Comparative analysis of fermentation and enzyme expression profiles among industrial Saccharomyces cerevisiae strains

Abstract

Industrial diploid strains of Saccharomyces cerevisiae are selected from natural populations and then domesticated by optimizing the preferred properties for producing products such as bread, wine, and sake. In this study, for comparing the fermentation performance of various industrial yeasts, seven diploid strains of S. cerevisiae, namely, BY4947 (laboratory yeast derived from S288C), Kyokai7 and Kyokai9 (sake yeasts), Red Star and NBRC0555 (bread yeasts), and QA23 and EC1118 (wine yeasts), were cultivated in a synthetic medium. The fermentation profiles of the seven yeast strains showed significant differences. The specific ethanol production rates of sake yeasts (Kyokai7 and Kyokai9) and wine strains (QA23 and EC1118) were higher and lower than those of laboratory strains, respectively. Targeted proteome analysis was also conducted to investigate the variation in the expression of metabolism-related enzymes. The expression profiles of central metabolism-related enzymes showed considerable variations among the industrial strains. Upregulation of the TCA cycle in wine strains was observed both in the synthetic and grape-juice media. These results suggested that these variations should be consequences of complex interactions between the domestication process, genetic polymorphism, and environmental factors such as the fermentation conditions.

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References

  1. Akao T, Yashiro I, Hosoyama A, Kitagaki H, Horikawa H, Watanabe D, Akada R, Ando Y, Harashima S, Inoue T, Inoue Y, Kajiwara S, Kitamoto K, Kitamoto N, Kobayashi O, Kuhara S, Masubuchi T, Mizoguchi H, Nakao Y, Nakazato A, Namise M, Oba T, Ogata T, Ohta A, Sato M, Shibasaki S, Takatsume Y, Tanimoto S, Tsuboi H, Nishimura A, Yoda K, Ishikawa T, Iwashita K, Fujita N, Shimoi H (2011) Whole-genome sequencing of sake yeast Saccharomyces cerevisiae Kyokai no. 7. DNA Res 18(6):423–434. https://doi.org/10.1093/dnares/dsr029

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Almeida P, Barbosa R, Zalar P, Imanishi Y, Shimizu K, Turchetti B, Legras JL, Serra M, Dequin S, Couloux A, Guy J, Bensasson D, Goncalves P, Sampaio JP (2015) A population genomics insight into the Mediterranean origins of wine yeast domestication. Mol Ecol 24(21):5412–5427. https://doi.org/10.1111/mec.13341

    Article  PubMed  Google Scholar 

  3. Balakrishnan R, Park J, Karra K, Hitz BC, Binkley G, Hong EL, Sullivan J, Micklem G, Cherry JM (2012) YeastMine—an integrated data warehouse for Saccharomyces cerevisiae data as a multipurpose tool-kit. Database (Oxford) 2012:bar062. https://doi.org/10.1093/database/bar062

    Article  CAS  Google Scholar 

  4. Bereman MS, MacLean B, Tomazela DM, Liebler DC, MacCoss MJ (2012) The development of selected reaction monitoring methods for targeted proteomics via empirical refinement. Proteomics 12(8):1134–1141

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Bradford MM (1976) A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72:248–254

    Article  PubMed  CAS  Google Scholar 

  6. Camarasa C, Sanchez I, Brial P, Bigey F, Dequin S (2011) Phenotypic landscape of Saccharomyces cerevisiae during wine fermentation: evidence for origin-dependent metabolic traits. PLoS One 6(9):e25147. https://doi.org/10.1371/journal.pone.0025147

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Chidi BS, Rossouw D, Bauer FF (2016) Identifying and assessing the impact of wine acid-related genes in yeast. Curr Genet 62(1):149–164. https://doi.org/10.1007/s00294-015-0498-6

    Article  PubMed  CAS  Google Scholar 

  8. Costenoble R, Picotti P, Reiter L, Stallmach R, Heinemann M, Sauer U, Aebersold R (2011) Comprehensive quantitative analysis of central carbon and amino-acid metabolism in Saccharomyces cerevisiae under multiple conditions by targeted proteomics. Mol Syst Biol 7:464

