Stability of the lipid biomarker H-Print within preserved animals

Highly branched isoprenoid lipid (HBI) biomarkers have been reported in a wide range of Arctic animals spanning all trophic levels. The HBI biomarker-based ‘H-Print’ has been used to estimate the relative contributions of sea ice- and phytoplankton-derived primary production utilised by Arctic anima...

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Bibliographic Details
Published in:Polar Biology
Main Author: Brown, Thomas Adam
Format: Article in Journal/Newspaper
Language:English
Published: 2018
Subjects:
H-print
HBI
IP25
Storage
Food web
Sea ice primary production
Arctic
Climate change
Phytoplankton
Polar Biology
Sea ice
Online Access:https://pure.uhi.ac.uk/en/publications/850f26d3-d64b-4917-a190-1b4a5af3e32b
https://doi.org/10.1007/s00300-018-2317-2
https://pureadmin.uhi.ac.uk/ws/files/3206177/Brown_2018_PURE.docx
Description
Summary:Highly branched isoprenoid lipid (HBI) biomarkers have been reported in a wide range of Arctic animals spanning all trophic levels. The HBI biomarker-based ‘H-Print’ has been used to estimate the relative contributions of sea ice- and phytoplankton-derived primary production utilised by Arctic animals. The resulting data are providing insight into the future impact of climate change-associated sea ice decline on ecosystems. Given the range of methods available to preserve biological tissues between sampling and analysis, it was considered important to test the suitability of these methods for storage prior to the analysis of HBI lipids. In the laboratory, Artemia sp. were fed diatoms containing HBIs of known proportion. These were then harvested and stored wet- and dry-frozen and in ethanol and 4% formalin. After 6 months, Artemia sp. H-Prints stored in ethanol were significantly different from the control, whereas H-Prints from all other methods were not significantly different from the control. Dry-frozen Artemia sp. H-Prints bared the closest similarity to the control, representing the best method tested for tissue preservation prior to analysis of HBIs. This study will contribute to improving the robustness of HBI-based H-Print analyses in rapidly changing Arctic ecosystems.

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