Aquaculture, Fish and Fisheries (Feb 2024)

Rapid detection of heat stress biomarkers in Atlantic salmon (Salmo salar) liver using targeted proteomics

  • Omar Mendoza‐Porras,
  • Anca G. Rusu,
  • Christopher Stratford,
  • Nicholas M. Wade

DOI
https://doi.org/10.1002/aff2.147
Journal volume & issue
Vol. 4, no. 1
pp. n/a – n/a

Abstract

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Abstract Most fish are ectothermic; therefore, their physiology is significantly affected by temperature. Aquaculture fish have limited ability to avoid elevated water temperatures, with impacts increasing as a result of climate change. To date, quantifying gene expression has been proposed to monitor heat stress in salmon liver. This study aimed to establish a faster multiplexed proteomics method to measure the abundance of thermal stress biomarkers in liver of salmon reared at 15°C or 20°C. Moreover, this study aimed to determine the effects that sample pooling, and data normalisation using housekeeping (HK) protein peptides would exert over the statistical significance of these thermal stress markers. A multiple reaction monitoring (MRM) mass spectrometry method, comprised 45 peptides derived from thermal stress markers and 10 peptides from HK proteins, was applied to measure these markers in liver of salmon reared at 15°C or 20°C. When samples were processed individually, 34 peptides were significant between salmon livers at 15°C or 20°C. In pooled samples, this decreased to five significant peptides. Peptides hprt1_HYADDLDR (hypoxanthine phosphoribosyl transferase) and gapdh_VPTPNVSVVDLTVR (glyceraldehyde‐3‐phosphate dehydrogenase) were the most stable and unstable HK protein peptides, respectively. When data was normalised with hprt1_HYADDLDR, 16 peptides were significant in individual samples and 13 in pooled samples. Significant peptides serpinh1a_ADLSNISGK, SerpinH1_TNSILFIGR, ela2_VVGGEDVR and gapdh_VPTPNVSVVDLTVR were common regardless of data strategy. A fast and reliable MRM method was established to validate thermal stress markers in salmon liver, where individual samples yielded better results than pooled samples. Sample pooling was only better when combined with normalisation as it validated twice the number of markers than sample pooling alone. This method could be applied to monitoring stress response in experiments involving feeding additives designed to mitigate thermal stress or in selective breeding programs to help understanding family variance in thermal tolerance.

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