Antonie van Leeuwenhoek

, Volume 102, Issue 2, pp 247–255 | Cite as

Transcriptome analysis identifies genes involved in ethanol response of Saccharomyces cerevisiae in Agave tequilana juice

  • Jesús Ramirez-Córdova
  • Jenny Drnevich
  • Jaime Alberto Madrigal-Pulido
  • Javier Arrizon
  • Kirk Allen
  • Moisés Martínez-Velázquez
  • Ikuri Alvarez-Maya
Original Paper

Abstract

During ethanol fermentation, yeast cells are exposed to stress due to the accumulation of ethanol, cell growth is altered and the output of the target product is reduced. For Agave beverages, like tequila, no reports have been published on the global gene expression under ethanol stress. In this work, we used microarray analysis to identify Saccharomyces cerevisiae genes involved in the ethanol response. Gene expression of a tequila yeast strain of S. cerevisiae (AR5) was explored by comparing global gene expression with that of laboratory strain S288C, both after ethanol exposure. Additionally, we used two different culture conditions, cells grown in Agave tequilana juice as a natural fermentation media or grown in yeast-extract peptone dextrose as artificial media. Of the 6368 S. cerevisiae genes in the microarray, 657 genes were identified that had different expression responses to ethanol stress due to strain and/or media. A cluster of 28 genes was found over-expressed specifically in the AR5 tequila strain that could be involved in the adaptation to tequila yeast fermentation, 14 of which are unknown such as yor343c, ylr162w, ygr182c, ymr265c, yer053c-a or ydr415c. These could be the most suitable genes for transforming tequila yeast to increase ethanol tolerance in the tequila fermentation process. Other genes involved in response to stress (RFC4, TSA1, MLH1, PAU3, RAD53) or transport (CYB2, TIP20, QCR9) were expressed in the same cluster. Unknown genes could be good candidates for the development of recombinant yeasts with ethanol tolerance for use in industrial tequila fermentation.

Keywords

Saccharomyces cerevisiae Agave tequilana Ethanol stress DNA microarray Gene expression 

Abbreviations

YPD

Yeast peptone dextrose

ATJ

Agave tequilana juice

Notes

Acknowledgments

John Dye of Peace Corps México assisted with the revision of the article.

Conflict of interests

The authors declare that they have no competing interests.

