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      Liver transcriptome analysis of Atlantic cod ( Gadus morhua) exposed to PCB 153 indicates effects on cell cycle regulation and lipid metabolism

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          Abstract

          Background

          Polychlorinated biphenyls (PCBs) are persistent organic pollutants (POPs) with harmful effects in animals and humans. Although PCB 153 is one of the most abundant among PCBs detected in animal tissues, its mechanism of toxicity is not well understood. Only few studies have been conducted to explore genes and pathways affected by PCB 153 by using high throughput transcriptomics approaches. To obtain better insights into toxicity mechanisms, we treated juvenile Atlantic cod ( Gadus morhua) with PCB 153 (0.5, 2 and 8 mg/kg body weight) for 2 weeks and performed gene expression analysis in the liver using oligonucleotide arrays.

          Results

          Whole-genome gene expression analysis detected about 160 differentially regulated genes. Functional enrichment, interactome, network and gene set enrichment analysis of the differentially regulated genes suggested that pathways associated with cell cycle, lipid metabolism, immune response, apoptosis and stress response were among the top significantly enriched. Particularly, genes coding for proteins in DNA replication/cell cycle pathways and enzymes of lipid biosynthesis were up-regulated suggesting increased cell proliferation and lipogenesis, respectively.

          Conclusions

          PCB 153 appears to activate cell proliferation and lipogenic genes in cod liver. Transcriptional up-regulation of marker genes for lipid biosynthesis resembles lipogenic effects previously reported for persistent organic pollutants (POPs) and other environmental chemicals. Our results provide new insights into mechanisms of PCB 153 induced toxicity.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1471-2164-15-481) contains supplementary material, which is available to authorized users.

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          Most cited references48

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment.

            Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.
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              The genome sequence of Atlantic cod reveals a unique immune system.

              Atlantic cod (Gadus morhua) is a large, cold-adapted teleost that sustains long-standing commercial fisheries and incipient aquaculture. Here we present the genome sequence of Atlantic cod, showing evidence for complex thermal adaptations in its haemoglobin gene cluster and an unusual immune architecture compared to other sequenced vertebrates. The genome assembly was obtained exclusively by 454 sequencing of shotgun and paired-end libraries, and automated annotation identified 22,154 genes. The major histocompatibility complex (MHC) II is a conserved feature of the adaptive immune system of jawed vertebrates, but we show that Atlantic cod has lost the genes for MHC II, CD4 and invariant chain (Ii) that are essential for the function of this pathway. Nevertheless, Atlantic cod is not exceptionally susceptible to disease under natural conditions. We find a highly expanded number of MHC I genes and a unique composition of its Toll-like receptor (TLR) families. This indicates how the Atlantic cod immune system has evolved compensatory mechanisms in both adaptive and innate immunity in the absence of MHC II. These observations affect fundamental assumptions about the evolution of the adaptive immune system and its components in vertebrates.
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                Author and article information

                Contributors
                Fekadu.Yadetie@mbi.uib.no
                Odd.Karlsen@mbi.uib.no
                Marta.Eide@bio.uib.no
                Christer.Hogstrand@kcl.ac.uk
                Anders.Goksoyr@bio.uib.no
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                17 June 2014
                17 June 2014
                2014
                : 15
                : 1
                : 481
                Affiliations
                [ ]Department of Molecular Biology, University of Bergen, Bergen, Norway
                [ ]Department of Biology, University of Bergen, Bergen, Norway
                [ ]Diabetes and Nutritional Sciences Division, King’s College London, London, UK
                Article
                6174
                10.1186/1471-2164-15-481
                4078240
                24939016
                afcf7f87-cf80-4bfd-8738-2e279dcdee45
                © Yadetie et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 1 April 2014
                : 11 June 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics
                Genetics

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