Rhodophyta, Ochrophyta and Chlorophyta macroalgae from different sub-Antarctic regions (Chile) and their potential for polyunsaturated fatty acids - Ziemann dos Santos, Marco Aurelio; Berneira, Lucas Moraes; Goulart, Natalia Leite; Mansilla Muñoz, Andres Omar; Astorga España, Maria Soledad; Pereira de Pereira, Claudio Martin (My University, 2021)
Polyunsaturated fatty acids are essential biomolecules to human health since their consumption is associated with decreased risk of cardiovascular, inflammatory and cancer diseases, for instance. Despite largely unexplored, sub-Antarctic macroalgae have a considerable nutraceutical potential since this region is known for its harsh environmental conditions, which forces macroalgae to produce secondary metabolites. Therefore, the aims of this work were to determine the fatty acid profile of Ulva sp., Lessonia flavicans Bory and Pyropia columbina (Montagne) W.A. Nelson collected from different collection sites in the Magellan region. Results showed that macroalgae were comprised of 18 to 24 fatty acids with generally a predominance of saturated fatty acids (SFAs) than unsaturated fatty acids. SFAs comprehended 34.40 +/- 0.61 mol% of Lessonia flavicans while Pyropia columbina had 69.06 +/- 0.77 mol% mainly in the form of palmitic acid. Polyunsaturated fatty acids were found in concentrations ranging from 15.80 +/- 0.56 mol% in Pyropia columbina to 54.93 +/- 0.15 in Lessonia flavicans. The nutraceutical potential of these macroalgae was observed as the samples had a n-ary sumation n3/ n-ary sumation n6 ratio above the indicated by the World Health Organization. Principal Component Analysis showed that the fatty acid profile is characteristic of each macroalgae being a biochemical marker for the identification of the organisms. Therefore, sub-Antarctic macroalgae comprise a promising renewable source of essential fatty acids, mainly as n3, that are essential to the maintenance of human health.
Keywords: collection sites; fatty acids; gas chromatography; macroalgae; principal component analysis