera metabolic pathways, paving the bases for its use as a robust chassis in bioproduction. By comparing S. fibuligera with the traditional model S. cerevisiae, we demonstrate the metabolic potential of this non-conventional yeast to serve as a superior chassis for the production of high-value metabolites, particularly terpenoids.
Our experimental data suggests that S. fibuligera possesses a highly active MVA pathway. The native concentrations of the universal isoprenoid precursors IPP and DMAPP were found higher than those in S. cerevisiae. Furthermore, the presence of high FPP levels suggest that farnesyl diphosphate synthase in S. fibuligera is extremely efficient at converting precursors, making this yeast a promising candidate for the industrial production of sesquiterpenoids and triterpenoids.
In addition, the Crabtree-negative phenotype offers a physiological advantage for industrial bioprocessing. By preventing the diversion of carbon flux toward ethanol fermentation and ensuring a stable supply of precursors for the TCA and ETC, this phenotype reinforces the yeast’s ability to sustain complex synthetic routes.
Moreover, a robust nitrogen metabolism with a strong apparent capacity for nitrogen storage was observed, which is essential for cell growth and protein synthesis during intensive metabolic engineering.
Together, these results highlight S. fibuligera as a promising non-conventional yeast chassis for terpenoid bioproduction. However, the lack of optimized transformation protocols and genetic engineering tools for S. fibuligera greatly limits this yeast, at least for the time being, for its fully industrial capacity.
During this work, S. cerevisiae was used as the main strain to compare with S. fibuligera due to its dominant role in yeast-based isoprenoid engineering. However, since S. fibuligera appears to display a Crabtree-negative metabolic phenotype, future studies should include direct comparisons with respiratory non-conventional yeasts commonly used in industry, such as Komagataella phaffii and Yarrowia lipolytica. These comparisons would help determine whether the enhanced MVA pathway intermediates and terpenoid precursor availability observed in S. fibuligera are species-specific traits or are more broadly associated with Crabtree-negative yeast metabolism.
Furthermore, although complementary gene expression data would provide valuable insight into the regulation of terpenoid-related pathways in S. fibuligera, reliable transcriptomic interpretation is currently constrained by the limited functional annotation of the available genome. Future studies combining improved genome annotation, transcriptomics and metabolomics will be important to further elucidate the molecular basis of the metabolic phenotypes observed in the present study.
In conclusion, S. fibuligera has the potential to emerge as a natural highly efficient chassis for metabolic engineering in bioproduction processes. Its intrinsic ability to accumulate large amounts of mevalonate and downstream precursors, combined with its high energy efficiency and metabolic plasticity, suggests that S. fibuligera could be a valuable addition for the sustainable industrial production of terpenoids and other value-added bioproducts.
This work serves as a preliminary study highlighting the potential of this yeast. However, to unlock its industrial potential further research must be done.
Supplementary Information
Supplementary Material 1: Additional File 1. Includes dry weight and cell number of both cultures (Table S1); mass spectral data (Table S2); and mean, standard deviation, fold-change and p-value of metabolites in S. fibuligera respect S. cerevisiae (Table S3).
Acknowledgements
Authors acknowledge the support of the Vicente Lopez Fellowship by Fundació Eurecat granted to A.L.B.
Abbreviations
- CoA
Coenzyme A
- CRISPR/Cas9
Clustered regularly interspaced short palindromic repeats / CRISPR-associated protein 9
- DMAPP
Dimethylallyl pyrophosphate
- ETC
Electron transfer chain
- FC / Log₂FC
Fold-change / log₂ fold-change
- FPP
Farnesyl pyrophosphate
- FPPS
Farnesyl diphosphate synthase
- GGPP
Geranylgeranyl pyrophosphate
- GPP
Geranyl pyrophosphate
- HILIC-Z
Hydrophilic interaction liquid chromatography-zwitterionic column
- HMG-CoA
3-hydroxy-3-methylglutaryl-CoA
- IPP
Isopentenyl pyrophosphate
- LC-MS
Liquid chromatography-mass spectrometry
- LC-MS/MS
Liquid chromatography-tandem mass spectrometry
- MRM
Multiple reaction monitoring
- MVA
Mevalonic acid
- MVA-5P
Mevalonic acid 5-phosphate
- Mevalonate-5PP
Mevalonate 5-pyrophosphate
- NAD⁺
Nicotinamide adenine dinucleotide, oxidized form
- NRRL
Northern Regional Research Laboratory culture collection designation
- TCA
Tricarboxylic acid
- UHPLC
Ultra-high-performance liquid chromatography
- YPD
Yeast extract peptone dextrose
Authors’ contributions
A.L.B designed the study and perform the experiments; A.L.B and S.F.A. carried out the data analysis and statistics; S.F.A. performed the data curation and supervised the analytical performance; A.L.B. and S.F.A wrote the main manuscript, prepared the figures and the additional information; N.C., H.T. and N.A. help in the conceptualization and revision of the manuscript. H.T. and N.C. provided the funding acquisition and project administration; All authors reviewed and accepted the manuscript.
Funding
This work was supported by the Agència Catalana per la Competitivitat de l’Empresa [grant ACCIÓ-Eurecat TRAÇA 2023-FEREMIC] and the Agència de Gestió d’Ajuts Universitaris i de Recerca [SGR01275-IOMICS].
Data availability
Raw chromatogram data (.d format) are publicly available in BioStudies under accession number S-BSST3138 (https://www.ebi.ac.uk/biostudies/studies/S-BSST3138).
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
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
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material 1: Additional File 1. Includes dry weight and cell number of both cultures (Table S1); mass spectral data (Table S2); and mean, standard deviation, fold-change and p-value of metabolites in S. fibuligera respect S. cerevisiae (Table S3).
Data Availability Statement
Raw chromatogram data (.d format) are publicly available in BioStudies under accession number S-BSST3138 (https://www.ebi.ac.uk/biostudies/studies/S-BSST3138).