The storage lipid metabolism of two caridean shrimp species (Crangon crangon and Pandalus montagui) was studied through a combination of enzyme assays, total lipid determination and transcriptome analyses. The initital sampling was carried out in June, July and August 2021 by the research vessel R/V Uthörn. Freshly caught shrimps from the North Sea were measured, weighted and dissected and brought back to the laboratory facilites of the Alfread-Wegener-Institute, Bremerhaven, Germany. Individual midgut glands were weighted to determine the wet mass and freeze-dried. Dry mass was termined and lipids were extracted after Hagen (2000, see in Postel et al. 2000). The total lipid content of individual midgut glands of Crangon crangon and Pandalus montagui was determined gravimetrically. The synthesis of the storage lipid triacylglycerol (TAG) was measured in pooled microsomal fraction of midgut gland tissue of both shrimp species through the activity of the enzyme diacylglycerol acyltransferase (DGAT) at 37 °C in a water bath (McFie & Stone 2011). Here a fluorescent activated fatty acid (NBD-palmitoyl-CoA, 810229 Avanti Polar Lipids) was used. Lipids in the reaction mix were extracted and lipid classes separated on a thin layer chromatography plate. DGAT activity was measured through arbitrary fluorescent units (AFU/min/mg protein) of the correscponding TAG product. Annotated transcriptomes of both species (C. crangon Bioproject: PRJNA479562, NCBI; P. montagui Bioproject PRJNA798226, NCBI) were screened for enzymes involved in the lipid metabolism. Transcripts identified as relevant enzymes using BLAST were translated into amino acid sequences.
Objective: This project concerns the first large-scale application of the full range of omics technologies in a population study aiming at a) the discovery and validation of novel biomarkers predictive of increased risks of a number of chronic diseases, b) the exploration of the association of such biomarkers with environmental exposures, including high-priority pollutants and emerging exposures, and c) the discovery and validation of biomarkers of exposure to the above and other high-priority environmental exposures. The project will utilise three existing prospective cohorts. Cancer-related -omics biomarkers will be developed using a case-control study nested within 2 cohorts which contain biosamples collected prior to disease diagnosis, exposure and followup health information. Biomarkers will be compared in 600 breast cancer cases, 300 NHL cases and equal numbers of matched controls, to evaluate their risk predictivity. Biomarkers of chronic diseases which establish themselves in early childhood but persist into adult life will be evaluated using a mother-child cohort. Biosamples collected from 600 children at birth and at ages 2 and 4 years will be analysed and results compared with clinical indices obtained at age 4. Thanks to the availability of repeat samples, collected over a wide range of time intervals, the intra-individual variation of biomarkers and their relationship with disease progression will be evaluated. Biomarker search will utilize state-of-the-art metabonomics, epigenomics, proteomics and transcriptomics, in combination with advanced bioinformatics and systems biology tools. It will also include technical validation of -omics technology s utilisation with biobank samples. Exposure assessment will utilize exposure biomarkers, questionnaires, modelling and GIS technology. Additional data on exposure, biomarkers (including SNP data) and health indices, available through other projects, will be utilised, thus generating substantial added value.