Project description:Toxicity of river sediments are assessed using whole sediment toxicity tests with benthic organisms. The challenge, however, is the differentiation between multiple effects caused by complex contaminant mixtures and the unspecific toxicity endpoints such as survival, growth or reproduction. Moreover, natural sediment properties, such as grain size distribution and organic carbon content, can influence the test parameters by masking pollutant toxicity. The use of gene expression profiling facilitates the identification of transcriptional changes at the molecular level that are specific to the bioavailable fraction of pollutants. The nematode Caenorhabditis elegans is ideally suited for these purposes, as (i) it can be exposed to whole sediments, and (ii) its genome is fully sequenced and widely annotated. In this pilot study we exposed C. elegans for 48 h to three sediments varying in degree of contamination with e.g. heavy metals and organic pollutants. Following the exposure period, gene expression was profiled using a whole genome DNA-microarray approach. Whole genome DNA microarray experiments were performed using a common reference design to identify differentially expressed genes in nematodes exposed to one of three river sediments of differing pollution level. Each sample consists of the 5 “biological replicates”.
Project description:The zebrafish embryo has repeatedly proved to be a useful model for the analysis of effects by environmental toxicants. This proof-of-concept study was performed to investigate if an approach combining mechanism-specific bioassays with microarray techniques can obtain more in-depth insights into the ecotoxicity of complex pollutant mixtures as present, e.g., in sediment extracts. For this end, altered gene expression was compared to data from established bioassays as well as to results from chemical analysis. Microarray analysis revealed several classes of significantly regulated genes which could to a considerably extend be related to the hazard potential. Results indicate that potential classes of contaminants can be assigned to sediment extracts by both classical biomarker genes and corresponding expression profile analyses of known substances. However, it is difficult to distinguish between specific responses and more universal detoxification of the organism. Microarray analysis were performed with early life stages of zebrafish exposed to 2 sediment extracts from the Upper part of the River Rhine, Germany. The expression profile as then compared to the expression pattern of model toxicants, such as, 4-chloroaniline, Cadmium, DDT, TCDD, and Valproic acid (Gene Expression Omnibus Series GSE9357). Additionally, combining mechanism-specific bioassays as well as chemical analysis of the sediments to the gene expression data has contributed to a more comprehensive view on the hazard potential of the sediments.
Project description:Toxicity of river sediments are assessed using whole sediment toxicity tests with benthic organisms. The challenge, however, is the differentiation between multiple effects caused by complex contaminant mixtures and the unspecific toxicity endpoints such as survival, growth or reproduction. Moreover, natural sediment properties, such as grain size distribution and organic carbon content, can influence the test parameters by masking pollutant toxicity. The use of gene expression profiling facilitates the identification of transcriptional changes at the molecular level that are specific to the bioavailable fraction of pollutants. The nematode Caenorhabditis elegans is ideally suited for these purposes, as (i) it can be exposed to whole sediments, and (ii) its genome is fully sequenced and widely annotated. In this pilot study we exposed C. elegans for 48 h to three sediments varying in degree of contamination with e.g. heavy metals and organic pollutants. Following the exposure period, gene expression was profiled using a whole genome DNA-microarray approach.
Project description:Metaproteomic data for Rodriguez-Ramos, et al. interrogating microbial and viral communities of hyporheic river sediments within the Columbia River. Samples were digested with trypsin, and analyzed by LC-MS/MS. Data was searched with MS-GF+ using PNNL's DMS Processing pipeline.
Project description:The zebrafish embryo has repeatedly proved to be a useful model for the analysis of effects by environmental toxicants. This study was performed to investigate if an approach combining mechanism-specific bioassays with microarray techniques can obtain more in-depth insights into the ecotoxicity of complex pollutant mixtures as present, e.g., in freeze-dried whole sediment samples and their corresponding organic extracts in parallel. To this end, altered gene expression was compared to data from established bioassays as well as to results from chemical analysis. Microarray analysis revealed several classes of significantly regulated genes which could to a considerable extent be related to the hazard potential. Results indicate that potential classes of contaminants can be assigned to sediment extracts by both classical biomarker genes and corresponding expression profile analyses of known substances. However, it is difficult to distinguish between specific responses and more universal detoxification of the organism. Additionally, different gene expression was shown to be less influenced by the sampling site than by the method of exposure, which could be attributed to differential bioavailability of contaminants. Microarray analyses were performed with early life stages of zebrafish exposed to sediment extracts or freeze-dried sediment from three sampling sites (Ehingen, Lauchert, Sigmaringen) along the Upper part of the Danube River, Germany. The expression profiles were compared within the sampling sites, between the exposure scheme and to the expression pattern of model toxicants, such as 4-chloroaniline, Cadmium, DDT, TCDD, and Valproic acid (Gene Expression Omnibus Series GSE9357). Additionally, mechanism-specific bioassays and chemical analysis of the sediments have been combined and compared to the present gene expression data.