Interactions of a pesticide/heavy metal mixture in marine bivalves: a transcriptomic assessment

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 import...

Photosynthetic and molecular responses of the marine diatom Thalassiosira pseudonana to triphenyltin exposure

“…Moreover, photosynthesis inhibition, chlorophyll or phycocyanin content, and activity of nitrate reductase have also been applied to study the toxic effect of TPT to algae (Mooney and Patching, 1995;Huang et al, 1996). In recent years, global analyses of genes and proteins have been successfully applied in revealing the effects of chemical contaminants on aquatic organisms (Carvalho and Lettieri, Page 6 of 40 A c c e p t e d M a n u s c r i p t 6 2011; Dondero et al, 2011;Leung et al, 2011). A combination of molecular and physiological approaches can enable us to understand the linkage between responses of organisms at different levels and reveal the toxic mechanism of chemical contaminants (Hayes and Bradfield, 2005).…”

Predicting growth and mortality of bivalve larvae using gene expression and supervised machine learning

“…For example, two ganglioside gm2 activator (GM2A) homologues (-a and -b in Table 4) were also associated with hyperlipidosis syndrome of chemically exposed adult mussels (Dondero et al, 2011). For example, the GM2A was induced in benzo[a]pyrene-treated adult mussels (Brown et al, 2006), involved in lipid metabolism in adult hypoxic oysters (Sussarellu et al, 2010) and nickel-or heat-stressed mussels (Mohamed et al, 2014).…”

Proteomic research in bivalves

“…For instance, combining transcriptomic tools with functional genomics was utilized to study the interactive effects of a pesticide and heavy metal mixture in marine bivalves [85] or the integration of proteomics and transcriptomics to analyze the effects of a neonicotinoid insecticide mixture in the marine mussel M. galloprovicialis [86].…”