Element load, conventional biomarkers and altered protein expression profiles were studied in Carcinus maenas crabs, to assess contamination of “Domingo Rubio” stream, an aquatic ecosystem that receives pyritic metals, industrial contaminants, and pesticides. Lower antioxidative activities – glucose-6-phosphate and 6-phosphogluconate dehydrogenases, catalase – were found in parallel to higher levels of damaged biomolecules – malondialdehyde, oxidized glutathione –, due to oxidative lesions promoted by contaminants, as the increased levels of essential – Zn, Cu, Co – and nonessential – Cr, Ni, Cd – elements. Utility of Proteomics to assess environmental quality was confirmed, especially after considering the six proteins identified by de novo sequencing through capLC-μESI-ITMS/MS and homology search on databases. They include tripartite motif-containing protein 11 and ATF7 transcription factor (upregulated), plus CBR-NHR-218 nuclear hormone receptor, two components of the ABC transporters and aldehyde dehydrogenase (downregulated). These proteins could be used as novel potential biomarkers of the deleterious effects of pollutants present in the area.

In recent years, concerns about using Bisphenol A (BPA) in daily consume products and its effects in many chronic human diseases have prompted the removal of BPA. However, the widely used BPA alternatives, including Bisphenol S (BPS), have a high structural similarity with BPA, suggesting that they may have similar biological effects towards human beings. Indeed, BPS was also found to have endocrine-disrupting effects. Epigenetic mechanism was reported to be involved in BPA-induced biological effects in both in vitro and in vivo models. However, there is no assessment on whether BPS could cause epigenetic changes. In this work, we investigated the possible epigenetic effects of BPS that might induce in human breast cancer cell line MCF-7. We found that BPS could change DNA methylation level of transposons. Besides, methylation status in promoter of breast cancer related genes CDH1, SFN, TNFRSF10C were also changed, which implied that BPS might play a role in the development of breast cancer. Gene expression profiling showed that some genes related to breast cancer progression were upregulated, including THBS4, PPARGC1A, CREB5, COL5A3. Gene ontology (GO) analysis of the differentially expressed genes revealed the significantly changes in PI3K-Akt signaling pathway and extracellular matrix, which were related to the proliferation, migration and invasion of breast cancer cells. These results illustrated that BPS exposure might play roles in the progression of breast cancer.

Degradation of heavy oil by bacteria to decompose organic compounds such as aliphatic and aromatic hydrocarbons has been used in bioremediation. However, the biological and environmental effects of the degradation products including intermediates are still not clear. Here, we monitored the degradation of C-heavy oil by analyzing the products formed in cultures with oil-degrading bacteria (complex microbes or a single bacterial strain). Furthermore, proliferation assays using breast cancer MCF-7 cells and gene-expression profiling of MCF-7 cells using oligonucleotide-DNA microarrays were performed to evaluate the estrogenic activity of the degradation products. While the products did not show any significant cell-proliferative activity, the oil samples cultured for longer periods (2–3 months), whether cultured with mixed microbes or a single bacterial strain, showed gene-expression profiles similar to that of 17β-estradiol (E₂). These results suggest that oil-degradation products have estrogenic activity, and estrogen-like components could possibly be produced during the degradation process.

Polycyclic aromatic hydrocarbons (PAHs) are the most persistent organic pollutants in worldwide aquatic environments. The extensive isolation of genes responsive to PAH pollution in soft coral (Scleronephthya gracillimum) is described herein. Soft coral colonies were exposed to 100 μg/L of a standard mixture of PAHs. Gene candidates with transcript levels that changed in response to PAH exposure were identified by differential display polymerase chain reaction (DD-PCR). There were 37 types of candidate genes identified, of which 20 were upregulated in expression and 17 were downregulated. The functions of the genes identified included oxidative stress response, ribosomal structure maintenance, molecular chaperone activity, protein kinase activation and tumorigenesis, defense mechanisms, transcription, and other biological responses. mRNA quantification was carried out using real-time quantitative PCR in eight selected genes: cytosolic malate dehydrogenase, protein disulfide isomerase, ribosomal protein L6, ral guanine nucleotide dissociation stimulator-like 1, poly(ADP-ribose) polymerase 4, peptidylglycine α-hydroxylating monooxygenase, a disintegrin and metalloproteinase (ADAM) metallopeptidase protein, and eukaryotic initiation factor 4 gamma 3. Changes in transcript levels were consistent with DD-PCR results. The gene candidates isolated in this study were differentially expressed and therefore have potential as molecular biomarkers for understanding coral responses to environmental stressors.

Monitoring of marine microalgae is important to predict and manage harmful algae blooms. It currently relies mainly on light-microscopic identification and enumeration of algal cells, yet several molecular tools are currently being developed to complement traditional methods. MIcroarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a hierarchical multispecies microarray as one of these tools. Prototype arrays are currently being tested with field samples, yet the analysis of the large quantities of data generated by these arrays presents a challenge as suitable analysis tools or protocols are scarce. This paper proposes a two-part protocol for the analysis of the MIDTAL and other hierarchical multispecies arrays: Signal-to-noise ratios can be used to determine the presence or absence of signals and to identify potential false-positives considering parallel and hierarchical probes. In addition, normalized total signal intensities are recommended for comparisons between microarrays and in order to relate signals for specific probes to cell concentrations using external calibration curves. Hybridization- and probe-specific detection limits can be calculated to help evaluate negative results. The suggested analyses were implemented in “GPR-Analyzer”, a platform-independent and graphical user interface-based application, enabling non-specialist users to quickly and quantitatively analyze hierarchical multispecies microarrays. It is available online at http://folk.uio.no/edvardse/gpranalyzer .

