Advertisement

Yeast Genome Screening and Methods for the Discovery of Metabolic Pathways Involved in a Phenotypic Response to Anticancer Agents

  • Magdalena Cal
  • Irwin Matyjaszczyk
  • Stanisław UłaszewskiEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2049)

Abstract

The dramatic increase of cancer in the world drives the search for a new generation of drugs useful in effective and safe chemotherapy. In the postgenomic era the use of the yeast Saccharomyces cerevisiae as a simple eukaryotic model is required in molecular studies of biological activity of compounds that may be potential drugs in the future. The phenotype analysis of numerous deletion mutants (from the EUROSCARF collection) allows one to define the specific influence of tested compound on metabolism, stress generation and response of eukaryotic cell to stress. Moreover, it allows one to determine cell viability, design of new drugs and doses used in preclinical and clinical trials. Undoubtedly, this is also a good way to save the lives of many laboratory animals. Here we present a simple and cheap new approach to study the metabolic and stress response pathways in eukaryotic cells involved in the response to tested compounds (e.g., anticancer agents). The precise determination of biological activity mechanisms of tested compounds at the molecular level can contribute to the fast introduction of new cancer therapies, which is extremely important nowadays.

Key words

Saccharomyces cerevisiae Energy metabolism Genome screen Methods Yeast deletion mutants Anticancer agents 

