Advertisement

Evolutionary Ecology

, Volume 21, Issue 4, pp 535–547 | Cite as

Resistance to glyphosate in the cyanobacterium Microcystis aeruginosa as result of pre-selective mutations

  • Victoria López-Rodas
  • Antonio Flores-Moya
  • Emilia Maneiro
  • Nieves Perdigones
  • Fernando Marva
  • Marta E. García
  • Eduardo Costas
Article

Abstract

Adaptation of Microcystis aeruginosa (Cyanobacteria) to resist the herbicide glyphosate was analysed by using an experimental model. Growth of wild-type, glyphosate-sensitive (Gs) cells was inhibited when they were cultured with 120 ppm glyphosate, but after further incubation for several weeks, occasionally the growth of rare cells resistant (Gr) to the herbicide was found. A fluctuation analysis was carried out to distinguish between resistant cells arising from rare spontaneous mutations and resistant cells arising from other mechanisms of adaptation. Resistant cells arose by rare spontaneous mutations prior to the addition of glyphosate, with a rate ranging from 3.1 × 10−7 to 3.6 × 10−7 mutants per cell per generation in two strains of M. aeruginosa; the frequency of the Gr allele ranged from 6.14 × 10−4 to 6.54 × 10−4. The Gr mutants are slightly elliptical in outline, whereas the Gs cells are spherical. Since Gr mutants have a diminished growth rate, they may be maintained in uncontaminated waters as the result of a balance between new resistants arising from spontaneous mutation and resistants eliminated by natural selection. Thus, rare spontaneous pre-selective mutations may allow the survival of M. aeruginosa in glyphosate-polluted waters via Gr clone selection.

Keywords

Cell morphology Glyphosate Microcystis Mutation rate Natural selection 

Abbreviations and symbols

CF

Coefficient of form

Gr

Glyphosate-resistant cells

Gs

Glyphosate-sensitive cells

\( m_{{\text{G}}^{\text{r}} } \)

Malthusian fitness parameter from glyphosate-resistant cells

\( m_{{\text{G}}^{\text{s}} } \)

Malthusian fitness parameter from glyphosate-sensitive cells

N0

No. of cells at the start of the experiment

Nt

No. of cells at the end of the experiment

P0

Proportion of cultures without Gr cells in the set 1 fluctuation analysis experiment

q

Frequency of Gr allele in natural, non-exposed to glyphosate populations

s

Coefficient of selection

μ

Mutation rate

Notes

Acknowledgements

This work was financially supported by REN 2000-0771 HID, REN 2001-1211 HID, Parques Nacionales 093/2003, P05-RNM-00935 and DOÑANA-2005 grants. Dr. Eric C. Henry (Herbarium, Department of Botany and Plant Pathology, Oregon State University, USA) kindly revised the English style and usage.

