Alachlor has been a commonly applied herbicide and is a substance of ecotoxicological concern. The present study aims to identify molecular biomarkers in the eukaryotic model Saccharomyces cerevisiae that can be used to predict potential cytotoxic effects of alachlor, while providing new mechanistic clues with possible relevance for experimentally less accessible eukaryotes. It focuses on genome-wide expression profiling in a yeast population in response to two exposure scenarios exerting effects from slight to moderate magnitude at phenotypic level. In particular, 100 and 264 genes, respectively, were found as differentially expressed on a 2-h exposure of yeast cells to the lowest observed effect concentration (110 mg/L) and the 20% inhibitory concentration (200 mg/L) of alachlor, in comparison with cells not exposed to the herbicide. The datasets of alachlor-responsive genes showed functional enrichment in diverse metabolic, transmembrane transport, cell defense, and detoxification categories. In general, the modifications in transcript levels of selected candidate biomarkers, assessed by quantitative reverse transcriptase polymerase chain reaction, confirmed the microarray data and varied consistently with the growth inhibitory effects of alachlor. Approximately 16% of the proteins encoded by alachlor-differentially expressed genes were found to share significant homology with proteins from ecologically relevant eukaryotic species. The biological relevance of these results is discussed in relation to new insights into the potential adverse effects of alachlor in health of organisms from ecosystems, particularly in worst-case situations such as accidental spills or careless storage, usage, and disposal.

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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