Application of physiologically based modelling and transcriptomics to probe the systems toxicology of aldicarb for Caenorhabditis elegans (Maupas 1900).

The toxicity of aldicarb on movement, life cycle, population growth rate and resource allocation, and the gene expression changes underpinning these effects, were investigated for Caenorhabditis elegans. A clear effect of aldicarb on nematode movement was found suggesting that this pesticide acts as a neurotoxicant. Aldicarb also had an effect on life cycle traits including low concentration life-span extension; high concentration brood size reduction and a high concentration extension of time to first egg. All life-cycle and growth data were integrated into a biology-based model (DEBtox) to characterise aldicarb effects on life-history traits, resource allocation and population growth rate within a single modelling framework. The DEBtox fits described concentration dependent effects on individual traits and population growth rate and indicated that the most probable mechanism of action of the pesticide was an increase in energy demands for somatic and reproductive tissue maintenance. Transcriptomic profiling indicated that aldicarb was associated with changes in amino acid metabolism, DNA structure, fatty acid metabolism and cytochrome P450 mediated xenobiotic metabolism. The changes in the amino acid and fatty acid pathways suggest an effect of aldicarb on protein integrity; while effects on DNA suggests that aldicarb influence DNA morphology or replication. Both these effects have the potential to incur increased costs for structural maintenance of macromolecules. These effects, coupled to the effect on biotransformation enzymes also seen, represent the materialisation of the maintenance costs indicated by DEBtox modelling.

Linking toxicant physiological mode of action with induced gene expression changes in Caenorhabditis elegans.

BACKGROUND: Physiologically based modelling using DEBtox (dynamic energy budget in toxicology) and transcriptional profiling were used in Caenorhabditis elegans to identify how physiological modes of action, as indicated by effects on system level resource allocation were associated with changes in gene expression following exposure to three toxic chemicals: cadmium, fluoranthene (FA) and atrazine (AZ). RESULTS: For Cd, the physiological mode of action as indicated by DEBtox model fitting was an effect on energy assimilation from food, suggesting that the transcriptional response to exposure should be dominated by changes in the expression of transcripts associated with energy metabolism and the mitochondria. While evidence for effect on genes associated with energy production were seen, an ontological analysis also indicated an effect of Cd exposure on DNA integrity and transcriptional activity. DEBtox modelling showed an effect of FA on costs for growth and reproduction (i.e. for production of new and differentiated biomass). The microarray analysis supported this effect, showing an effect of FA on protein integrity and turnover that would be expected to have consequences for rates of somatic growth. For AZ, the physiological mode of action predicted by DEBtox was increased cost for maintenance. The transcriptional analysis demonstrated that this increase resulted from effects on DNA integrity as indicated by changes in the expression of genes chromosomal repair. CONCLUSIONS: Our results have established that outputs from process based models and transcriptomics analyses can help to link mechanisms of action of toxic chemicals with resulting demographic effects. Such complimentary analyses can assist in the categorisation of chemicals for risk assessment purposes.

'Systems toxicology' approach identifies coordinated metabolic responses to copper in a terrestrial non-model invertebrate, the earthworm Lumbricus rubellus.

BACKGROUND: New methods are needed for research into non-model organisms, to monitor the effects of toxic disruption at both the molecular and functional organism level. We exposed earthworms (Lumbricus rubellus Hoffmeister) to sub-lethal levels of copper (10-480 mg/kg soil) for 70 days as a real-world situation, and monitored both molecular (cDNA transcript microarrays and nuclear magnetic resonance-based metabolic profiling: metabolomics) and ecological/functional endpoints (reproduction rate and weight change, which have direct relevance to population-level impacts). RESULTS: Both of the molecular endpoints, metabolomics and transcriptomics, were highly sensitive, with clear copper-induced differences even at levels below those that caused a reduction in reproductive parameters. The microarray and metabolomic data provided evidence that the copper exposure led to a disruption of energy metabolism: transcripts of enzymes from oxidative phosphorylation were significantly over-represented, and increases in transcripts of carbohydrate metabolising enzymes (maltase-glucoamylase, mannosidase) had corresponding decreases in small-molecule metabolites (glucose, mannose). Treating both enzymes and metabolites as functional cohorts led to clear inferences about changes in energetic metabolism (carbohydrate use and oxidative phosphorylation), which would not have been possible by taking a 'biomarker' approach to data analysis. CONCLUSION: Multiple post-genomic techniques can be combined to provide mechanistic information about the toxic effects of chemical contaminants, even for non-model organisms with few additional mechanistic toxicological data. With 70-day no-observed-effect and lowest-observed-effect concentrations (NOEC and LOEC) of 10 and 40 mg kg-1 for metabolomic and microarray profiles, copper is shown to interfere with energy metabolism in an important soil organism at an ecologically and functionally relevant level.