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      Transcriptomics Responses in Marine Diatom Thalassiosira pseudonana Exposed to the Polycyclic Aromatic Hydrocarbon Benzo[a]pyrene

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      PLoS ONE
      Public Library of Science

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          Abstract

          Diatoms are unicellular, photosynthetic, eukaryotic algae with a ubiquitous distribution in water environments and they play an important role in the carbon cycle. Molecular or morphological changes in these species under ecological stress conditions are expected to serve as early indicators of toxicity and can point to a global impact on the entire ecosystem. Thalassiosira pseudonana, a marine diatom and the first with a fully sequenced genome has been selected as an aquatic model organism for ecotoxicological studies using molecular tools. A customized DNA microarray containing probes for the available gene sequences has been developed and tested to analyze the effects of a common pollutant, benzo(a)pyrene (BaP), at a sub-lethal concentration. This approach in diatoms has helped to elucidate pathway/metabolic processes involved in the mode of action of this pollutant, including lipid metabolism, silicon metabolism and stress response. A dose-response of BaP on diatoms has been made and the effect of this compound on the expression of selected genes was assessed by quantitative real time-PCR. Up-regulation of the long-chain acyl-CoA synthetase and the anti-apoptotic transmembrane Bax inhibitor, as well as down-regulation of silicon transporter 1 and a heat shock factor was confirmed at lower concentrations of BaP, but not the heat-shock protein 20. The study has allowed the identification of molecular biomarkers to BaP to be later on integrated into environmental monitoring for water quality assessment.

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          Most cited references38

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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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            Processing of gene expression data generated by quantitative real-time RT-PCR.

            Quantitative real-time PCR represents a highly sensitive and powerful technique for the quantitation of nucleic acids. It has a tremendous potential for the high-throughput analysis of gene expression in research and routine diagnostics. However, the major hurdle is not the practical performance of the experiments themselves but rather the efficient evaluation and the mathematical and statistical analysis of the enormous amount of data gained by this technology, as these functions are not included in the software provided by the manufacturers of the detection systems. In this work, we focus on the mathematical evaluation and analysis of the data generated by quantitative real-time PCR, the calculation of the final results, the propagation of experimental variation of the measured values to the final results, and the statistical analysis. We developed a Microsoft Excel-based software application coded in Visual Basic for Applications, called Q-Gene, which addresses these points. Q-Gene manages and expedites the planning, performance, and evaluation of quantitative real-time PCR experiments, as well as the mathematical and statistical analysis, storage, and graphical presentation of the data. The Q-Gene software application is a tool to cope with complex quantitative real-time PCR experiments at a high-throughput scale and considerably expedites and rationalizes the experimental setup, data analysis, and data management while ensuring highest reproducibility.
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              Aquatic phototrophs: efficient alternatives to land-based crops for biofuels.

              To mitigate some of the potentially deleterious environmental and agricultural consequences associated with current land-based-biofuel feedstocks, we propose the use of biofuels derived from aquatic microbial oxygenic photoautotrophs (AMOPs), more commonly known as cyanobacteria, algae, and diatoms. Herein we review their demonstrated productivity in mass culturing and aspects of their physiology that are particularly attractive for integration into renewable biofuel applications. Compared with terrestrial crops, AMOPs are inherently more efficient solar collectors, use less or no land, can be converted to liquid fuels using simpler technologies than cellulose, and offer secondary uses that fossil fuels do not provide. AMOPs pose a new set of technological challenges if they are to contribute as biofuel feedstocks.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                3 November 2011
                : 6
                : 11
                : e26985
                Affiliations
                [1]Rural, Water, and Ecosystem Resources Unit, Institute for Environment and Sustainability, European Commission - Joint Research Centre, Ispra, Varese, Italy
                UCLA-DOE Institute for Genomics and Proteomics, United States of America
                Author notes

                Conceived and designed the experiments: TL SKB. Performed the experiments: RNC SKB. Analyzed the data: RNC TL. Wrote the paper: RNC SKB TL.

                Article
                PONE-D-11-13747
                10.1371/journal.pone.0026985
                3207822
                22073232
                33c9fc31-57b8-4657-806e-01de79a0aeeb
                Carvalho et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 19 July 2011
                : 7 October 2011
                Page count
                Pages: 9
                Categories
                Research Article
                Biology
                Computational Biology
                Microarrays
                Genomics
                Genome Expression Analysis
                Model Organisms
                Plant and Algal Models
                Molecular Cell Biology
                Cellular Stress Responses
                Gene Expression
                Plant Science
                Plants
                Algae
                Toxicology
                Predictive Toxicology

                Uncategorized
                Uncategorized

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