Assessing the mutagenic and estrogenic effect potential of pharmaceuticals and of their transformation products. Implications in the gene expression profiling
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE77215 | GEO | 2016/09/13
SECONDARY ACCESSION(S): PRJNA309760
REPOSITORIES: GEO
Similar Datasets
Project description:The goals of this study are to use SWATH-MS to detect bacterial proteomic profiles of wild-type Acinetobacter baylyi ADP1, and its protein response under the exposure of non-antibiotic pharmaceuticals, including ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and iopromide. The concentrations were 0.5 mg/L for ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and 1.0 mg/L for iopromide. The group without dosing pharmaceutical was the control group. Each concentration was conducted in triplicate. By comparing the proteomic profiles of experimental groups and control group, the effects of non-antibiotic pharmaceuticals on translational levels can be revealed.
2020-05-22 | PXD016798 | Pride
Project description:Proteomics to decipher the cocktail effects of three pharmaceuticals (diclofenac, carbamazepine and venlafaxine) as a mixture on the digestive gland of male mussels Mytilus galloprovincialis.
2023-12-21 | PXD045957 | Pride
Project description:BACKGOUND: Drinking water can be contaminated with pharmaceuticals. However, it is uncertain whether this contamination can have harmful consequences for the liver, especially in the context of obesity. OBJECTIVES: To determine whether chronic, low dose exposure to pharmaceuticals could have deleterious effects in livers of lean and obese mice. METHODS: Lean and ob/ob male mice (5-week-old) were treated for 4 months with a mixture of 11 drugs (acetaminophen, caffeine, carbamazepine, cotinine, diclofenac, erythromycin, ibuprofen, phenazone, roxithromycin, salicylic acid and sulfamethoxazole) provided in drinking water at a concentration of 1 mg/L (for each drug). At the end of the treatment, investigations were performed in liver and plasma. RESULTS: Some liver and plasma abnormalities were observed in ob/ob mice treated with the cocktail containing 1 mg/L of each drug. For this dosage, a gene expression analysis by microarray showed altered expression of circadian genes (e.g. Bmal1, Dbp, Cry1) in lean and obese mice. RT-qPCR analyses carried out in all groups of animals indicated that expression of 8 different circadian genes was significantly modified in a dose-dependent manner. For some genes, a significant modification was observed for dosages as low as 100-1,000 ng/L. Drug mixture and obesity presented an additive effect on circadian gene expression. These data were confirmed in an independent study performed in female mice. CONCLUSIONS: Chronic, low dose exposure to pharmaceuticals disturbed hepatic expression of circadian genes, especially in obese mice. Because some of the 11 drugs can be found in the drinking water at such concentrations (e.g. acetaminophen, carbamazepine, ibuprofen) our data could be relevant in environmental toxicology, in particular for obese individuals exposed to these contaminants.
2014-03-04 | GSE49195 | GEO
Project description:BACKGOUND: Drinking water can be contaminated with pharmaceuticals. However, it is uncertain whether this contamination can have harmful consequences for the liver, especially in the context of obesity. OBJECTIVES: To determine whether chronic, low dose exposure to pharmaceuticals could have deleterious effects in livers of lean and obese mice. METHODS: Lean and ob/ob male mice (5-week-old) were treated for 4 months with a mixture of 11 drugs (acetaminophen, caffeine, carbamazepine, cotinine, diclofenac, erythromycin, ibuprofen, phenazone, roxithromycin, salicylic acid and sulfamethoxazole) provided in drinking water at a concentration of 1 mg/L (for each drug). At the end of the treatment, investigations were performed in liver and plasma. RESULTS: Some liver and plasma abnormalities were observed in ob/ob mice treated with the cocktail containing 1 mg/L of each drug. For this dosage, a gene expression analysis by microarray showed altered expression of circadian genes (e.g. Bmal1, Dbp, Cry1) in lean and obese mice. RT-qPCR analyses carried out in all groups of animals indicated that expression of 8 different circadian genes was significantly modified in a dose-dependent manner. For some genes, a significant modification was observed for dosages as low as 100-1,000 ng/L. Drug mixture and obesity presented an additive effect on circadian gene expression. These data were confirmed in an independent study performed in female mice. CONCLUSIONS: Chronic, low dose exposure to pharmaceuticals disturbed hepatic expression of circadian genes, especially in obese mice. Because some of the 11 drugs can be found in the drinking water at such concentrations (e.g. acetaminophen, carbamazepine, ibuprofen) our data could be relevant in environmental toxicology, in particular for obese individuals exposed to these contaminants. C57BL/6J lean and ob/ob male mice (5-week-old) were treated for 4 months with a mixture of 11 drugs provided in drinking water at a concentration of 1 mg/L (for each drug). 4 groups were designed: untreated versus treated WT and ob/ob mice (n=6 mice per group).
