Chronic Phytotoxicity in Gametophytes: DNA as Biomarker of Growth and Chlorophyll Autofluorescence as Biomarker of Cell Function

  • Myriam Catalá
  • José Luis Rodríguez-Gil


The use of an adequate range of taxa in ecotoxicological studies is a key point for the achievement of ecologically relevant results. Higher plants are an essential part of a healthy and balanced ecosystem and new plant models are essential in the evaluation of potential impacts of pollutants. With more than 10,000 living species, ferns are the second-largest group of vascular plants. Fern spores, and spore-developed gametophytes, have long been recognized as useful models for plant research in important areas. One of the main advantages of this model is its naturally miniature size. Fern spores are single meiotic cells which develop into gametophytes which are miniature mature higher plants. The use of microtubes and microplates is imposed by the natural model. Chronic toxicity testing involves longer periods of exposure to toxicants (>48 h) and assesses the ability of a substance to disrupt a significant portion of an organism’s life stage. DNA content in developing gametophytes is a biomarker of the disturbance that the toxicant provokes in gametophyte growth and development. The use of the DNA fluorescent probe Hoechst is a rapid, sensitive, and reliable method frequently used in cell biology which has been successfully applied to spores and gametophytes. Chlorophyll autofluorescence can also be used as a biomarker of the physiological state. Both biomarkers can easily be measured using 96 multiwell plates and plate readers. The combined use of these biomarkers in chronic toxicity tests using developing gametophytes of the riparian Polystichum setiferum is yielding very satisfactory results and is a promising new model for Ecotoxicology.


United States Environmental Protection Agency Fern Spore Chronic Toxicity Test Chlorophyll Autofluorescence Fern Gametophyte 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors want to thank Raquel Feito for giving permission to use unpublished results to illustrate the examples shown in this chapter.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Biology and Geology, ESCETRey Juan Carlos UniversityMóstolesSpain

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