首页> 外文期刊>Chemical Senses >Detection of Volatile Indicators of Illicit Substances by the Olfactory Receptors of Drosophila melanogaster
【24h】

Detection of Volatile Indicators of Illicit Substances by the Olfactory Receptors of Drosophila melanogaster

机译:果蝇嗅觉受体检测非法物质的挥发性指标

获取原文
获取原文并翻译 | 示例
           

摘要

Insects can detect a large range of odors with a numerically simple olfactory system that delivers high sensitivity and accurate discrimination. Therefore, insect olfactory receptors hold great promise as biosensors for detection of volatile organic chemicals in a range of applications. The array of olfactory receptor neurons of Drosophila melanogaster is rapidly becoming the best-characterized natural nose. We have investigated the suitability of Drosophila receptors as detectors for volatiles with applications in law enforcement, emergency response, and security. We first characterized responses of the majority of olfactory neuron types to a set of diagnostic odorants. Being thus able to correctly identify neurons, we then screened for responses from 38 different types of neurons to 35 agents. We identified 13 neuron types with responses to 13 agents. As individual Drosophila receptor genes have been mapped to neuron types, we can infer which genes confer responsiveness to the neurons. The responses were confirmed for one receptor by expressing it in a nonresponsive neuron. The fly olfactory system is mainly adapted to detect volatiles from fermenting fruits. However, our findings establish that volatiles associated with illicit substances, many of which are of nonnatural origin, are also detected by Drosophila receptors.
机译:昆虫可以通过数字简单的嗅觉系统检测各种气味,该系统具有很高的灵敏度和准确的判别力。因此,昆虫嗅觉受体作为用于检测多种应用中的挥发性有机化学物质的生物传感器具有广阔的前景。果蝇的嗅觉受体神经元的阵列正在迅速成为特征最丰富的自然鼻子。我们已经研究了果蝇受体作为挥发物检测器的适用性,并将其应用于执法,紧急响应和安全领域。我们首先表征了大多数嗅觉神经元类型对一组诊断增味剂的反应。为了能够正确识别神经元,我们随后筛选了38种不同类型的神经元对35种药物的反应。我们确定了13种神经元对13种药物的反应。由于果蝇受体基因已经映射到神经元类型,我们可以推断出哪些基因对神经元具有响应性。通过在无反应性神经元中表达一种受体,确认了该反应。果蝇嗅觉系统主要适用于检测发酵水果中的挥发物。但是,我们的发现表明,果蝇受体也可以检测到与非法物质相关的挥发物,其中许多是非天然来源的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号