Coupling of activity, metabolism and behaviour across the Drosophila brain.
Coupling of activity, metabolism and behaviour across the Drosophila brain.
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DOI：
10.1038/s41586-021-03497-0
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发表时间：
2021-05
期刊：
影响因子：
64.8
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中科院分区：
文献类型：
--
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在许多物种中，神经元网络之间的协调活动是静息和活跃行为状态的标志。这些全球模式在几秒到几小时内改变能量代谢，这支持了广泛使用氧气消耗和葡萄糖摄取作为神经活动的代理。然而，在与行为相关的时间尺度上，神经活动的变化是否与完整回路的代谢通量有因果关系尚不清楚。在这里，我们将苍蝇大脑的双光子显微镜与传感器结合起来，可以同时测量神经活动和代谢通量，包括静息状态和活跃行为状态。我们证明了神经活动驱动代谢通量的变化，在这些信号之间创建了一个紧密的耦合，可以通过大脑网络测量。利用局部光遗传扰动，我们证明即使神经活动的短暂增加也会导致胞质ATP的快速和持续增加，这表明神经元代谢可预测地分配资源以预测未来活动的能量需求。最后，我们的研究表明，即使是最小的行为运动的开始也会导致神经活动和能量代谢模式的大规模变化，这表明大脑的广泛参与。由于神经活动和能量代谢之间的关系可能是进化上古老且高度保守的，我们的研究为使用代谢代理来捕捉神经活动的变化提供了重要的基础。
Coordinated activity across networks of neurons is a hallmark of both resting and active behavioural states in many species. These global patterns alter energy metabolism over seconds to hours, which underpins the widespread use of oxygen consumption and glucose uptake as proxies of neural activity. However, whether changes in neural activity are causally related to metabolic flux in intact circuits on the timescales associated with behaviour is unclear. Here we combine two-photon microscopy of the fly brain with sensors that enable the simultaneous measurement of neural activity and metabolic flux, across both resting and active behavioural states. We demonstrate that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across brain networks. Using local optogenetic perturbation, we demonstrate that even transient increases in neural activity result in rapid and persistent increases in cytosolic ATP, which suggests that neuronal metabolism predictively allocates resources to anticipate the energy demands of future activity. Finally, our studies reveal that the initiation of even minimal behavioural movements causes large-scale changes in the pattern of neural activity and energy metabolism, which reveals a widespread engagement of the brain. As the relationship between neural activity and energy metabolism is probably evolutionarily ancient and highly conserved, our studies provide a critical foundation for using metabolic proxies to capture changes in neural activity.
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