US Arid-Land Agricultural Research Center, USDA-ARS, Maricopa, AZ 85138, USA.
J Chem Ecol. 2013 Aug;39(8):1081-9. doi: 10.1007/s10886-013-0328-6. Epub 2013 Jul 30.
Dose-response curves of the effects of semiochemicals on neurophysiology and behavior are reported in many articles in insect chemical ecology. Most curves are shown in figures representing points connected by straight lines, in which the x-axis has order of magnitude increases in dosage vs. responses on the y-axis. The lack of regression curves indicates that the nature of the dose-response relationship is not well understood. Thus, a computer model was developed to simulate a flux of various numbers of pheromone molecules (10(3) to 5 × 10(6)) passing by 10(4) receptors distributed among 10(6) positions along an insect antenna. Each receptor was depolarized by at least one strike by a molecule, and subsequent strikes had no additional effect. The simulations showed that with an increase in pheromone release rate, the antennal response would increase in a convex fashion and not in a logarithmic relation as suggested previously. Non-linear regression showed that a family of kinetic formation functions fit the simulated data nearly perfectly (R(2) >0.999). This is reasonable because olfactory receptors have proteins that bind to the pheromone molecule and are expected to exhibit enzyme kinetics. Over 90 dose-response relationships reported in the literature of electroantennographic and behavioral bioassays in the laboratory and field were analyzed by the logarithmic and kinetic formation functions. This analysis showed that in 95% of the cases, the kinetic functions explained the relationships better than the logarithmic (mean of about 20% better). The kinetic curves become sigmoid when graphed on a log scale on the x-axis. Dose-catch relationships in the field are similar to dose-EAR (effective attraction radius, in which a spherical radius indicates the trapping effect of a lure) and the circular EARc in two dimensions used in mass trapping models. The use of kinetic formation functions for dose-response curves of attractants, and kinetic decay curves for inhibitors, will allow more accurate predictions of insect catch in monitoring and control programs.
在昆虫化学生态学的许多文章中都有报道关于信息素对神经生理学和行为影响的剂量-反应曲线。大多数曲线以图形形式表示，连接各点的直线表示 x 轴上剂量的数量级增加与 y 轴上的响应之间的关系。缺乏回归曲线表明，对剂量-反应关系的性质还没有很好的理解。因此，开发了一种计算机模型来模拟各种数量的信息素分子（10(3) 到 5×10(6)) 通过分布在昆虫触角上的 10(4)个受体流过的情况，这些受体的数量为 10(6)。每个受体至少被一个分子的冲击去极化，随后的冲击没有额外的效果。模拟结果表明，随着信息素释放率的增加，触角的反应将以凸形方式增加，而不是以前所建议的对数关系。非线性回归表明，一组动力学形成函数几乎完全拟合模拟数据（R(2)>0.999）。这是合理的，因为嗅觉受体具有与信息素分子结合的蛋白质，预计会表现出酶动力学。通过对数和动力学形成函数对文献中报道的 90 多个在实验室和现场进行的触角电生理和行为生物测定的剂量-反应关系进行了分析。该分析表明，在 95%的情况下，动力学函数比对数函数更好地解释了这些关系（平均约好 20%）。当在 x 轴上以对数刻度绘制时，动力学曲线呈 S 形。野外的剂量-捕获关系类似于剂量-EAR（有效吸引力半径，其中一个球形半径表示诱饵的诱捕效果）和二维中用于大规模诱捕模型的圆形 EARc。使用动力学形成函数来表示引诱剂的剂量-反应曲线，以及抑制剂的动力学衰减曲线，将能够更准确地预测监测和控制计划中的昆虫捕获量。
