What 100+ amino acid isotope (CSIA-AA) studies reveal about tracing organismal ecology: Roles of trophic interactions, phylogeny, and environment
Compound-specific stable isotope analysis of amino acids (CSIA-AA) has the potential to reveal an organism’s ecology to an extent not attainable with conventional bulk isotopic analysis. By measuring the isotope ratios of many amino acids from a particular sample, more information is generated and researchers have more inferential power. For example, CSIA has been used to precisely define trophic levels, to compare nutrient allocation in different environments, and to identify producers in complex food webs. The potential applications of CSIA are many, as evidenced by the exponential growth in the use of this method over the past decade.
We aggregated over 100 articles, book chapters, and dissertations that presented compound-specific isotopic data on natural-abundance carbon or nitrogen in organismal amino acids. The samples analyzed in these papers spanned 370 species, 6 continents, and 160,000 years. Next, we modeled how various amino acids correlate with a range of ecological factors to determine which amino acid isotope measurements are the best candidates for inferring ecological processes. Finally, we tested how broadly some proposed inferential models could be successfully applied to novel systems.
Whether studies examined amino acid δ13C or δ15N, some commonalities emerged: the majority of studies were observational (> 60%), focused on marine eukaryotic organisms, and reported data from relatively few samples (mean n < 16). δ13C values of essentially all amino acids were at least weakly positively correlated with one another, but there was more variability in the pairwise correlations of amino acid δ15N values. For primary producers, amino acid isotope measurements strongly reflected phylogeny. Conversely, consumer amino acid isotope measurements were most strongly correlated with diet, but the signature was potentially modified by a range of physiological factors ranging from presence of endosymbionts to body condition.
Several of the paradigms in CSIA-AA warrant further examination. Methods of hydrolysis, derivatization, and analysis are not uniform across labs, and may limit inter-lab comparability of data. The most widely used models for calculating trophic positions mischaracterize many organisms. The trophic/source dichotomy routinely used to categorize amino acids may be better viewed as a gradient than categorically, and this has implications for the interpretation of organismal ecology. Ultimately, generating more data on more amino acids will allow researchers to better contextualize findings and improve the inferences drawn from compound-specific amino acid data.