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Marine Biology

, Volume 148, Issue 4, pp 779–788 | Cite as

Trophic modification of essential fatty acids by heterotrophic protists and its effects on the fatty acid composition of the copepod Acartia tonsa

  • Adriana J. Veloza
  • Fu-Lin E. Chu
  • Kam W. Tang
Research Article

Abstract

To test whether heterotrophic protists modify precursors of long chain n−3 polyunsaturated fatty acids (LCn−3PUFAs) present in the algae they eat, two algae with different fatty acid contents (Rhodomonas salina and Dunaliella tertiolecta) were fed to the heterotrophic protists Oxyrrhis marina Dujardin and Gyrodinium dominans Hulbert. These experiments were conducted in August 2004. Both predators and prey were analyzed for fatty acid composition. To further test the effects of trophic upgrading, the calanoid copepod Acartia tonsa Dana was fed R. salina, D. tertiolecta, or O. marina that had been growing on D. tertiolecta (OM-DT) in March 2005. Our results show that trophic upgrading was species-specific. The presence of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in the heterotrophic protists despite the lack of these fatty acids in the algal prey suggests that protists have the ability to elongate and desaturate 18:3 (n−3), a precursor of LCn−3PUFAs, to EPA and/or DHA. A lower content of these fatty acids was detected in protists that were fed good-quality algae. Feeding experiments with A. tonsa showed that copepods fed D. tertiolecta had a significantly lower content of EPA and DHA than those fed OM-DT. The concentration of EPA was low on both diets, while DHA content was highest in A. tonsa fed R. salina and OM-DT. These results suggest that O. marina was able to trophically upgrade the nutritional quality of the poor-quality alga, and efficiently supplied DHA to the next trophic level. The low amount of EPA in A. tonsa suggests EPA may be catabolized by the copepod.

Keywords

Dunaliella Heterotrophic Dinoflagellate Heterotrophic Protist Dunaliella Tertiolecta Paracalanus Parvus 
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.

Notes

Acknowledgements

This study was supported by NOAA-CMER awards NA03NMF4550382 and NA04NMF4550390, and by Sigma Xi Grants In Aid of Research. The authors are grateful for Dr. Eric Lund’s advice and help in lipid analysis, GC operation and editing the revised version of this manuscript. The authors thank Mrs. Georgetta Constantin for assistance in lipid analyses. Contribution no. 2698 by the Virginia Institute of Marine Science, College of William and Mary.

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Adriana J. Veloza
    • 1
  • Fu-Lin E. Chu
    • 1
  • Kam W. Tang
    • 1
  1. 1.Virginia Institute of Marine ScienceGloucester PointUSA

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