2014-03-04 | E-GEOD-49195 | biostudies-arrayexpress
Project description:The goals of this study are to use SWATH-MS to detect bacterial proteomic profiles of E. coli K-12 LE392 with conjugative RP4 plasmid, P. putida KT2440, and their protein response under the exposure of six kinds of non-antibiotic pharmaceuticals, i.e., ibuprofen (ibu), naproxen (nap), gemfibrozil (gem), iopromide (iop), diclofenac (dic), propanolol (pro). Each treatment condition was conducted in triplicate. By comparing the proteomic profiles of experimental groups and control group, the effects of these non-antibiotic pharmaceuticals on translational levels can be revealed.
2022-02-15 | PXD012642 | Pride
Project description:The present study explores the potential of compound-specific gene-upregulation profiles in the ubiquitous purple nonsulfur bacterium Rhodospirillum rubrum S1H as biomarkers for exposure to surface water contaminants, i.e. high production-volume pharmaceuticals. Even though the pharmaceuticals [i.e., acetylsalicylic acid (ASA), diclofenac (DCF), and 17M-NM-1-ethinylestradiol (EE2)] did not affect the bacterial growth kinetics at environmentally-relevant concentrations (86nM), whole-genome microarray analyses revealed the upregulation of 128, 49, and 47 genes upon exposure to DCF, ASA, and EE2, respectively. A strong overlap (27-48%) was observed between transcriptional responses, but a total of 93 genes were found to be upregulated in a compound-specific manner. Hence, we were able to identify 74 and 15 potential biomarker genes for DCF and ASA, respectively. DCF specifically induced genes involved mainly in stress response, signal transduction, response regulation, the electron transport chain, and transcription, while ASA specifically induced genes predominantly involved in signal transduction, response regulation, and trans-membrane translocation. Moreover, our findings validated triclosan-specific biomarker genes that were identified previously. As only 4 genes were specifically-upregulated for EE2, no representative biomarker profile was identified. This study illustrates that a pollutant-specific molecular response can be generated in R. rubrum S1H, which could become a relevant model-microorganism to screen for the ecological impact of surface water contaminants in situ. KEYWORDS: environmental impact studies, risk assessment, biosensor, wastewater, micropollutant, aspirin Two-condition experiments. Comparing samples after induction of three pharmaceuticals each with a non-induced samples. Biological triplicate. Each array contains 3 technical replicates.
