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Neural coding of binary mixtures in a structurally related odorant pair.

ABSTRACT: The encoding of odorant mixtures by olfactory sensory neurons depends on molecular interactions at peripheral receptors. However, the pharmacological basis of these interactions is not well defined. Both competitive and noncompetitive mechanisms of receptor binding and activation, or suppression, could contribute to coding. We studied this by analyzing responses of olfactory bulb glomeruli evoked by a pair of structurally related odorants, eugenol (EG) and methyl isoeugenol (MIEG). Fluorescence imaging in synaptopHluorin (spH) mice revealed that EG and MIEG evoked highly overlapped glomerular inputs, increasing the likelihood of mixture interactions. Glomerular responses to binary mixtures of EG and MIEG mostly showed hypoadditive interactions at intermediate and high odorant concentrations, with a few near threshold responses showing hyperadditivity. Dose-response profiles were well fitted by a model of two odorants competitively binding and activating a shared receptor linked to a non-linear transduction cascade. We saw no evidence of non-competitive mechanisms.

SUBMITTER: Cruz G

PROVIDER: S-EPMC3564033 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Neural coding of binary mixtures in a structurally related odorant pair.

Cruz Georgina G Lowe Graeme G

Scientific reports 20130205

The encoding of odorant mixtures by olfactory sensory neurons depends on molecular interactions at peripheral receptors. However, the pharmacological basis of these interactions is not well defined. Both competitive and noncompetitive mechanisms of receptor binding and activation, or suppression, could contribute to coding. We studied this by analyzing responses of olfactory bulb glomeruli evoked by a pair of structurally related odorants, eugenol (EG) and methyl isoeugenol (MIEG). Fluorescence ...[more]

PMID: 23386975

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Project description:The recent development of a custom cDNA microarray platform for one of thé standard organisms in aquatic toxicology, Daphnia magna, opened up new ways to mechanistic insights of toxicological responses. In this study, gene expression and (sub)organismal responses (Cellular Energy Allocation, growth) were assayed after short-term waterborne metal exposure. Microarray analysis of Ni-exposed daphnids revealed several affected functional gene classes, of which the largest ones were involved in different metabolic processes (mainly protein and chitin related processes), cuticula turnover, transport and signal transduction. Furthermore, genes involved in oxygen transport and heme metabolism (hemoglobin, δ-aminolevilunate synthase) were down-regulated. Applying a Partial Least Squares regression on nickel fingerprints and biochemical (sub)organismal parameters revealed a set of co-varying genes (hemoglobin, RNA terminal phosphate cyclase, a ribosomal protein and an “unknown” gene fragment). An inverse relationship was seen between the mRNA expression levels of different cuticula proteins and available energy reserves. In addition to the nickel exposure, daphnids were exposed to binary mixtures of nickel and cadmium or nickel and lead. Using multivariate analysis techniques, the mixture gene expression fingerprints (Ni2++Cd2+, Ni2++Pb2+) were compared to those of the single metal treatments (Ni2+, Cd2+, Pb2+). It was hypothesized that the molecular fingerprints of the mixtures would be additive combinations of the gene expression profiles of the individual compounds present in the mixture. However, our results clearly showed additionally affected pathways after mixture treatment (e.g. additional affected genes involved in carbohydrate catabolic processes and proteolysis), indicating interactive molecular responses which are not merely the additive sum of the individual metals. These findings, although indicative of the complex nature of mixture toxicity evaluation, underline the potential of a toxicogenomics approach in gaining more mechanistic information on the effects of single compounds and mixtures.

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Neural coding of binary mixtures in a structurally related odorant pair.

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Neural coding of binary mixtures in a structurally related odorant pair.

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