Marta Eide

Towards the Digital Salmon: From a reactive to a pre-emptive research strategy in aquaculture (DigiSal)

Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. Project DigiSal will lay the foundations for a Digital Salmon: an ensemble of mathematical descriptions of salmon physiology, combining ...

Coastal zones and oceans constitute an essential fundament for Norway’s history as well as current economy, providing ecosystem services for fisheries, aquaculture, transport, tourism, and recreation. The petroleum activities in Norwegian waters have been crucial for Norway’s financial growth and in financing the Norwegian welfare state. As the pressure on the oceans continuously increases, both the petroleum industry and the seafood industries have acknowledged that awareness and actions are ...

Aim: To investigate whether Atlantic cod that feed close to aquatic breeding facilities are affected by chlorpyrifos-methyl. Feeding experiment with chlorpyrifos-methyl, an organophosphorous pesticide detected in plant based salmon feed. Based on previous experiments using salmon.

Doses: 0, 0.5, 5.0, 25 mg/kg) chlorpyrifos-methyl. Duration: 30 days Set-up: Three tanks per treatment (12 in total)

Samples include: Liver, plasma, bile, brain. Analysis include:

• Have RNAseq and metabolomics from 36 ...

Interspecies differences in sensitivity to chemical exposures pose a great challenge in toxicological risk assessments. How an organism copes with chemicals is largely determined by the genes and proteins that collectively function to defend against, detoxify and eliminate chemical stressors. This integrative network includes receptors and transcription factors, biotransformation enzymes, transporters, antioxidants, and metal- and heat-responsive genes, and is collectively known as the chemical ...

Location: UiB Date: 8-20 June 2017 Compounds tested: WY-14,643 (PPAR alpha agonist), GW501516 (PPAR beta agonist) No. of test groups: 5 (Control 1: DMSO/saline/PEG, WY-14.643 High (40 mg/kg), WY-14.643 Low (4.0 mg/kg), GW501516 High (4.0 mg/kg), GW501516 Low (0.4 mg/kg)) No. of fish per group: 22

Aim: *To investigate effects on lipid metabolism in Atlantic cod ( Gadus morhua) mediated by peroxisome proliferator-activated receptors (Ppars) by in vivo exposure to two mammalian PPAR agonists.

Fish weight (start - end), length, total growth and specific growth rate (SGR)

Liver samples from Atlantic cod males. Total RNA isolated using TRI Reagent (Fekadu Yadetie). Sequencing performed with Illumina Stranded mRNA (sequencing poly-A mRNA) at Genomic Core Facility at UiB/Haukeland (contact person Rita Holdhus).

The data sets are submitted to the ArrayExpress repository, and will be linked here.

Build the chemical defensome gene list for 5 fish: Zebrafish (Danio rerio), Atlantic cod (Gadus morhua), medaka (Oryzias latipes), Atlantic killifish (Fundulus heteroclitus) and stickleback (Gasterosteus aculeatus). Source code and relevant files can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/defensomeGenes

To study the defensome genes' expression in early developmental stages of zebrafish and stickleback. Souce code and relevant files can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/developmentalStages

Exposing zebrafish to benzo(a)pyrene (B(a)P) (gene counts from NCBI GEO: GSE64198, previously published by Fang, et al. 2015. Souce code and relevant files can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/exposureResponse

Untargeted lipidomics analysis was performed on plasma and liver samples of four male fish from each group (n = 4) at Per Bruheim’s lab at NTNU, Norway, using Liquid Chromatography Hybrid Quadrupole Mass Spectrometry (UPLC-HDMS).

Targeted lipidomic analysis was performed on plasma and isolated liver microsomes of eight male fish from solvent control (Control) and High-Dose groups (n = 8) at Cinta Porte’s lab at CSIC, Spain, using Flow Injection Analysis High-Resolution Mass Spectrometry (FIA-HRMS).

The data is submitted to the MetaboLights repository.

The data is submitted to the PRIDE repository, and will be linked here.

The aim of the exposure was to study the effects of activation of peroxisome proliferator-activated receptors (PPARs) in Atlantic cod (Gadus morhua), by injecting the fish with the compounds WY-14,643 and GW501516. Using luciferase reporter assay in vitro, we have shown that WY-14,643 activate Atlantic cod Ppara1 and Ppara2, while GW501516 activate Ppara1, Ppara2, and Pparb. The experimental set-up was as follows: Immature cod were injected at day 0 and day 4 with either high dose (40 mg/kg ...

Untargeted lipidomics analysis was performed on plasma and liver samples of four male fish from each group (n = 4) at Per Bruheim’s lab at NTNU, Norway, using Liquid Chromatography Hybrid Quadrupole Mass Spectrometry (UPLC-HDMS).

Normalisation: The fraction of each lipid compound among all measured lipids in every sample was calculated and was used in the downstream analysis.

The four treatment groups were Control (0 mg CPM/kg, with DMSO), 0.5 mg CPM/kg, 4.2 mg CPM/kg and 23.2 mg CPM/kg. Each treatment group consisted of 9 fish. These fish were sampled from 3 different tanks per treatment, with n=9 per treatment. A total of 36 samples were sequenced. For each sample, about 50 million 150 bp paired-end reads were generated.

There are four datasheets in the Excel file: 1. Gene pattern and the corresponding category (the gene list is then divided into the other three datasheets); 2. These gene names (patterns) can be directly followed by either a letter or a number; 3. These gene names (patterns) should be directly followed by a letter; 4. These gene names (patterns) should be directly followed by a number.

Biometric data from in vivo II experiment

This is an auto-generated model with COBRA Matlab toolbox. This model was deposited in BioModels [1] and assigned the identifier MODEL2010090003.

[1] Malik-Sheriff et al. BioModels — 15 years of sharing computational models in life science. Nucleic Acids Research. 2020 Jan, 48(D1):D407–415

This is an auto-generated model with COBRA Matlab toolbox. This model was deposited in BioModels [1] and assigned the identifier MODEL2010090002.

[1] Malik-Sheriff et al. BioModels — 15 years of sharing computational models in life science. Nucleic Acids Research. 2020 Jan, 48(D1):D407–415

This is an auto-generated model with COBRA Matlab toolbox. This model was deposited in BioModels [1] and assigned the identifier MODEL2010090001.

[1] Malik-Sheriff et al. BioModels — 15 years of sharing computational models in life science. Nucleic Acids Research. 2020 Jan, 48(D1):D407–415

Supplementary Table1 and Table2 for manuscript "The chemical defensome of fish"