References

  1. Ayala FJ, Kiger JA Jr (1980) Modern genetics. The Benjamins/Cummings Publishing Company, Menlo Park, CA, USAGoogle Scholar
  2. Bañares-España E, López-Rodas V, Salgado C, Costas E, Flores-Moya A (2006) Inter-strain variability in the photosynthetic use of inorganic carbon, exemplified by the pH compensation point, in the cyanobacterium Microcystis aeruginosa. Aquat Bot 85:159–162CrossRefGoogle Scholar
  3. Baos R, García-Villada L, Agrelo M, López-Rodas V, Hiraldo F, Costas E (2002) Short-term adaptation of microalgae in highly stressful environments: an experimental model analysing the resistance of Scenedesmus intermedius (Chlorophyceae) to the heavy metals mixture from the Aznalcóllar mine spill. Eur J Phycol 37:593–600CrossRefGoogle Scholar
  4. Baucom RS, Mauricio R (2004) Fitness costs and benefits of novel herbicide tolerance in a noxious weed. Proc Natl Acad Sci USA 101:13386–13390PubMedCrossRefGoogle Scholar
  5. Belfiore NM, Anderson SL (2001) Effects of contaminants on genetic patterns in aquatic organisms: a review. Mutat Res 489:97–122PubMedCrossRefGoogle Scholar
  6. Bradshaw AD, Hardwick K (1989) Evolution and stress—genotype and phenotype components. Biol J Linn Soc 37:137–155CrossRefGoogle Scholar
  7. British Standards Institute (1979) Precision of test methods. I. Guide for the determination of repeatability and reproducibility for a standard test method for inter-laboratory tests. BS 5497. Part I. British Standards Institute, London, UKGoogle Scholar
  8. Cairns J, Overbaugh J, Miller S (1998) The origin of mutants. Nature 335:142–145CrossRefGoogle Scholar
  9. Carrillo E, Ferrero LM, Alonso-Andicoberry C, Basanta A, Martín A, López-Rodas V, Costas E (2003) Interstrain variability in toxin production in populations of the cyanobacterium Microcystis aeruginosa from water-supply reservoirs of Andalusia and lagoons of Doñana National Park (southern Spain). Phycologia 42:269–274CrossRefGoogle Scholar
  10. Costas E, Carrillo E, Ferrero LM, Agrelo M, García-Villada L, Juste J, López-Rodas V (2001) Mutation of algae from sensitivity to resistance against environmental selective agents: the ecological genetics of Dictyosphaerium chlorelloides (Chlorophyceae) under lethal doses of 3-(3,4-dichlorophenyl)-1,1-dimethylurea herbicide. Phycologia 40:391–398CrossRefGoogle Scholar
  11. Coustau C, Chevillon C, Ffrench-Constant R (2000) Resistance to xenobiotics and parasites: can we count the cost? Trends Ecol Evol 15:378–383CrossRefPubMedGoogle Scholar
  12. Crow JF, Kimura M (1970) An introduction to population genetics theory. Harper and Row, New York, NY, USAGoogle Scholar
  13. Falkowski PG, Raven JA, (1997) Aquatic photosynthesis. Blackwell Science, Malden, MA, USAGoogle Scholar
  14. Flores-Moya A, Costas E, Bañares-España E, García-Villada L, Altamirano M, López-Rodas V (2005) Adaptation of Spirogyra insignis (Chlorophyta) to an extreme natural environment (sulphureous waters) through preselective mutations. New Phytol 165:655–661CrossRefGoogle Scholar
  15. Foster PL (2000) Adaptive mutation: implications for evolution. BioEssays 22:1067–1074PubMedCrossRefGoogle Scholar
  16. García-Villada L, López-Rodas V, Bañares-España E, Flores-Moya A, Agrelo M, Martín-Otero L, Costas E (2002) Evolution of microalgae in highly stressing environments: an experimental model analyzing the rapid adaptation of Dictyosphaerium chlorelloides (Chlorophyceae) from sensitivity to resistance against 2,4,6-trinitrotoluene by rare preselective mutations. J Phycol 38:1074–1081CrossRefGoogle Scholar
  17. García-Villada L, Rico M, Altamirano M, Sánchez-Martín L, López-Rodas V, Costas E (2004) Occurrence of copper resistant mutants in the toxic cyanobacterium Microcystis aeruginosa: characterization and future implications in the use of copper sulphate as an algaecide. Water Res 38:2207–2213PubMedCrossRefGoogle Scholar
  18. Goyanes VJ, Ron-Corzo A, Costas E, Maneiro E (1990) Morphometric categorization of human oocyte and early conceptus. Hum Reprod 5:613–618PubMedGoogle Scholar
  19. Huxley J (1942) Evolution: the modern synthesis. Harper, New York, NY, USAGoogle Scholar
  20. Junghans M, Backhaus T, Faust M, Scholze M, Grimme LH, (2006) Application and validation of approaches for the predictive hazard assessment of realistic pesticide mixtures. Aquat Toxicol 76:93–110PubMedCrossRefGoogle Scholar
