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The effect of chemical information on the spatial distribution of fruit flies: II Parameterization, calibration, and sensitivity.

ABSTRACT: In a companion paper (Lof et al., in Bull. Math. Biol., 2008), we describe a spatio-temporal model for insect behavior. This model includes chemical information for finding resources and conspecifics. As a model species, we used Drosophila melanogaster, because its behavior is documented comparatively well. We divide a population of Drosophila into three states: moving, searching, and settled. Our model describes the number of flies in each state, together with the concentrations of food odor and aggregation pheromone, in time and in two spatial dimensions. Thus, the model consists of 5 spatio-temporal dependent variables, together with their constituting relations. Although we tried to use the simplest submodels for the separate variables, the parameterization of the spatial model turned out to be quite difficult, even for this well-studied species. In the first part of this paper, we discuss the relevant results from the literature, and their possible implications for the parameterization of our model. Here, we focus on three essential aspects of modeling insect behavior. First, there is the fundamental discrepancy between the (lumped) measured behavioral properties (i.e., fruit fly displacements) and the (detailed) properties of the underlying mechanisms (i.e., dispersivity, sensory perception, and state transition) that are adopted as explanation. Detailed quantitative studies on insect behavior when reacting to infochemicals are scarce. Some information on dispersal can be used, but quantitative data on the transition between the three states could not be found. Second, a dose-response relation as used in human perception research is not available for the response of the insects to infochemicals; the behavioral response relations are known mostly in a qualitative manner, and the quantitative information that is available does not depend on infochemical concentration. We show how a commonly used Michaelis-Menten type dose-response relation (incorporating a saturation effect) can be adapted to the use of two different but interrelated stimuli (food odors and aggregation pheromone). Although we use all available information for its parameterization, this model is still overparameterized. Third, the spatio-temporal dispersion of infochemicals is hard to model: Modeling turbulent dispersal on a length scale of 10 m is notoriously difficult. Moreover, we have to reduce this inherently three-dimensional physical process to two dimensions in order to fit in the two-dimensional model for the insects. We investigate the consequences of this dimension reduction, and we demonstrate that it seriously affects the parameterization of the model for the infochemicals. In the second part of this paper, we present the results of a sensitivity analysis. This sensitivity analysis can be used in two manners: firstly, it tells us how general the simulation results are if variations in the parameters are allowed, and secondly, we can use it to infer which parameters need more precise quantification than is available now. It turns out that the short term outcome of our model is most sensitive to the food odor production rate and the fruit fly dispersivity. For the other parameters, the model is quite robust. The dependence of the model outcome with respect to the qualitative model choices cannot be investigated with a parameter sensitivity analysis. We conclude by suggesting some experimental setups that may contribute to answering this question.

SUBMITTER: de Gee M

PROVIDER: S-EPMC2792343 | biostudies-other | 2008 Oct

REPOSITORIES: biostudies-other

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Project description:Toxicokinetics (TK) provides critical information for integrating chemical toxicity and exposure assessments in order to determine potential chemical risk (i.e., the margin between toxic doses and plausible exposures). For thousands of chemicals that are present in our environment, in vivo TK data are lacking. The publicly available R package "httk" (version 1.8, named for "high throughput TK") draws from a database of in vitro data and physico-chemical properties in order to run physiologically-based TK (PBTK) models for 553 compounds. The PBTK model parameters include tissue:plasma partition coefficients (Kp) which the httk software predicts using the model of Schmitt (Toxicol In Vitro 22 (2):457-467, 2008). In this paper we evaluated and modified httk predictions, and quantified confidence using in vivo literature data. We used 964 rat Kp measured by in vivo experiments for 143 compounds. Initially, predicted Kp were significantly larger than measured Kp for many lipophilic compounds (log10 octanol:water partition coefficient > 3). Hence the approach for predicting Kp was revised to account for possible deficiencies in the in vitro protein binding assay, and the method for predicting membrane affinity was revised. These changes yielded improvements ranging from a factor of 10 to nearly a factor of 10,000 for 83 Kp across 23 compounds with only 3 Kp worsening by more than a factor of 10. The vast majority (92%) of Kp were predicted within a factor of 10 of the measured value (overall root mean squared error of 0.59 on log10-transformed scale). After applying the adjustments, regressions were performed to calibrate and evaluate the predictions for 12 tissues. Predictions for some tissues (e.g., spleen, bone, gut, lung) were observed to be better than predictions for other tissues (e.g., skin, brain, fat), indicating that confidence in the application of in silico tools to predict chemical partitioning varies depending upon the tissues involved. Our calibrated model was then evaluated using a second data set of human in vivo measurements of volume of distribution (Vss) for 498 compounds reviewed by Obach et al. (Drug Metab Dispos 36(7):1385-1405, 2008). We found that calibration of the model improved performance: a regression of the measured values as a function of the predictions has a slope of 1.03, intercept of - 0.04, and R2 of 0.43. Through careful evaluation of predictive methods for chemical partitioning into tissues, we have improved and calibrated these methods and quantified confidence for TK predictions in humans and rats.

Project description:BackgroundThe olive fruit fly (Bactrocera oleae) is the most destructive pest of the olive cultivation worldwide causing significant production losses and olive fruit impoverishment, as its larvae feed exclusively on the olive fruit. Reproductive and sexual behavior, as well as host-plant recognition of the fly, are highly dependent on its chemosensory system. Therefore, exploring the role of genes that play a critical role in olfaction, could reveal potential molecular targets that determine species-specific features on chemical communication and could be used to impair sexual behavior.ResultsIn this study we identified the gene that encodes the conserved olfactory co-receptor Orco (Odorant receptor co-receptor), which interacts with all divergent insect odorant receptors, and investigated how disruption of its expression affects chemoreception. We initially searched the expression profile of Bo-Orco in both sexes during sexual maturation, as well as pre- and post-mating communication by relative quantitative real time PCR (qRT-PCR) analysis suggesting that Bo-Orco was abundantly expressed in sexually mature adults. We further investigated the functional role of Bo-Orco in mating and oviposition behavior via transient gene silencing that was performed through in vivo dsRNA hemolymph injections in sexually mature flies 7 days after eclosion. Orco-knockdown phenotypes in both sexes showed reduced copulation rates in mating competitiveness tests, possibly through impaired olfactory-mediated detection of sex pheromone. In addition, oviposition was significantly inhibited in dsRNA-Orco injected females in a post-mating behavior test.ConclusionsOur results demonstrate that Orco plays a crucial role in the reproductive behavior of the olive fruit fly, since pre- and post-mating processes were affected. This is the first report in the olive fruit fly that links the chemosensory pathway with the mating behavior and the reproductive potential at a molecular basis, rendering this gene a potential target for the improvement of the olive fruit fly population control techniques.

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The effect of chemical information on the spatial distribution of fruit flies: II Parameterization, calibration, and sensitivity.

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