References

  1. Aguilar-Uscanga B, Arrizon J, Ramírez J, Solis-Pacheco J (2007) Effect of Agave tequilana juice on cell wall polysaccharides of three Saccharomyces cerevisiae strains from different origins. Antonie Van Leeuwenhoek 91:151–157PubMedCrossRefGoogle Scholar
  2. Alexandre H, Rousseaux I, Charpentier C (1994) Relationship between ethanol tolerance, lipid composition and plasma membrane fluidity in Saccharomyces cerevisiae and Kloeckeraapiculata. FEMS Microbiol Lett 124:17–22PubMedCrossRefGoogle Scholar
  3. Alexandre H, Ansanay-Galeote V, Blondin S, Dequin S (2001) Global gene expression during short-term ethanol stress in Saccharomyces cerevisiae. FEBS Lett 498:98–103PubMedCrossRefGoogle Scholar
  4. Arrizon J, Gschaedler A (2007) Effects of the addition of different nitrogen sources in the tequila fermentation process at high sugar concentration. J Appl Microbiol 102:1123–1131PubMedGoogle Scholar
  5. Attfield PV (1997) Stress tolerance: the key to effective strains of industrial baker’s yeast. Nat Biotechnol 15(13):1351–1357PubMedCrossRefGoogle Scholar
  6. Auesukaree C, Damnernsawad A, Kruatrachue M, Pokethitiyook P, Boonchird C et al (2009) Genome-wide identification of genes involved in tolerance to various environmental stresses in Saccharomyces cerevisiae. J Appl Genet 50:301–310PubMedCrossRefGoogle Scholar
  7. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 57:289–300Google Scholar
  8. Betz C, Schlenstedt G, Bailer SM (2004) Asr1p, a novel yeast ring/PHD finger protein, signals alcohol stress to the nucleus. J Biol Chem 279:28174–28181PubMedCrossRefGoogle Scholar
  9. Causton HC, Ren B, Koh SS et al (2001) Remodeling of yeast genome expression in response to environmental changes. Mol Biol Cell 12:323–337PubMedGoogle Scholar
  10. Chandler M, Stanley GA, Rogers P, Chambers P (2004) A genomic approach to defining the ethanol stress response in the yeast Saccharomyces cerevisiae. Ann Microbiol 54:427–454Google Scholar
  11. Chi Z, Arneborg N (1999) Relationship between lipid composition, frequency of ethanol-induced respiratory deficient mutants, and ethanol tolerance in Saccharomyces cerevisiae. J Appl Microbiol 86:1047–1052PubMedCrossRefGoogle Scholar
  12. Del Castillo Agudo L, Nieto Soria A, Sentandreu R (1992) Differential expression of the invertase-encoding SUC genes in Saccharomyces cerevisiae. Gene 120(1):59–65CrossRefGoogle Scholar
  13. DeRisi JL, Iyer VR, Brown PO (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278:680–686PubMedCrossRefGoogle Scholar
  14. Eisen MB, Brown PO (1999) DNA arrays for analysis of gene expression. Methods Enzymol 303:179–205PubMedCrossRefGoogle Scholar
  15. Fujita K, Matsuyama A, Kobayashi Y, Iwahashi H (2006) The genome-wide screening of yeast deletion mutants to identify the genes required for tolerance to ethanol and other alcohols. FEMS Yeast Res 6:744–750PubMedCrossRefGoogle Scholar
  16. Gasch AP, Spellman PT, Kao CM, Carmel-Harel O, Eisen MB et al (2000) Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell 11:4241–4257PubMedGoogle Scholar
  17. Gibson BR, Lawrence SJ, Leclaire JP, Powell CD, Smart KA (2007) Yeast responses to stresses associated with industrial brewery handling. FEMS Microbiol Rev 31:535–569PubMedCrossRefGoogle Scholar
  18. Hohmann S, Mager WH (eds) (2003) Introduction. In: Topics in current genetics, vol 1, Yeast stress responses. Springer-Verlag, BerlinGoogle Scholar
  19. Köhrer K, Domdey H (1991) Preparation of high molecular weight RNA. Methods Enzymol 194:398–405PubMedCrossRefGoogle Scholar
  20. Kubota S, Takeo I, Kume K, Kanai M, Shitamukai A et al (2004) Effect of ethanol on cell growth of budding yeast: genes that are important for cell growth in the presence of ethanol. Biosci Biotechnol Biochem 68:968–972PubMedCrossRefGoogle Scholar
  21. Langfelder P, Zhang B (2008) Horvath S (2007) Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut library for R. Bioinformatics 24(5):719–720PubMedCrossRefGoogle Scholar
  22. Ma M, Liu ZL (2010) Mechanisms of ethanol tolerance in Saccharomyces cerevisiae. Appl Microbiol Biotechnol 87:829–845PubMedCrossRefGoogle Scholar
  23. MacPherson S, Larochelle M, Turcotte B (2006) A fungal family of transcriptional regulators: the zinc cluster proteins. Microbiol Mol Biol Rev 70:583–604PubMedCrossRefGoogle Scholar
