ArticleBMC genomics2011
Interactions of a pesticide/heavy metal mixture in marine bivalves: a transcriptomic assessment.
Article in BMC genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 104 citations in OpenAlex.
- Assessment of Effects of Discharged Firefighting Water on the Nemunas River Based on Biomarker Responses.Toxics · 2025Article
- Core histone families of mollusca: systematic identification, evolutionary insights, and functional analysis.BMC genomics · 2025Article
- Concentrations and transportation of metal and organochlorine pollutants in vegetables and risk assessment of human exposure in rural, urban and industrial environments (Bouches-du-Rhône, France).Environmental science and pollution research international · 2021Article
- Neurotoxicity in Marine Invertebrates: An Update.Biology · 2021Review
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- Metabolite Changes in an Estuarine Annelid Following Sublethal Exposure to a Mixture of Zinc and Boscalid.Metabolites · 2019Article
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- Synergistic Effects of Heavy Metals and Pesticides in Living Systems.Frontiers in chemistry · 2017Review
- Additivity and Interactions in Ecotoxicity of Pollutant Mixtures: Some Patterns, Conclusions, and Open Questions.Toxics · 2015Review
- Effects of Carbon Nanotube Environmental Dispersion on an Aquatic Invertebrate, Hirudo medicinalis.PloS one · 2015Article
- Molecular and Cellular Effects Induced in Mytilus galloprovincialis Treated with Oxytetracycline at Different Temperatures.PloS one · 2015Article
- Unexpected toxic interactions in the freshwater amphipod Gammarus pulex (L.) exposed to binary copper and nickel mixtures.Environmental science and pollution research international · 2014Article
- Bivalve omics: state of the art and potential applications for the biomonitoring of harmful marine compounds.Marine drugs · 2013Review
- Transcriptional responses indicate attenuated oxidative stress in the springtail Folsomia candida exposed to mixtures of cadmium and phenanthrene.Ecotoxicology (London, England) · 2013Article
- Transcriptional response of the mussel Mytilus galloprovincialis (Lam.) following exposure to heat stress and copper.PloS one · 2013Article
- Effects of nickel, chlorpyrifos and their mixture on the Dictyostelium discoideum proteome.International journal of molecular sciences · 2012Article
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Corrections and comments
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Authors and funding
6 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMixtures of chemicals present in aquatic environments may elicit toxicity due to additive or synergistic effects among the constituents or, vice versa, the adverse outcome may be reduced by antagonistic interactions. Deviations from additivity should be explained either by the perturbations of toxicokinetic parameters and/or chemical toxicodynamics. We addressed this important question in marine mussels exposed subchronically to a binary mixture made of two wide-spread pollutants: the heavy metal nickel and the organic phosphorus pesticide Chlorpyrifos. To this aim, we carried out in tissues of Mytius galloprovincialis (Lam) a systems approach based on the evaluation and integration of different disciplines, i.e. high throughput gene expression profiling, functional genomics, stress biomakers and toxicokinetics.
resultsCellular and tissue biomarkers, viz. digestive gland lysosomal membrane stability, lysosomal/cytosol volume ratio, neutral lipid content and gill acetylcholinesterase activity were, in general, altered by either the exposure to nickel and Chlorpyrifos. However, their joint action rendered (i) an overall decrease of the stress syndrome level, as evaluated through an expert system integrating biomarkers and (ii) statistically significant antagonistic deviations from the reference model systems to predict mixture toxicity. While toxicokinetic modeling did not explain mixture interactions, gene expression profiling and further Gene Ontology-based functional genomics analysis provided clues that the decrement of toxicity may arise from the development of specific toxicodynamics. Multivariate statistics of microarray data (238 genes in total, representing about 14% of the whole microarray catalogue) showed two separate patterns for the single chemicals: the one belonging to the heavy metal -135 differentially expressed genes (DEGs) was characterized by the modulation of transcript levels involved in nucleic acid metabolism, cell proliferation and lipid metabolic processes. Chlorpyrifos exposure (43 DEGs) yielded a molecular signature which was biased towards carbohydrate catabolism (indeed, chitin metabolism) and developmental processes. The exposure to the mixture (103 DEGs) elicited a composite complex profile which encompassed the core properties of the pesticide but also a relevant set of unique features. Finally, the relative mRNA abundance of twelve genes was followed by Q-PCR to either confirm or complement microarray data. These results, in general, were compatible with those from arrays and indeed confirmed the association of the relative abundance of two GM-2 ganglioside activator genes in the development of the hyperlipidosis syndrome observed in digestive gland lysosomes of single chemical exposed mussels.
conclusionThe transcriptomic assessment fitted with biological data to indicate the occurrence of different toxicodynamic events and, in general, a decrease of toxicity, driven by the mitigation or even abolition of lysosomal responses. Furthermore, our results emphasized the importance of the application of mechanistic approaches and the power of systems assessment to study toxicological responses in ecologically relevant organisms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.