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Updated: May 7, 2026

Analysis of Fatty Acid Content and Composition in Microalgae
Published on: October 1, 2013
Effect of environmental variations on amino acid δ15N values in macroalgae
Hee Young Yun1, Sangil Kim2, Eun-Ji Won1
1Institute of Ocean and Atmospheric Sciences, Hanyang University, Ansan, 15588, Republic of Korea.
None:
Macroalgae are widely used as indicators of environmental change, yet distinguishing natural physiological variability from environmental stressor-induced biochemical responses remains challenging in dynamic coastal environments. We investigated amino acid (AA) specific nitrogen isotope composition (δ15NAA) variations in the macroalgae Ecklonia and Ulva to evaluate eco-physiological responses across contrasting environmental conditions. We assessed perennial Ecklonia and ephemeral Ulva collected in different seasons and combined with cultured Ulva exposed to nitrogen addition under a temperature gradient (12 °C, 20 °C, and 27.5 °C) in laboratory experiments. In field-collected macroalgae, the δ15NAA values varied temporally, but overall δ15NAA patterns were relatively consistent, characterized by isotopically high glutamic acid (Glu) relative to isotopically low glycine (Gly) and serine (Ser). In contrast, overall δ15NAA patterns (i.e., δ15NGlu > δ15NGly and δ15NSer) were not comparably detected in cultured Ulva, where the magnitude and direction of the isotopic shifts depended on nitrogen addition and temperature. The δ15N offset between glutamic acid and phenylalanine was 4.0 ± 1.0 ‰ in Ecklonia, consistent with recalculated reference values (3.9 ± 1.1 ‰) but was lower in field-collected Ulva (1.8 ± 1.1 ‰) and cultured Ulva at 12 °C with N addition (i.e., -5.6 ± 1.5 ‰). These results show that δ15NAA metrics were sensitive to N enrichment and temperature in controlled experiments, and exhibited seasonal differences between species in the field, reflecting alterations in glutamic acid-centered nitrogen metabolism, particularly in opportunistic Ulva. Ultimately, this approach enhances our interpretation of food-web baselines by linking species-specific physiological traits to ecological responses in eutrophic and warming coastal ecosystems.
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