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. de Godoy LM, Olsen JV, Cox J, Nielsen ML, Hubner NC, Frohlich F, Walther TC, Mann M (2008) Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast. Nature 455(7217):1251–1254. https://doi.org/10.1038/nature07341

    Article  PubMed  CAS  Google Scholar 

  10. Erasmus D, Cliff M, van Vuuren H (2004) Impact of yeast strain on the production of acetic acid, glycerol, and the sensory attributes of Icewine. Am J Enol Vitic 55:371–378

    CAS  Google Scholar 

  11. Gallone B, Steensels J, Prahl T, Soriaga L, Saels V, Herrera-Malaver B, Merlevede A, Roncoroni M, Voordeckers K, Miraglia L, Teiling C, Steffy B, Taylor M, Schwartz A, Richardson T, White C, Baele G, Maere S, Verstrepen KJ (2016) Domestication and divergence of Saccharomyces cerevisiae beer yeasts. Cell 166(6):1397–1410 e1316. https://doi.org/10.1016/j.cell.2016.08.020

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Ghaemmaghami S, Huh WK, Bower K, Howson RW, Belle A, Dephoure N, O’Shea EK, Weissman JS (2003) Global analysis of protein expression in yeast. Nature 425(6959):737–741. https://doi.org/10.1038/nature02046

    Article  PubMed  CAS  Google Scholar 

  13. Kamiie J, Ohtsuki S, Iwase R, Ohmine K, Katsukura Y, Yanai K, Sekine Y, Uchida Y, Ito S, Terasaki T (2008) Quantitative atlas of membrane transporter proteins: development and application of a highly sensitive simultaneous LC/MS/MS method combined with novel in-silico peptide selection criteria. Pharm Res 25(6):1469–1483

    Article  PubMed  CAS  Google Scholar 

  14. Kulak NA, Pichler G, Paron I, Nagaraj N, Mann M (2014) Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells. Nat Methods 11(3):319–324. https://doi.org/10.1038/nmeth.2834

    Article  PubMed  CAS  Google Scholar 

  15. Lambrechts M, Pretorius I (2000) Yeast and its importance in wine aroma—a review. S Afr J Eno Viti 21:97–129

    CAS  Google Scholar 

  16. Legras JL, Merdinoglu D, Cornuet JM, Karst F (2007) Bread, beer and wine: Saccharomyces cerevisiae diversity reflects human history. Mol Ecol 16(10):2091–2102. https://doi.org/10.1111/j.1365-294X.2007.03266.x

    Article  PubMed  CAS  Google Scholar 

  17. Lill R, Mühlenhoff U (2005) Iron-sulfur-protein biogenesis in eukaryotes. Trends Biochem Sci 30(3):133–141

    Article  PubMed  CAS  Google Scholar 

  18. Lu P, Vogel C, Wang R, Yao X, Marcotte EM (2007) Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat Biotechnol 25(1):117–124. https://doi.org/10.1038/nbt1270

    Article  PubMed  CAS  Google Scholar 

  19. MacLean B, Tomazela DM, Shulman N, Chambers M, Finney GL, Frewen B, Kern R, Tabb DL, Liebler DC, MacCoss MJ (2010) Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26(7):966–968

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Marsit S, Dequin S (2015) Diversity and adaptive evolution of Saccharomyces wine yeast: a review. FEMS Yeast Res 15(7):fov067. https://doi.org/10.1093/femsyr/fov067

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Marsit S, Leducq JB, Durand E, Marchant A, Filteau M, Landry CR (2017) Evolutionary biology through the lens of budding yeast comparative genomics. Nat Rev Genet 18(10):581–598. https://doi.org/10.1038/nrg.2017.49