References

  1. 1.
    Oliver SG, Van der Aart QJM, Agostoni-Carbone ML et al (1992) The complete DNA sequence of yeast chromosome III. Nature 357:38–46CrossRefGoogle Scholar
  2. 2.
    Richardson SM, Mitchell LA, Stracquadanio G et al (2017) Design of a synthetic yeast genome. Science 355:1040–1044CrossRefGoogle Scholar
  3. 3.
    Bharucha N, Kumar A (2007) Yeast genomics and drug target identification. Comb Chem High Throughput Screen 10:618–634CrossRefGoogle Scholar
  4. 4.
    Goffeau A, Barrell BG, Bussey H et al (1996) Life with 6000 genes. Science 274:546,563–546,567CrossRefGoogle Scholar
  5. 5.
    Dolinski K, Ball CA, Chervitz SA et al (1998) Expanding yeast knowledge online. Yeast 14:1453–1469CrossRefGoogle Scholar
  6. 6.
    Davenport M (2015) Tapping Yeast’s genome. Chem Eng News 93:8–13Google Scholar
  7. 7.
    Lis P, Jurkiewicz P, Cal-Bakowska M et al (2016) Screening the yeast genome for energetic metabolism pathways involved in a phenotypic response to the anti-cancer agent 3-bromopyruvate. Oncotarget 7:10153–10173CrossRefGoogle Scholar
  8. 8.
    Hammer SK, Avalos JL (2017) Harnessing yeast organelles for metabolic engineering. Nat Chem Biol 8:823–832CrossRefGoogle Scholar
  9. 9.
    Rabilloud TH (ed) (2000) Proteome research: two-dimensional gel electrophoresis and identification methods. Springer, Berlin, HeidelbergGoogle Scholar
  10. 10.
    Nielsen J, Jewett MC (eds) (2007) Metabolomics. A powerful tool in systems biology. Springer, Berlin, HeidelbergGoogle Scholar
  11. 11.
    Atkin AL (2011) Yeast bioinformatics and strain engineering resources. Methods Mol Biol 765:173–187CrossRefGoogle Scholar
  12. 12.
    Rieger J, Kaniak A, Jean-Yves Coppée JY et al (1997) Large-scale phenotypic analysis—the pilot project on yeast chromosome III. Yeast 13:1547–1562CrossRefGoogle Scholar
  13. 13.
    Karathia H, Vilaprinyo E, Sorribas A et al (2011) Saccharomyces cerevisiae as a model organism: a comparative study. PLoS One 6:e16015CrossRefGoogle Scholar
  14. 14.
    Tenreiro S, Fleming Outeiro T (2010) Simple is good: yeast models of neurodegeneration. FEMS Yeast Res 10:970–979CrossRefGoogle Scholar
  15. 15.
    Matuo R, Sousa FG, Soares DG et al (2012) Saccharomyces cerevisiae as a model system to study the response to anticancer agents. Cancer Chemother Pharmacol 70:491–502CrossRefGoogle Scholar
  16. 16.
    Hartwell LH, Szankasi P, Roberts CJ et al (1997) Integrating genetic approaches into the discovery of anticancer drugs. Science 278:1064–1068CrossRefGoogle Scholar
  17. 17.
    Winzeler EA, Shoemaker DD, Astromoff A et al (1999) Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285:901–906CrossRefGoogle Scholar
  18. 18.
    Amberg DC, Burke DJ, Strathern JN (2005) Methods in yeast genetics: a cold spring harbor laboratory course manual. John Inglis, Cold Spring Harbor Laboratory Press, New YorkGoogle Scholar
  19. 19.
    De la Torre-Ruiz MA, Pujol N, Sundaran V (2015) Coping with oxidative stress. The yeast model. Curr Drug Targets 16:2–12CrossRefGoogle Scholar
  20. 20.
    Niedźwiecka K, Dyląg M, Augustyniak D et al (2016) Glutathione may have implications in the design of 3-bromopyruvate treatment protocols for both fungal and algal infections as well as multiple myeloma. Oncotarget 7:65614–65626CrossRefGoogle Scholar
  21. 21.
    Lis P, Zarzycki M, Ko YH et al (2012) Transport and cytotoxicity of the anticancer drug 3-bromopyruvate in the yeast Saccharomyces cerevisiae. J Bioenerg Biomembr 44:155–161CrossRefGoogle Scholar
  22. 22.
    Majkowska-Skrobek G, Augustyniak D, Lis P et al (2014) Killing multiple myeloma cells with the small molecule 3-bromopyruvate: implications for therapy. Anti-Cancer Drugs 25:673–682PubMedGoogle Scholar
  23. 23.
    Pedersen PL, Mathupala S, Rempel A et al (2002) Mitochondrial bound type II hexokinase: a key player in the growth and survival of many cancers and an ideal prospect for therapeutic intervention. Biochim Biophys Acta 1555:14–20CrossRefGoogle Scholar
  24. 24.
    Diaz-Ruiz R, Uribe-Carvajal S, Devin A et al (2009) Tumor cell energy metabolism and its common features with yeast metabolism. Biochim Biophys Acta 1796:252–265PubMedGoogle Scholar
  25. 25.
    Coutinho I, Pereira G, Leão M et al (2009) Differential regulation of p53 function by protein kinase C isoforms revealed by a yeast cell system. FEBS Lett 583:3582–3588CrossRefGoogle Scholar
  26. 26.
    Diaz-Ruiz R, Rigoulet M, Devin A (2011) The Warburg and Crabtree effects: on the origin of cancer cell energy metabolism and of yeast glucose repression. Biochim Biophys Acta 1807:568–576CrossRefGoogle Scholar
  27. 27.
    Burz C, Berindan-Neagoe I, Balacescu O et al (2009) Apoptosis in cancer: key molecular signaling pathways and therapy targets. Acta Oncol 48:811–821CrossRefGoogle Scholar
  28. 28.
    Ko YH, Smith BL, Wang Y et al (2004) Advanced cancers: eradication in all cases using 3-bromopyruvate therapy to deplete ATP. Biochem Biophys Res Commun 324:269–275CrossRefGoogle Scholar
  29. 29.
    Pedersen PL (2012) 3-Bromopyruvate (3BP) a fast acting, promising, powerful, specific, and effective “small molecule” anti-cancer agent taken from labside to bedside: introduction to a special issue. J Bioenerg Biomembr 44:1–6CrossRefGoogle Scholar
  30. 30.
    Pedersen PL (2012) Mitochondria in relation to cancer metastasis: introduction to a mini-review series. J Bioenerg Biomembr 44:615–617CrossRefGoogle Scholar
  31. 31.
    Lis P, Dyląg M, Niedźwiecka K et al (2016) The HK2 dependent “Warburg effect” and mitochondrial oxidative phosphorylation in cancer:targets for effective therapy with 3-Bromopyruvate. Molecules 21:1–15CrossRefGoogle Scholar
  32. 32.
    Hartwell LH (2004) Yeast and cancer. Biosci Rep 24:523–544CrossRefGoogle Scholar
  33. 33.
    Ko YH, Verhoeven HA, Lee MJ et al (2012) A translational study “case report” on the small molecule “energy blocker” 3-bromopyruvate (3BP) as a potent anticancer agent: from bench side to bedside. J Bioenerg Biomembr 44:163–170CrossRefGoogle Scholar
  34. 34.
    Kimmich GA, Randles J, Brand JS (1975) Assay of picomole amounts of ATP, ADP and AMP using the luciferase enzyme system. Anal Biochem 69(1):187–206CrossRefGoogle Scholar
  35. 35.
    Cal-Bakowska M, Litwin I, Bocer T et al (2011) The Swi2-Snf2-like protein Uls1 is involved in replication stress response. Nucleic Acids Res 39:8765–8777CrossRefGoogle Scholar
  36. 36.
    Woodward JR, Cirillo VP, Edmunds LN Jr (1978) Light effects in yeast: inhibition by visible light of growth and transport in Saccharomyces cerevisiae grown at low temperatures. J Bacteriol 133:692–698PubMedPubMedCentralGoogle Scholar
  37. 37.
    Gregory R, Stuart Janine H, Santos Micheline K et al (2006) Mitochondrial and nuclear DNA defects in Saccharomyces cerevisiae with mutations in DNA polymerase γ associated with progressive external ophthalmoplegia. Hum Mol Genet 15:363–374CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Magdalena Cal
    • 1
  • Irwin Matyjaszczyk
    • 1
  • Stanisław Ułaszewski
    • 1
    Email author
  1. 1.Department of Genetics, Institute of Genetics and MicrobiologyUniversity of WroclawWroclawPoland

Personalised recommendations