  21. Kirk JTO (1994) Light and photosynthesis in aquatic ecosystems, 2nd edn. Cambridge University Press, New York, NY, USAGoogle Scholar
  22. Koenig F (2001) Eukaryotic Algae, Cyanobacteria and Pesticides. In: Rai LC, Gaur JP (eds) Algal adaptation to environmental stresses. Physiological, biochemical and molecular mechanisms, Springer, Berlin, Germany, pp 389–406Google Scholar
  23. Lewontin RC, (1974) The genetic basis of evolutionary change. Columbia University Press, New York, NY, USAGoogle Scholar
  24. López-Rodas V, Agrelo M, Carrillo E, Ferrero LM, Larrauri A, Martín-Otero L, Costas E (2001) Resistance of microalgae to modern water contaminants as the result of rare spontaneous mutations. Eur J Phycol 36:179–190CrossRefGoogle Scholar
  25. López-Rodas V, Costas E, Bañares-España E, García-Villada L, Altamirano M, Rico M, Salgado C, Flores-Moya A (2006) Analysis of polygenic traits of Microcystis aeruginosa (Cyanobacteria) strains by Restricted Maximum Likelihood (REML) procedures: 2. Microcystin net production, photosynthesis and respiration. Phycologia 45:243–248CrossRefGoogle Scholar
  26. Luria SE, Delbrück M (1943) Mutations of bacteria from virus sensitivity to virus resistance. Genetics 28:491–511PubMedGoogle Scholar
  27. Margulis L, Schwartz KV, (1982) Five kingdoms. An illustrated guide to the phyla of life on earth. W. H. Freeman, San Francisco, CA, USAGoogle Scholar
  28. Myers N, Knoll AH (2001) The biotic crisis and the future of evolution. Proc Natl Acad Sci USA 98:5389–5392PubMedCrossRefGoogle Scholar
  29. Palumbi SR (2001) Humans as world’s greatest evolutionary force. Science 293:1786–1790PubMedCrossRefGoogle Scholar
  30. Renau-Piqueras J, Gómez-Perretta C, Guerri C, Sanchis R (1985) Qualitative and quantitative ultrastructural alterations in hepatocytes of rats prenatally exposed to ethanol with special reference to mitochondria, golgi apparatus and peroxisomes. Virchows Arch 405:237–251CrossRefGoogle Scholar
  31. Rico M, Altamirano M, López-Rodas V, Costas E (2006) Analysis of polygenic traits of Microcystis aeruginosa (Cyanobacteria) strains by Restricted Maximum Likelihood (REML) procedures: 1. Size and shape of colonies and cells. Phycologia 45:237–242CrossRefGoogle Scholar
  32. Rosche WA, Foster PL, (2000) Determining mutation rates in bacterial populations. Methods 20:4–17PubMedCrossRefGoogle Scholar
  33. Skulberg OM, Carmichael WW, Codd GA, Skulberg R (1993) Toxigenic cyanophytes identification and taxonomy. In: Falconer IR (ed) Algal toxins in seafood and drinking water, Academic Press, London, pp. 145–164Google Scholar
  34. Sniegowski PD (2005) Linking mutation to adaptation: overcoming stress at the spa. New Phytol. 166:360–362PubMedCrossRefGoogle Scholar
  35. Sniegowski PD, Lenski RE (1995) Mutation and adaptation: The directed mutation controversy in evolutionary perspective. Annu Rev Ecol Syst 26:553–578CrossRefGoogle Scholar
  36. Spiess EB (1989) Genes in Populations, 2nd edn. Wiley, New York, NY, USAGoogle Scholar
  37. Thrusfield M (1995) Veterinary epidemiology. Blackwell Science, New York, NY, USAGoogle Scholar
  38. Whitton BA (2002) Phylum Cyanophyta (Blue Green Algae/Cyanobacteria). In: John DJ, Whitton BA, Brook AJ (eds) The freshwater algal flora of the British Isles. An identification guide to freshwater and terrestrial algae. Cambridge University Press, Cambridge, UK, pp 25–122Google Scholar
  39. Williams MA (1977) Quantitative methods in biology. North Holland, Amsterdam, NetherlandsGoogle Scholar
  40. Woodruff DS (2001) Declines of biomes and biotas and the future of evolution. Proc Natl Acad Sci USA 98:5471–5476PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Victoria López-Rodas
    • 1
  • Antonio Flores-Moya
    • 2
  • Emilia Maneiro
    • 1
  • Nieves Perdigones
    • 1
  • Fernando Marva
    • 1
  • Marta E. García
    • 3
  • Eduardo Costas
    • 1
  1. 1.Genética (Producción Animal), Facultad de VeterinariaUniversidad ComplutenseMadridSpain
  2. 2.Biología Vegetal (Botánica), Facultad de CienciasUniversidad de MálagaMálagaSpain
  3. 3.Sanidad Animal (Microbiología), Facultad de VeterinariaUniversidad ComplutenseMadridSpain

Personalised recommendations