2013-08-23 | E-GEOD-23794 | biostudies-arrayexpress
Project description:The present study explores the potential of compound-specific gene-upregulation profiles in the ubiquitous purple nonsulfur bacterium Rhodospirillum rubrum S1H as biomarkers for exposure to surface water contaminants, i.e. high production-volume pharmaceuticals. Even though the pharmaceuticals [i.e., acetylsalicylic acid (ASA), diclofenac (DCF), and 17α-ethinylestradiol (EE2)] did not affect the bacterial growth kinetics at environmentally-relevant concentrations (86nM), whole-genome microarray analyses revealed the upregulation of 128, 49, and 47 genes upon exposure to DCF, ASA, and EE2, respectively. A strong overlap (27-48%) was observed between transcriptional responses, but a total of 93 genes were found to be upregulated in a compound-specific manner. Hence, we were able to identify 74 and 15 potential biomarker genes for DCF and ASA, respectively. DCF specifically induced genes involved mainly in stress response, signal transduction, response regulation, the electron transport chain, and transcription, while ASA specifically induced genes predominantly involved in signal transduction, response regulation, and trans-membrane translocation. Moreover, our findings validated triclosan-specific biomarker genes that were identified previously. As only 4 genes were specifically-upregulated for EE2, no representative biomarker profile was identified. This study illustrates that a pollutant-specific molecular response can be generated in R. rubrum S1H, which could become a relevant model-microorganism to screen for the ecological impact of surface water contaminants in situ. KEYWORDS: environmental impact studies, risk assessment, biosensor, wastewater, micropollutant, aspirin
2013-08-23 | GSE23794 | GEO
Project description:The endocrine disrupting pharmaceuticals, non-steroidal anti-inflammatory drugs (NSAIDs) and 17α-ethinyl-estradiol (EE2), are among the most relevant molecules found in aquatic ecosystems, surface and drinking water due to their incomplete removal by wastewater treatment plants. Exposure to therapeutic doses has a negative impact on gonadal development and fertility in rodent models; however, the effects of their chronic exposure at lower doses are not known. In this study, we investigated the impact of chronic exposure to a mixture containing ibuprofen, 2hydroxy-ibuprofen, diclofenac, and EE2 at two environmentally relevant doses (added to the drinking water from fetal life, 8.5 dpc, until sexual maturity) on the reproductive tract in F1 exposed mice and their F2 offspring. In adult F1 and F2 animals, chronic exposure to low environmental doses of IBU, 2hydroxy-IBU, DCF, and EE2 mixtures, affected reproductive organ maturation, estrous cyclicity (in females), spermiogenesis (in males), and some sperm parameters in F2 males. Transcriptomics further revealed significant changes in gene expression patterns and associated pathways, underlying the modified mechanisms on testis and ovarian physiology and on germ cells, the precursors of gametes. Consequently, fertility of F1 male and female animals exposed to the higher dose of pharmaceuticals and that of their F2 offsprings, measured through the total number of pups and the time between litters, was affected after 5 months of age. This suggested that exposure to these drug cocktails has an inter-generational impact.
2024-01-01 | GSE235393 | GEO
Project description:The goals of this study are to use Next-generation sequencing (NGS) to detect bacterial mRNA profiles of wild-type A.baylyi ADP1, and its mRNA response under the exposure of six non-antibiotic pharmaceuticals, including ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and iopromide. The concentrations were 0.5 mg/L for ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and 1.0 mg/L for iopromide. The group without dosing pharmaceutical was the control group. Each concentration was conducted in triplicate. By comparing the mRNA profiles of experimental groups and control group, the effects of these six non-antibiotic pharmaceuticals on transcriptional levels can be revealed. Illumina HiSeq 2500 was applied. The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the A.baylyi ADP1 reference genome (NC_005966.1), using SeqAlto (version 0.5). Cufflinks (version 2.2.1) to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell cultures. The statistical analyses and visualization were conducted using CummeRbund package in R. (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.
2020-07-22 | GSE142061 | GEO
Project description:The goals of this study are to use Next-generation sequencing (NGS) to detect bacterial mRNA profiles of wild-type E. coli K-12 LE392, P. putida KT2440 and IncPα RP4 plasmid, and their mRNA response under the exposure of six non-antibiotic pharmaceuticals, including ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and iopromide. The concentrations were 0.5 mg/L for ibuprofen, naproxen, gemfibrozil, diclofenac, propanolol, and 1.0 mg/L for iopromide. The group without dosing pharmaceutical was the control group. Each concentration was conducted in triplicate. By comparing the mRNA profiles of experimental groups and control group, the effects of these six non-antibiotic pharmaceuticals on transcriptional levels can be revealed. Illumina HiSeq 2500 was applied. The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the E. coli reference genome (NC_000913), P.putida reference genome (NC_002947), and IncPα plasmid reference genome (NC_00) using SeqAlto (version 0.5). Cufflinks (version 2.2.1) was used to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell cultures. The statistical analyses and visualization were conducted using CummeRbund package in R (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.
2021-09-01 | GSE130562 | GEO