Characterizing Isotopic Fingerprints of Eukaryotic Microalgae to Study Sources and Cycling of Organic Matter through Food Webs

Phytoplankton community composition influences the structure of and carbon flux into food webs. While bulk carbon isotope analysis has been used to study the sources and cycling of organic matter for decades, this approach cannot accurately identify which primary producer taxonomic groups are fueling higher trophic levels. Compound-specific isotope analysis of amino acids (CSIA-AA) has the potential to fill this gap based on the concept that different phytoplankton taxa have unique amino acid isotope values or “fingerprints” reflecting the metabolic diversity in their amino acid synthesis pathways. While such “amino acid isotope fingerprints” have been identified for broad taxonomic groups, we do not yet know how taxonomically specific these fingerprints may be. Here, we conducted an experiment using controlled cultures of multiple eukaryotic microalgae to analyze their carbon isotope values using CSIA-AA. Microalgae were harvested during their exponential growth phase which was beneficial for both maximum phytoplankton and minimum bacterial growth as excess bacterial contamination confounded the targeted microalgae fingerprint. Axenic cultures for select species were grown in parallel to aid separation between bacterial and phytoplankton fingerprinting. Through controlled phytoplankton cultures, bacterial staining and enumeration, and CSIA-AA analysis, we generated a unique fingerprinting library for a suite of eukaryotic microalgae with strong separation in essential amino acid carbon isotope values among different taxa. By targeting essential amino acids, these unique tracers are passed onto higher trophic consumers unaltered, providing a roadmap for carbon flow throughout the food web. A better understanding for carbon sources and cycles informs our ability to characterize which taxa fuel and structure food webs, understand phytoplankton impacts on fisheries dynamics and biogeochemical cycling, and identify the links between oceanic ecosystems and atmospheric climate. In addition, better understanding these processes can give valuable insight into how cycles may change with the future changing climate.