  24. Mancilla-Margalli N, Lopez MG (2002) Generation of Maillard compounds from inulin during thermal processing of Agave tequilana blue variety. J Agric Food Chem 50:806–812PubMedCrossRefGoogle Scholar
  25. Marks VD, Ho Sui SJ, Erasmus D, van der Merwe GK, Brumm J et al (2008) Dynamics of the yeast transcriptome during wine fermentation reveals a novel fermentation stress response. FEMS Yeast Res 8:35–52PubMedCrossRefGoogle Scholar
  26. Ogawa Y, Nitta A, Uchiyama H, Imamura T, Shiomoi H et al (2000) Tolerance mechanism of the ethanol-tolerant mutant of sake yeast. J Biosci Bioeng 90:313–320PubMedGoogle Scholar
  27. R Development Core Team (2008) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0Google Scholar
  28. Ritchie ME, Silver J, Oshlack A, Silver J, Holmes M, Diyagama D, Holloway A, Smyth GK (2007) A comparison of background correction methods for two-colour microarrays. Bioinformatics 23:2700–2707PubMedCrossRefGoogle Scholar
  29. Rossignol T, Dulau L, Julien A, Blondin B (2003) Genome-wide monitoring of wine yeast gene expression during alcoholic fermentation. Yeast 20:1369–1385PubMedCrossRefGoogle Scholar
  30. Smyth GK (2004) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3(1) article 3Google Scholar
  31. Smyth GK (2005) Limma: linear models for microarray data. In: Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W (eds) Bioinformatics and computational biology solutions using R and bioconductor. Springer, New York, pp 397–420CrossRefGoogle Scholar
  32. Smyth GK, Speed TP (2003) Normalization of cDNA microarray data. Methods 31:265–273PubMedCrossRefGoogle Scholar
  33. Smyth GK, Michaud J, Scott H (2005) The use of within-array replicate spots for assessing differential expression in microarray experiments. Bioinformatics 21:2067–2075PubMedCrossRefGoogle Scholar
  34. Swan T, Watson K (1998) Stress tolerance in a yeast sterol auxotroph: role of ergosterol, heat shock proteins and trehalosa. FEMS Microbiol Lett 169:191–197PubMedCrossRefGoogle Scholar
  35. Takagi H, Takaoka M, Kawaguchi A, Kubo Y (2005) Trends in biotechnological production of fuel ethanol from different feedstocks. Appl Environ Microbiol 71(12):8656–8662PubMedCrossRefGoogle Scholar
  36. Teixeira MC, Raposo LR, Mira NP, Lourenço AB, Sá-Correia I (2009) Genome-wide identification of Saccharomyces cerevisiae genes required for maximal tolerance to ethanol. Appl Environ Microbiol 75(18):5761–5772Google Scholar
  37. Van Voorst F, Houghton-Larsen J, Jønson L, Kielland-Brandt MC, Brandt A (2006) Genome-wide identification of genes required for growth of Saccharomyces cerevisiae under ethanol stress. Yeast 23:351–359PubMedCrossRefGoogle Scholar
  38. Varela C, Cardenas J, Melo F, Agosin E (2005) Quantitative analysis of wine yeast gene expression profiles under winemaking conditions. Yeast 22(369):383Google Scholar
  39. Vianna CR, Silva CL, Neves MJ, Rosa CA (2008) Saccharomyces cerevisiae strains from traditional fermentations of Brazilian cachaca: trehalose metabolism, heat and ethanol resistance. Antonie Van Leeuwenhoek 93:205–217PubMedCrossRefGoogle Scholar
  40. Yoshikawa K, Tanaka T, Furusawa C, Nagahisa K, Hirasawa T et al (2009) Comprehensive phenotypic analysis for identification of genes affecting growth under ethanol stress in Saccharomyces cerevisiae. FEMS Yeast Res 9:32–44PubMedCrossRefGoogle Scholar
  41. You KM, Rosenfield CL, Knipple DC (2003) Ethanol tolerance in the yeast Saccharomyces cerevisiae is dependent on cellular oleic acid content. Appl Environ Microbiol 69:1499–1503PubMedCrossRefGoogle Scholar
  42. Zuzuarregui A, Monteoliva L, Gil C, Del Olmo M (2006) Transcriptomic and proteomic approach for understanding the molecular basis of adaptation of Saccharomyces cerevisiae to wine fermentation. Appl Environ Microbiol 72:836–847PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Jesús Ramirez-Córdova
    • 1
  • Jenny Drnevich
    • 2
  • Jaime Alberto Madrigal-Pulido
    • 1
  • Javier Arrizon
    • 3
  • Kirk Allen
    • 1
  • Moisés Martínez-Velázquez
    • 1
  • Ikuri Alvarez-Maya
    • 1
  1. 1.Medical and Pharmaceutical Biotechnology Unit, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco (CIATEJ)GuadalajaraMexico
  2. 2.The Roy J. Carver Biotechnology CenterUniversity of IllinoisUrbanaUSA
  3. 3.Industrial Biotechnology UnitCIATEJGuadalajaraMexico

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