Daphnia magna exposed to non-polar narcotics (aliphatic alcohol) and polar narcotics (substituted benzene derivatives)
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ABSTRACT:
ORGANISM(S): Daphnia magna
PROVIDER: GSE52663 | GEO | 2015/11/14
SECONDARY ACCESSION(S): PRJNA229757
REPOSITORIES: GEO
Similar Datasets
Project description:This SuperSeries is composed of the following subset Series: GSE29854: Daphnia magna exposed to narcotics and polar narcotics - aniline GSE29856: Daphnia magna exposed to narcotics and polar narcotics - 4-chloroaniline GSE29857: Daphnia magna exposed to narcotics and polar narcotics - 3,5-dichloroaniline GSE29858: Daphnia magna exposed to narcotics and polar narcotics - 2,3,4-trichloroaniline GSE29862: Daphnia magna exposed to narcotics and polar narcotics - ethanol GSE29864: Daphnia magna exposed to narcotics and polar narcotics - isopropanol GSE29867: Daphnia magna exposed to narcotics and polar narcotics - methanol Refer to individual Series
2012-02-01 | E-GEOD-29993 | biostudies-arrayexpress
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.
2012-02-01 | GSE29867 | GEO
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.
2012-02-01 | GSE29862 | GEO
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.
2012-02-01 | GSE29854 | GEO
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.
2012-02-01 | GSE29864 | GEO
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.
2012-02-01 | GSE29856 | GEO
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.
2012-02-01 | GSE29858 | GEO
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants.
2012-02-01 | GSE29857 | GEO
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants. The hybridization design was a universal reference design (a mixture of aliquots from control and exposed samples), which is recommended when class discovery is the main purpose of the experiment. One of the three biological replicates of each exposure condition was labeled with one dye, the remaining two samples were labeled with the second dye.
2012-02-01 | E-GEOD-29864 | biostudies-arrayexpress
Project description:Structural analogues are assumed to elicit toxicity via similar predominant modes of action (MOAs). Currently, MOA categorization of chemicals in environmental risk assessment is mainly based on the physico-chemical properties of potential toxicants. It is often not known whether such classification schemes are also supported by mechanistic biological data. In this study, the toxic effects of two groups of structural analogues (alcohols and anilines) with predefined MOA (narcotics and polar narcotics) were investigated at different levels of biological organization (gene transcription, energy reserves and growth). Chemical similarity was not indicative of a comparable degree of toxicity and a similar biological response. Categorization of the test chemicals based on the different biological responses (growth, energy use and gene transcription) did not result in a classification of the predefined narcotics versus the predefined polar narcotics. Moreover, gene transcription based clustering profiles were indicative of the observed effects at higher level of biological organization. Furthermore, a small set of classifier genes could be identified that was discriminative for the clustering pattern. These classifier genes co-varied with the organismal and physiological responses. Compared to the physico-chemistry based MOA classification, integrated biological multi-level effect assessment can provide the necessary MOA information that is crucial in high-quality environmental risk assessment. Our findings support the view that transcriptomics tools hold considerable promise to be used in biological response based mechanistic profiling of potential (eco)toxicants. The hybridization design was a universal reference design (a mixture of aliquots from control and exposed samples), which is recommended when class discovery is the main purpose of the experiment. One of the three biological replicates of each exposure condition was labeled with one dye, the remaining two samples were labeled with the second dye.
2012-02-01 | E-GEOD-29867 | biostudies-arrayexpress