Transcriptional profiling of nutritional deficiency in single neurons: insights for state-dependent behaviour and healthy ageing

背景我们神经系统的功能与我们的饮食密切相关。我们的大脑不断评估我们体内的能量和营养水平，让我们饿了就吃，吃饱了就停下来。大脑也比其他器官消耗更多的能量，因此高度依赖营养供应。然而，适当的营养并不总是可用的，一些缺乏会导致各种疾病。例如，蛋白质摄入量低与抑郁症和痴呆症有关，特别是在老年人中。构成蛋白质的氨基酸对于制造神经元用来交流的化学物质至关重要。然而，氨基酸如何有助于维持大脑健康，以及为什么在老年时摄入足够的氨基酸特别相关，目前尚不清楚。果蝇是研究大脑和营养的优秀模式生物。它们的生命周期短，在实验室培养成本低廉。尽管它们的大脑很小，但它们表现出许多复杂的行为，可以使用大量的遗传工具来人工操纵。值得注意的是，苍蝇饥饿和进食的调节机制与人类非常相似。控制摄食行为的神经元根据营养需要改变它们的活动。然而，对于这些神经元是如何感觉到动物是否饥饿，或者它们如何与其他大脑区域进行交流，人们知之甚少。发现调节这些神经元活动的机制将有助于解释动物如何选择它们的饮食。AIMS和目标我们将以果蝇为模型回答两个问题。首先，我们将确定大脑中的特定基因如何根据最需要的营养物质控制食物的偏好和消费。其次，我们将解释氨基酸缺乏如何影响老年人的记忆和其他行为。方法我们将使用最先进的方法和计算工具来识别其活性受无糖或蛋白质饮食影响的基因。单个神经元的分辨将精确地确定这些基因在大脑中的哪些位置是重要的。我们将人工改变候选基因的活性，以确定它们如何调节食物的选择和消费。我们还将测量缺乏氨基酸的饮食如何影响记忆，以揭示它们对大脑健康老化的重要性。使用与上述方法类似的方法，我们将发现在以缺乏蛋白质的饮食喂养的老年动物中，基因会改变它们的活动。这将有助于解释为什么蛋白质缺乏对老年动物的大脑有更显著的影响。OUTCOMES和BENEFITS他们的项目将揭示营养与大脑功能之间的基本机制。识别新的机制，将行为转变为摄入缺失的营养物质，将为理解饮食失调是如何发展的提供要素。通过测量蛋白质缺乏的长期后果，我们将探索饮食和老年人认知能力丧失之间的联系。了解神经变性的饮食原因有助于为有风险的患者制定预防策略。

BACKGROUNDThe function of our nervous system is intimately connected to our diet. Our brain constantly evaluates energy and nutrient levels in our bodies to make us eat when hungry and stop once sated. The brain also consumes much more energy than other organs and is therefore highly dependent on nutrient supply. However, appropriate nutrients are not always available, and some deficiencies can cause a variety of illnesses. For example, low levels of protein intake have been linked with depression and dementia, especially in aged individuals. Amino acids that constitute proteins are crucial for making the chemicals used by neurons to communicate. However, how amino acids contribute to maintaining brain health and why consuming them in sufficient amount is especially relevant in old age remains unclear.Fruit flies are an outstanding model organism to study brain and nutrition. They have a short life cycle and are inexpensive to culture in laboratories. Despite their small brain, they display many complex behaviours that can be artificially manipulated using a large selection of genetic tools. Notably, mechanisms regulating hunger and feeding in flies are very similar to those in humans. Neurons controlling feeding behaviour change their activity depending on nutritional needs. However, little is known about how these neurons sense whether the animal is hungry or not, or how they communicate with other brain regions. Discovering mechanisms regulating the activity of these neurons would help explain how animals choose their diet. AIMS AND OBJECTIVESWe will use fruit flies as a model to answer two questions. First, we will determine how specific genes in the brain control food preference and consumption, depending on the most needed nutrients. Second, we will explain how the lack of amino acids affects memory and other behaviours in aged individuals. METHODOLOGYWe will use state-of-the-art methods and computational tools to identify genes whose activity is influenced by a diet without sugars or proteins. Single-neuron resolution will precisely identify where in the brain these genes are important. We will artificially change the activity of candidate genes to determine how they regulate food choice and consumption. We will also measure how a diet lacking amino acids influences memory, to reveal their importance for healthy brain ageing. Using similar methods to those described above, we will find genes that change their activity in aged animals fed on a diet lacking proteins. This will help explain why protein deficiency has a more significant impact on the brains of aged animals.OUTCOMES AND BENEFITSThis project will shed light on essential mechanisms connecting nutrition with brain function. Identifying novel mechanisms to switch behaviour towards consuming missing nutrients will provide elements to understand how eating disorders develop. By measuring the long-term consequences of protein deprivation, we will explore the links between diet and the loss of cognitive abilities in aged individuals. Understanding dietary causes of neurodegeneration could help develop preventative strategies for patients at risk.