    Article  PubMed  CAS  Google Scholar 

  22. Matsuda F, Ogura T, Tomita A, Hirano I, Shimizu H (2015) Nano-scale liquid chromatography coupled to tandem mass spectrometry using the multiple reaction monitoring mode based quantitative platform for analyzing multiple enzymes associated with central metabolic pathways of Saccharomyces cerevisiae using ultra fast mass spectrometry. J Biosci Bioeng 119(1):117–120

    Article  PubMed  CAS  Google Scholar 

  23. Matsuda F, Kinoshita S, Nishino S, Tomita A, Shimizu H (2017) Targeted proteome analysis of single-gene deletion strains of Saccharomyces cerevisiae lacking enzymes in the central carbon metabolism. PLoS One 12(2):e0172742

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Nasuno R, Aitoku M, Manago Y, Nishimura A, Sasano Y, Takagi H (2014) Nitric oxide-mediated antioxidative mechanism in yeast through the activation of the transcription factor Mac1. PLoS One 9(11):e113788. https://doi.org/10.1371/journal.pone.0113788

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Ohnuki S, Okada H, Friedrich A, Kanno Y, Goshima T, Hasuda H, Inahashi M, Okazaki N, Tamura H, Nakamura R, Hirata D, Fukuda H, Shimoi H, Kitamoto K, Watanabe D, Schacherer J, Akao T, Ohya Y (2017) Phenotypic diagnosis of lineage and differentiation during sake yeast breeding. G3 (Bethesda) 7(8):2807–2820. https://doi.org/10.1534/g3.117.044099

    Article  Google Scholar 

  26. Picotti P, Aebersold R (2012) Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat Methods 9(6):555–566. https://doi.org/10.1038/nmeth.2015

    Article  PubMed  CAS  Google Scholar 

  27. Picotti P, Lam H, Campbell D, Deutsch EW, Mirzaei H, Ranish J, Domon B, Aebersold R (2008) A database of mass spectrometric assays for the yeast proteome. Nat Methods 5(11):913–914

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Picotti P, Bodenmiller B, Mueller LN, Domon B, Aebersold R (2009) Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics. Cell 138(4):795–806

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Picotti P, Rinner O, Stallmach R, Dautel F, Farrah T, Domon B, Wenschuh H, Aebersold R (2010) High-throughput generation of selected reaction-monitoring assays for proteins and proteomes. Nat Methods 7(1):43–46

    Article  PubMed  CAS  Google Scholar 

  30. Rappsilber J, Mann M, Ishihama Y (2007) Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat Protoc 2(8):1896–1906

    Article  PubMed  CAS  Google Scholar 

  31. Richards AL, Hebert AS, Ulbrich A, Bailey DJ, Coughlin EE, Westphall MS, Coon JJ (2015) One-hour proteome analysis in yeast. Nat Protoc 10(5):701–714. https://doi.org/10.1038/nprot.2015.040

    Article  PubMed  CAS  Google Scholar 

  32. Rossignol T, Kobi D, Jacquet-Gutfreund L, Blondin B (2009) The proteome of a wine yeast strain during fermentation, correlation with the transcriptome. J Appl Microbiol 107(1):47–55. https://doi.org/10.1111/j.1365-2672.2009.04156.x

    Article  PubMed  CAS  Google Scholar 

  33. Rossouw D, Olivares-Hernandes R, Nielsen J, Bauer FF (2009) Comparative transcriptomic approach to investigate differences in wine yeast physiology and metabolism during fermentation. Appl Environ Microbiol 75(20):6600–6612. https://doi.org/10.1128/AEM.01251-09

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Rossouw D, van den Dool AH, Jacobson D, Bauer FF (2010) Comparative transcriptomic and proteomic profiling of industrial wine yeast strains. Appl Environ Microbiol 76(12):3911–3923. https://doi.org/10.1128/AEM.00586-10

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Salvado Z, Chiva R, Rodriguez-Vargas S, Randez-Gil F, Mas A, Guillamon JM (2008) Proteomic evolution of a wine yeast during the first hours of fermentation. FEMS Yeast Res 8(7):1137–1146. https://doi.org/10.1111/j.1567-1364.2008.00389.x