Background, aim, and scope Pharmaceuticals are emerging pollutants widely used in everyday urban activities which can be detected in surface, ground, and drinking waters. Their presence is derived from consumption of medicines, disposal of expired medications, release of treated and untreated urban effluents, and from the pharmaceutical industry. Their growing use has become an alarming environmental problem which potentially will become dangerous in the future. However, there is still a lack of knowledge about long-term effects in non-target organisms as well as for human health. Toxicity testing has indicated a relatively low acute toxicity to fish species, but no information is available on possible sublethal effects. This study provides data on the physiological pathways involved in the exposure of Atlantic salmon as representative test species to three pharmaceutical compounds found in ground, surface, and drinking waters based on the evaluation of the xenobiotic-induced impairment resulting in the activation and silencing of specific genes. Materials and methods Individuals of Atlantic salmon (Salmo salar) parr were exposed during 5 days to environmentally relevant concentrations of three representative pharmaceutical compounds with high consumption rates: the analgesic acetaminophen (54.77 ± 34.67 µg L⁻¹), the anticonvulsant carbamazepine (7.85 ± 0.13 µg L⁻¹), and the beta-blocker atenolol (11.08 ± 7.98 µg L⁻¹). Five immature males were selected for transcriptome analysis in brain tissues by means of a 17k salmon cDNA microarray. For this purpose, mRNA was isolated and reverse-transcribed into cDNA which was labeled with fluorescent dyes and hybridized against a common pool to the arrays. Lists of significantly up- and down-regulated candidate genes were submitted to KEGG (Kyoto Encyclopedia of Genes and Genomes) in order to analyze for induced pathways and to evaluate the usefulness of this method in cases of not completely annotated test organisms. Results Exposure during 5 days to environmentally relevant concentrations of the selected pharmaceutical compounds acetaminophen, carbamazepine, and atenolol produced differences in the expression of 659, 700, and 480 candidate genes, respectively. KEGG annotation numbers (KO annotations) were obtained for between 26.57% and 33.33% of these differently expressed genes per treatment in comparison to non-exposure conditions. Pathways that showed to be induced did not always follow previously reported targets or metabolic routes for the employed treatments; however, several other pathways have been found (four or more features) to be significantly induced. Discussion Energy-related pathways have been altered under exposure in all the selected treatments, indicating a possible energy budget leakage due to additional processes resulting from the exposure to environmental contaminants. Observed induction of pathways may indicate additional processes involved in the mode of action of the selected pharmaceuticals which may not have been detected with conventional methods like quantitative PCR in which only suspected features are analyzed punctually for effects. The employment of novel high-throughput screening techniques in combination with global pathway analysis methods, even if the organism is not completely annotated, allows the examination of a much broader range of candidates for potential effects of exposure at the gene level. Conclusions The continuously growing number of annotations of representative species relevant for environmental quality testing is facilitating pathway analysis processes for not completely annotated organisms. KEGG has shown to be a useful tool for the analysis of induced pathways from data generated by microarray techniques with the selected pharmaceutical contaminants acetaminophen, carbamazepine, and atenolol, but further studies have to be carried out in order to determine if a similar expression pattern in terms of fold change quantity and pathways is observed after long-term exposure. Together with the information obtained in this study, it will then be possible to evaluate the potential risk that the continuous release of these compounds may have on the environment and ecosystem functioning.

Gene expression data may be very promising for the classification of toxicant types, but the development and application of transcriptomic-based gene classifiers for environmental toxicological applications are lacking compared to the biomedical sciences. Also, simultaneous classification across a set of toxicant types has not been investigated extensively. In the present study, we determined the transcriptomic response to three types of ubiquitous toxicants exposure in two types of human cell lines (HepG2 and HL-60), which are useful in vitro human model for evaluation of toxic substances that may affect human hepatotoxicity (e.g., polycyclic aromatic hydrocarbon [PAH] and persistent organic pollutant [POP]) and human leukemic myelopoietic proliferation (e.g., volatile organic compound [VOC]). The findings demonstrate characteristic molecular signatures that facilitated discrimination and prediction of the toxicant type. To evaluate changes in gene expression levels after exposure to environmental toxicants, we utilized 18 chemical substances; nine PAH toxicants, six VOC toxicants, and three POP toxicants. Unsupervised gene expression analysis resulted in a characteristic molecular signature for each toxicant group, and combination analysis of two separate multi-classifications indicated 265 genes as surrogate markers for predicting each group of toxicants with 100 % accuracy. Our results suggest that these expression signatures can be used as predictable and discernible surrogate markers for detection and prediction of environmental toxicant exposure. Furthermore, this approach could easily be extended to screening for other types of environmental toxicants.