ArticleEcotoxicology (London, England)2018
Comparative analysis of transcriptomic responses to sub-lethal levels of six environmentally relevant pesticides in Saccharomyces cerevisiae.
Article in Ecotoxicology (London, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 16 citations in OpenAlex.
- Deciphering the recent trends in pesticide bioremediation using genome editing and multi-omics approaches: a review.World journal of microbiology & biotechnology · 2023Review
- Omics Approaches to Pesticide Biodegradation.Current microbiology · 2020Review
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
Accidental spills and misuse of pesticides may lead to current and/or legacy environmental contamination and may pose concerns regarding possible risks towards non-target microbes and higher eukaryotes in ecosystems. The present study was aimed at comparing transcriptomic responses to effects of sub-lethal levels of six environmentally relevant pesticide active substances in the Saccharomyces cerevisiae eukaryotic model. The insecticide carbofuran, the fungicide pyrimethanil and the herbicides alachlor, S-metolachlor, diuron and methyl(4-chloro-2-methylphenoxy)acetate were studied. Some are currently used agricultural pesticides, while others are under restricted utilization or banned in Europe and/or North America albeit being used in other geographical locations. In the present work transcriptional profiles representing genome-wide responses in a standardized yeast population upon 2 h of exposure to concentrations of each compound exerting equivalent toxic effects, i.e., inhibition of growth by 20% relative to the untreated control cells, were examined. Hierarchical clustering and Venn analyses of the datasets of differentially expressed genes pointed out transcriptional patterns distinguishable between the six active substances. Functional enrichment analyses allowed predicting mechanisms of pesticide toxicity and response to pesticide stress in the yeast model. In general, variations in transcript numbers of selected genes assessed by Real-Time quantitative reverse transcription polymerase chain reaction confirmed microarray data and correlated well with growth inhibitory effects. A possible biological relevance of mechanistic predictions arising from these comparative transcriptomic analyses is discussed in the context of better understanding potential modes of action and adverse side-effects of pesticides.
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Registered trials
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