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The banana code—natural blend processing in the olfactory circuitry of Drosophila melanogaster

机译:香蕉代码-果蝇嗅觉回路中的自然融合处理

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摘要

Odor information is predominantly perceived as complex odor blends. For Drosophila melanogaster one of the most attractive blends is emitted by an over-ripe banana. To analyze how the fly's olfactory system processes natural blends we combined the experimental advantages of gas chromatography and functional imaging (GC-I). In this way, natural banana compounds were presented successively to the fly antenna in close to natural occurring concentrations. This technique allowed us to identify the active odor components, use these compounds as stimuli and measure odor-induced Ca2+ signals in input and output neurons of the Drosophila antennal lobe (AL), the first olfactory neuropil. We demonstrate that mixture interactions of a natural blend are very rare and occur only at the AL output level resulting in a surprisingly linear blend representation. However, the information regarding single components is strongly modulated by the olfactory circuitry within the AL leading to a higher similarity between the representation of individual components and the banana blend. This observed modulation might tune the olfactory system in a way to distinctively categorize odor components and improve the detection of suitable food sources. Functional GC-I thus enables analysis of virtually any unknown natural odorant blend and its components in their relative occurring concentrations and allows characterization of neuronal responses of complete neural assemblies. This technique can be seen as a valuable complementary method to classical GC/electrophysiology techniques, and will be a highly useful tool in future investigations of insect-insect and insect-plant chemical interactions.
机译:气味信息主要被认为是复杂的气味混合物。对于果蝇而言,最成熟的混合物之一是成熟的香蕉散发出来的。为了分析果蝇的嗅觉系统如何处理天然混合物,我们结合了气相色谱和功能成像(GC-I)的实验优势。这样,天然香蕉化合物就以接近自然发生的浓度连续出现在飞行天线上。这项技术使我们能够识别活性气味成分,使用这些化合物作为刺激并测量果蝇触角叶(AL)(第一个嗅觉神经纤维)的输入和输出神经元中的气味诱导的Ca 2 + 信号。 。我们证明了天然混合物的混合物相互作用非常罕见,并且仅在AL输出水平上发生,从而产生了令人惊讶的线性混合物表示。但是,AL中的嗅觉电路会强烈调制有关单个成分的信息,从而导致各个成分的表示形式与香蕉混合物的相似度更高。这种观察到的调制方式可能会以某种方式对嗅觉系统进行调节,以对气味成分进行明显分类并改善对合适食物来源的检测。因此,功能性GC-I能够分析几乎任何未知的天然气味混合物及其相对浓度的组分,并能够表征完整神经组件的神经元反应。该技术可以看作是经典GC /电生理技术的一种有价值的补充方法,并且在昆虫-昆虫和昆虫-植物化学相互作用的未来研究中将是非常有用的工具。

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