    Article  PubMed  CAS  Google Scholar 

  36. Sasano Y, Haitani Y, Ohtsu I, Shima J, Takagi H (2012) Proline accumulation in baker’s yeast enhances high-sucrose stress tolerance and fermentation ability in sweet dough. Int J Food Microbiol 152(1–2):40–43. https://doi.org/10.1016/j.ijfoodmicro.2011.10.004

    Article  PubMed  CAS  Google Scholar 

  37. Shima J, Takagi H (2009) Stress-tolerance of baker’s-yeast (Saccharomyces cerevisiae) cells: stress-protective molecules and genes involved in stress tolerance. Biotechnol Appl Biochem 53(Pt 3):155–164. https://doi.org/10.1042/BA20090029

    Article  PubMed  CAS  Google Scholar 

  38. Shimoi H, Sakamoto K, Okuda M, Atthi R, Iwashita K, Ito K (2002) The AWA1 gene is required for the foam-forming phenotype and cell surface hydrophobicity of sake yeast. Appl Environ Microbiol 68(4):2018–2025

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102(43):15545–15550. https://doi.org/10.1073/pnas.0506580102

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Sugimoto M, Koseki T, Hirayama A, Abe S, Sano T, Tomita M, Soga T (2010) Correlation between sensory evaluation scores of Japanese sake and metabolome profiles. J Agric Food Chem 58(1):374–383. https://doi.org/10.1021/jf903680d

    Article  PubMed  CAS  Google Scholar 

  41. Takagi H (2008) Proline as a stress protectant in yeast: physiological functions, metabolic regulations, and biotechnological applications. Appl Microbiol Biotechnol 81(2):211–223. https://doi.org/10.1007/s00253-008-1698-5

    Article  PubMed  CAS  Google Scholar 

  42. Uchida Y, Tachikawa M, Obuchi W, Hoshi Y, Tomioka Y, Ohtsuki S, Terasaki T (2013) A study protocol for quantitative targeted absolute proteomics (QTAP) by LC-MS/MS: application for inter-strain differences in protein expression levels of transporters, receptors, claudin-5, and marker proteins at the blood-brain barrier in ddY, FVB, and C57BL/6J mice. Fluids Barriers CNS 10(1):21

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Watanabe D, Araki Y, Zhou Y, Maeya N, Akao T, Shimoi H (2012) A loss-of-function mutation in the PAS kinase Rim15p is related to defective quiescence entry and high fermentation rates of Saccharomyces cerevisiae sake yeast strains. Appl Environ Microbiol 78(11):4008–4016. https://doi.org/10.1128/AEM.00165-12

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgments

We thank Prof. Yoshihiro Toya (Osaka University), Dr. Kenshi Hayakawa, Mr. Takuya Izumi (Kaneka corporation), Mr. Sho Katsuragi, and Mr. Kei Shimizu (SETI K.K.) for helpful comments on this manuscript and for supplying the yeast strains. We also thank Ms. Atsumi Tomita (Osaka University), Dr. Ichiro Hirano, and Dr. Taito Ogura (Shimadzu Co.) for technical support for the targeted proteome analysis.

Funding

This work was supported in part by Grants-in-Aid for Scientific Research (grant nos. 18K04851 and 17H06303).

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KU and FM executed the bench procedures. KU and FM performed the proteome analysis. KU, FM, and HS analyzed the data. KU, FM, and HS wrote the manuscript. FM and HS designed and supervised the overall of research project. All authors have read and approved the final version of the manuscript.

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Correspondence to Fumio Matsuda.

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The authors declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Uebayashi, K., Shimizu, H. & Matsuda, F. Comparative analysis of fermentation and enzyme expression profiles among industrial Saccharomyces cerevisiae strains. Appl Microbiol Biotechnol 102, 7071–7081 (2018). https://doi.org/10.1007/s00253-018-9128-9

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Keywords

  • Central carbon metabolism
  • Targeted proteomics
  • Saccharomyces cerevisiae
  • Industrial yeasts
  • Crabtree effect