Deciphering the Olfactory Code

描述（由申请人提供）：我们的嗅觉归功于气味化合物激活存在于我们鼻子中的嗅觉感觉神经元的膜表面上的气味受体的能力。我们目前的知识表明，在哺乳动物中，大约有1,000种气味受体，并且任何给定的神经元只表达一种类型的受体，不同的气味可以以不同的亲和力与之结合。因此，任何气味都可以被认为是由嗅觉系统以其自身与每个气味受体之间的一组亲和力的形式“编码”的。相反，气味受体原则上可以通过它们被（一些组）气味剂激活的模式来分类。目前的方法来检测气味和它们的受体之间的匹配范围从在体膜片钳记录从嗅上皮，灯泡或皮层，到Ca 2+成像的一小部分培养的神经元，在响应于一小组的气味。此外，由于神经元的反应是浓度依赖性的，每种气味剂必须在不同浓度下用分离的嗅觉感觉神经元进行筛选。一旦检测到给定神经元对任何浓度的给定气味剂的反应，就可以通过逆转录酶聚合酶链反应克隆受体，并随后测序。尽管这种方法可以精确地表征受体的分子结构，但它产生了不完整的功能描述，即它可能与数百种其他气味剂结合，而由于通量限制，这些气味剂在实验中不得不被错过。此外，气味受体只能探测一次，因为响应细胞是随机探测的。此外，该方法不足以从数百种气味剂的库中对由给定气味剂激活的所有气味剂受体进行详尽的搜索;因此，嗅觉系统内的气味剂的编码是未知的。 我们试图获得一个功能描述的所有气味受体存在于小鼠嗅上皮。这种功能描述不需要了解受体的分子结构。我们建议开发一个高通量的实验系统，该系统将允许检测大约100种气味剂的大型库与完整的相互作用受体（大约1，000）之间的匹配，即我们将找到气味剂库中每个成员的精确编码。所提出的系统包括：1）计算机控制的微流体装置，其可以用气味剂序列灌注嗅觉感觉神经元的大微阵列; 2）能够在大面积（> 5，000个细胞）上执行Ca 2+成像的光学设置;以及3）用于自动提取气味剂受体匹配的简单图像/数据处理算法。

DESCRIPTION (provided by applicant): We owe our sense of smell to the ability of odorant compounds to activate odorant receptors present on the membrane surface of olfactory sensory neurons in our nose. Our present knowledge indicates that, in mammals, there are around 1,000 types of odorant receptors and that any given neuron only expresses one type of receptor, to which different odorants can bind with different affinities. Thus, any odorant can be thought of as being "encoded" by the olfactory system in the form of a set of affinities between itself and each of the odorant receptors. Conversely, odorant receptors may, in principle, be categorized by their pattern of activation by (some set of) odorants. Present approaches to detect matches between odorants and their receptors range from in-vivo patch-clamp recordings from the olfactory epithelium, bulb or cortex, to Ca2+ imaging of a small number of cultured neurons, in response to a small set of odorants. In addition, since the neuron's response is concentration-dependent, each odorant must be screened at various concentrations with isolated olfactory sensory neurons. Once the response of a given neuron by a given odorant at any concentration is detected, the receptor can be cloned by reverse-transcriptase polymerase chain reaction and subsequently sequenced. Although this approach allows for exquisite detail in characterizing the molecular structure of the receptor, it yields an incomplete functional description, i.e. it might bind to hundreds of other odorants that had to be missed in the experiment due to throughput limitations. Furthermore, the odorant receptor can only be probed once because the responsive cell is probed at random. Additionally, the approach is inadequate for performing an exhaustive search of all the odorant receptors that are activated by a given odorant from a library of hundreds of odorants; hence the encoding of the odorant within the olfactory system is unknown. We seek to obtain a functional description of all the odorant receptors present in the mouse olfactory epithelium. This functional description will not require knowledge of the receptors' molecular structure. We propose to develop a high-throughput experimental system that will allow for detecting matches between a large library of around 100 odorants and the complete set of interacting receptors (approximately 1,000), i.e. we will find the exact encoding of each member of the odorant library. The proposed system consists of 1) a computer-controlled microfluidic device that can perfuse a large microarray of olfactory sensory neurons with sequences of odorants; 2) an optics setup capable of performing Ca2+ imaging over large areas (>5,000 cells); and 3) simple image/data processing algorithms for automated extraction of odorant-receptor matches.