Advertisement

Journal of Molecular Evolution

, Volume 86, Issue 2, pp 111–117 | Cite as

Beneficial Mutations from Evolution Experiments Increase Rates of Growth and Fermentation

  • Aysha L. Sezmis
  • Martino E. Malerba
  • Dustin J. Marshall
  • Michael J. McDonald
Original Article

Abstract

A major goal of evolutionary biology is to understand how beneficial mutations translate into increased fitness. Here, we study beneficial mutations that arise in experimental populations of yeast evolved in glucose-rich media. We find that fitness increases are caused by enhanced maximum growth rate (R) that come at the cost of reduced yield (K). We show that for some of these mutants, high R coincides with higher rates of ethanol secretion, suggesting that higher growth rates are due to an increased preference to utilize glucose through the fermentation pathway, instead of respiration. We examine the performance of mutants across gradients of glucose and nitrogen concentrations and show that the preference for fermentation over respiration is influenced by the availability of glucose and nitrogen. Overall, our data show that selection for high growth rates can lead to an enhanced Crabtree phenotype by the way of beneficial mutations that permit aerobic fermentation at a greater range of glucose concentrations.

Keywords

Beneficial mutations Fitness effects Experimental evolution Yeast Crabtree Trade-off 

Notes

Author Contributions

MJM conceived the study. ALS, MEM, DJM, and MJM designed the study. ALS and MJM conducted experiments. MEM and MJM analyzed the data. ALS, MEM, DJM, and MJM wrote the paper.

Funding

MJM was supported by ARC Grant No. FT170100441.

Compliance with Ethical Standards

Conflict of interest

We have no competing interests.

Supplementary material

239_2018_9829_MOESM1_ESM.pdf (373 kb)
Figure S1 Growth curve data for all mutant strains and the wild type in media containing 20 g/L glucose. The data from these growth curves were used to calculate values of R and K. X-axis displays time in 20-minute time intervals. A, all time point and all replicates, B, average growth curves. (PDF 372 KB)

