Key Laboratory of Molecular Biophysics of Ministry of Education, Hubei Bioinformatics and Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Nanjing University Institute of Artificial Intelligence Biomedicine, Nanjing, Jiangsu, 210031, China.
Nat Commun. 2024 May 1;15(1):3685. doi: 10.1038/s41467-024-48005-w.
Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-trained transformer (GPT) 3.5, which interprets 10.2-13.8% of Drosophila genes known to regulate the 3 behaviors. We develop an instrument for simultaneous video tracking of multiple moving objects, and conduct a genome-wide screen. We have identified 758 fly genes that regulate sleep and activities, including mre11 which regulates sleep only in the presence of conspecifics, and NELF-B which regulates sleep regardless of whether conspecifics are present. Based on LLM-reasoning, an educated signal web is modeled for understanding of potential relationships between its components, presenting comprehensive molecular signatures that control sleep, locomotor and social activities. This LLM-aided strategy may also be helpful for addressing other complex scientific questions.
睡眠、运动和社交活动是动物的基本行为，但它们之间的相互关系和潜在机制仍不清楚。在这里，我们利用前沿的大型语言模型（LLM），生成式预训练转换器（GPT）3.5，来解读已知调节这三种行为的 10.2-13.8%的果蝇基因。我们开发了一种同时对多个移动目标进行视频跟踪的仪器，并进行了全基因组筛选。我们已经鉴定出 758 个调节睡眠和活动的果蝇基因，包括仅在同种存在的情况下调节睡眠的 mre11 基因，以及无论同种是否存在都调节睡眠的 NELF-B 基因。基于 LLM 推理，我们构建了一个有教育意义的信号网络，以理解其组成部分之间的潜在关系，呈现出控制睡眠、运动和社交活动的综合分子特征。这种基于 LLM 的策略也可能有助于解决其他复杂的科学问题。
