bioRxivEcology
Errors associated with compound specific δ15N analysis of amino acids in preserved fish samples purified by high pressure liquid chromatography
R. Swalethorp, L. Aluwihare, A. R. Thompson, M. D. Ohman, M. R. Landry
Abstract
Compound specific isotopic analysis of amino acids (CSIA-AA) is increasingly used in ecological and biogeochemical studies tracking the origin and fate of nitrogen (N). Its advantages include the potential for resolving finer-scale trophic dynamics than possible with standard bulk SIA and for reconstructing historical changes in the food webs of consumers from analyses of specimens in preserved sample archives. For the latter, assessing the effects of chemical preservatives on {delta}15NAA has been inconclusive because the conventional CSIA approach for derivatized AAs by gas chromatography - combustion - isotope ratio mass spectrometry (GC-C-IRMS) has analytical errors (0.4 - 1.0 {per thousand}) in the range expected from chemical preservation. Here, we show improved analytical precision (0.15 {+/-} 0.08 {per thousand}) for 11 underivatized AA standards analyzed by high pressure liquid chromatography followed by offline elemental analysis - IRMS (HPLC/EA-IRMS), an approach originally developed by Broek and McCarthy (2014). Using this method, we report the first high-precision tests of preservation effects on {delta}15NAA in Northern Anchovy (Engraulis mordax) kept 1[1/2]-year in ethanol and up to 27-years in formaldehyde. We found minimal methodological induced fractionation for 8 AAs, and preservation effects on {delta}15N were similar regardless of duration and preservative used. Although some of the AAs differed significantly from frozen control samples (average +1.0 {+/-} 0.8 {per thousand}), changes in {delta}15N in the source AA Phenylalanine and trophic position estimates were statistically insignificant. Our results are encouraging for resolving fine-scale natural variability using HPLC/EA-IRMS on chemically preserved specimens and for ultimately reconstructing biogeochemical records and trophic dynamics over long time scales.
- organism: multiple species
- assay: bulk RNA-seq
- research focus: ecology & biodiversity
- approach: statistical model
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