References

  1. Bachmann H, Fischlechner M, Rabbers I, Barfa N, Branco dos Santos F, Molenaar D, Teusink B (2013) Availability of public goods shapes the evolution of competing metabolic strategies. Proc Natl Acad Sci USA 110:14302–14307.  https://doi.org/10.1073/pnas.1308523110 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Basan M, Hui S, Okano H, Zhang Z, Shen Y, Williamson JR, Hwa T (2015) Overflow metabolism in Escherichia coli results from efficient proteome allocation. Nature 528, 99–104.  https://doi.org/10.1038/nature15765 CrossRefPubMedPubMedCentralGoogle Scholar
  3. Bennett AF, Lenski RE (2007) An experimental test of evolutionary trade-offs during temperature adaptation. Proc Natl Acad Sci USA 104(Suppl 1):8649–8654.  https://doi.org/10.1073/pnas.0702117104 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Broach JR (2012) Nutritional control of growth and development in yeast. Genetics 192:73–105.  https://doi.org/10.1534/genetics.111.135731 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Crabtree HG (1929) Observations on the carbohydrate metabolism of tumours. Biochem J 23:536–545CrossRefPubMedPubMedCentralGoogle Scholar
  6. Crepin L, Nidelet T, Sanchez I, Dequin S, Camarasa C (2012) Sequential use of nitrogen compounds by Saccharomyces cerevisiae during wine fermentation: a model based on kinetic and regulation characteristics of nitrogen permeases. Appl Environ Microbiol 78:8102–8111.  https://doi.org/10.1128/AEM.02294-12 CrossRefPubMedPubMedCentralGoogle Scholar
  7. De Deken RH (1966) The Crabtree effect: a regulatory system in yeast. J Gen Microbiol 44:149–156.  https://doi.org/10.1099/00221287-44-2-149 CrossRefPubMedGoogle Scholar
  8. Frenkel EM, McDonald MJ, Van Dyken JD, Kosheleva K, Lang GI, Desai MM (2015) Crowded growth leads to the spontaneous evolution of semistable coexistence in laboratory yeast populations. Proc Natl Acad Sci USA.  https://doi.org/10.1073/pnas.1506184112 Google Scholar
  9. Giaever G, Chu AM, Ni L, Connelly C, Riles L, Veronneau S, Dow S, Lucau-Danila A, Anderson K, Andre B et al (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–391.  https://doi.org/10.1038/Nature00935 CrossRefPubMedGoogle Scholar
  10. Hagman A, Sall T, Piskur J (2014) Analysis of the yeast short-term Crabtree effect and its origin. FEBS J 281:4805–4814. ( https://doi.org/10.1111/febs.13019)CrossRefPubMedPubMedCentralGoogle Scholar
  11. Hammerschmidt K, Rose CJ, Kerr B, Rainey PB (2014) Life cycles, fitness decoupling and the evolution of multicellularity. Nature 515:75–79.  https://doi.org/10.1038/nature13884 CrossRefPubMedGoogle Scholar
  12. Jasmin JN, Dillon MM, Zeyl C (2012) The yield of experimental yeast populations declines during selection. Proc R Soc Lond B 279:4382–4388.  https://doi.org/10.1098/rspb.2012.1659 CrossRefGoogle Scholar
  13. Kryazhimskiy S, Rice DP, Jerison ER, Desai MM (2014) Microbial evolution. Global epistasis makes adaptation predictable despite sequence-level stochasticity. Science 344:1519–1522.  https://doi.org/10.1126/science.1250939 CrossRefPubMedPubMedCentralGoogle Scholar
  14. Lang GI, Desai MM (2014) The spectrum of adaptive mutations in experimental evolution. Genomics 104:412–416.  https://doi.org/10.1016/j.ygeno.2014.09.011 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Lang GI, Murray AW, Botstein D (2009) The cost of gene expression underlies a fitness trade-off in yeast. Proc Natl Acad Sci USA 106:5755–5760.  https://doi.org/10.1073/Pnas.0901620106 CrossRefPubMedPubMedCentralGoogle Scholar
  16. Lang GI, Botstein D, Desai MM (2011) Genetic variation and the fate of beneficial mutations in asexual populations. Genetics 188:647–661.  https://doi.org/10.1534/Genetics.111.128942 CrossRefPubMedPubMedCentralGoogle Scholar
  17. Lang GI, Rice DP, Hickman MJ, Sodergren E, Weinstock GM, Botstein D, Desai MM (2013) Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature 500:571–574.  https://doi.org/10.1038/nature12344 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Levy SF, Blundell JR, Venkataram S, Petrov DA, Fisher DS, Sherlock G (2015) Quantitative evolutionary dynamics using high-resolution lineage tracking. Nature 519, 181–186.  https://doi.org/10.1038/nature14279 CrossRefPubMedPubMedCentralGoogle Scholar
  19. Luckinbill LS (1978) r and K selection in experimental populations of Escherichia coli. Science 202, 1201–1203.  https://doi.org/10.1126/science.202.4373.1201 CrossRefPubMedGoogle Scholar
  20. McDonald MJ, Rice DP, Desai MM (2016) Sex speeds adaptation by altering the dynamics of molecular evolution. Nature 531:233–236.  https://doi.org/10.1038/nature17143 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Meyer JR, Dobias DT, Weitz JS, Barrick JE, Quick RT, Lenski RE (2012) Repeatability and contingency in the evolution of a key innovation in phage lambda. Science 335:428–432.  https://doi.org/10.1126/Science.1214449 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Novak M, Pfeiffer T, Lenski RE, Sauer U, Bonhoeffer S (2006) Experimental tests for an evolutionary trade-off between growth rate and yield in E. coli. Am Nat 168:242–251.  https://doi.org/10.1086/506527 PubMedGoogle Scholar
  23. Otterstedt K, Larsson C, Bill RM, Stahlberg A, Boles E, Hohmann S, Gustafsson L (2004) Switching the mode of metabolism in the yeast Saccharomyces cerevisiae. EMBO Rep 5:532–537.  https://doi.org/10.1038/sj.embor.7400132 CrossRefPubMedPubMedCentralGoogle Scholar
  24. Pfeiffer T, Morley A (2014) An evolutionary perspective on the Crabtree effect. Front Mol Biosci 1:17.  https://doi.org/10.3389/fmolb.2014.00017 CrossRefPubMedPubMedCentralGoogle Scholar
  25. Pfeiffer T, Schuster S, Bonhoeffer S (2001) Cooperation and competition in the evolution of ATP-producing pathways. Science 292:504–507.  https://doi.org/10.1126/science.1058079 CrossRefPubMedGoogle Scholar
  26. Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2016) Linear and nonlinear mixed effects models. (R package version). 3:1–89Google Scholar
  27. Pronk JT (2002) Auxotrophic yeast strains in fundamental and applied research. Appl Environ Microbiol 68:2095–2100CrossRefPubMedPubMedCentralGoogle Scholar
  28. R Development Core Team (2016) A language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  29. Reznick D, Bryant MJ Bashey F (2002) r- and K- selection revisted: the role of population regulation in life history evolution. Ecology 83, 1509–1520. ( https://doi.org/10.2307/3071970)CrossRefGoogle Scholar
  30. Roemer T, Bussey H (1991) Yeast beta-glucan synthesis: KRE6 encodes a predicted type II membrane protein required for glucan synthesis in vivo and for glucan synthase activity in vitro. Proc Natl Acad Sci USA 88:11295–11299CrossRefPubMedPubMedCentralGoogle Scholar
  31. Taylor TB, Mulley G, Dills AH, Alsohim AS, McGuffin LJ, Studholme DJ, Silby MW, Brockhurst MA, Johnson LJ, Jackson RW (2015) Evolution. Evolutionary resurrection of flagellar motility via rewiring of the nitrogen regulation system. Science 347, 1014–1017.  https://doi.org/10.1126/science.1259145 CrossRefPubMedGoogle Scholar
  32. van Gulik WM, Heijnen JJ (1995) A metabolic network stoichiometry analysis of microbial growth and product formation. Biotechnol Bioeng 48:681–698.  https://doi.org/10.1002/bit.260480617 CrossRefPubMedGoogle Scholar
  33. Venkataram S, Dunn B, Li Y, Agarwala A, Chang J, Ebel ER, Geiler-Samerotte K, Herissant L, Blundell JR, Levy SF et al (2016) Development of a comprehensive genotype-to-fitness map of adaptation-driving mutations in yeast. Cell 166, 1585–1596.  https://doi.org/10.1016/j.cell.2016.08.002 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Verduyn C, Zomerdijk TPL, van Dijken JP, Scheffers WA (1984) Continuous measurement of ethanol production by aerobic yeast suspensions with an enzyme electrode. Appl Microbiol Biotechnol 19:181–185.  https://doi.org/10.1007/bf00256451 CrossRefGoogle Scholar
  35. Verduyn C, Stouthamer AH, Scheffers WA, van Dijken JP (1991) A theoretical evaluation of growth yields of yeasts. Antonie Van Leeuwenhoek 59:49–63CrossRefPubMedGoogle Scholar
  36. Walker JRL (1992) Spectrophotometric determination of enzyme-activity : alcohol-dehydrogenase (Adh). Biochem Educ 20:42–43.  https://doi.org/10.1016/0307-4412(92)90021-D CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Centre for Geometric Biology, School of Biological SciencesMonash UniversityClaytonAustralia

Personalised recommendations