Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical Tools

使用新颖的计算建模和分析工具解码神经回路中的星形胶质细胞信号传导

• 批准号: 10650384
• 负责人: Guoqiang Yu
• 金额: $ 68.14万
• 依托单位: VIRGINIA POLYTECHNIC INST AND ST UNIV
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-14 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10650384
• 关键词: Astrocytes; Award; BRAIN initiative; Behavior; Behavioral; Biological; Blood Vessels; Brain; Breathing; Calcium; Cells; Collaborations; Communication; Complex; Computer Models; Computer software; Computing Methodologies; Consensus; Data; Data Science; Data Set; Development; Dimensions; Disease; Event; Feedback; Fluorescence; Funding; Goals; Health; Hour; Human; Image; Individual; Learning; Link; Machine Learning; Membrane; Memory; Methods; Microglia; Microscopy; Modeling; Modernization; Morphology; Motor; Mus; Neurodegenerative Disorders; Neuroglia; Neurons; Noise; Oligodendroglia; Outcome; Paper; Parkinson Disease; Pathologic; Pattern; Pharmaceutical Preparations; Phosphotransferases; Physiological; Play; Positioning Attribute; Protocols documentation; Role; Science; Scientist; Signal Induction; Signal Transduction; Sleep; Software Engineering; Speed; Statistical Models; Synapses; Techniques; Testing; Time; Treatment Efficacy; Vertebral column; Work; Zebrafish; analytical tool; brain disorder therapy; calcium indicator; cell type; computerized tools; experimental study; extracellular; flexibility; imaging capabilities; improved; in silico; induced pluripotent stem cell; insight; laboratory experiment; method development; millisecond; multidisciplinary; multiplexed imaging; nervous system disorder; neural circuit; neuronal circuitry; neuropsychiatric disorder; neurotransmission; new therapeutic target; novel; novel therapeutics; prototype; receptor; stem cell model; success; synaptic function; theories; therapeutic target; tool; transmission process; user-friendly; vigilance; visual motor

Astrocyte is the most abundant glia cell and significantly outnumbers neuron in the human brain. Long thought to be primarily passive cell, astrocyte has been increasingly recognized as essential player with active regulatory role in neural circuitry and behaviors. Since a single astrocyte interacts with thousands of synapses, other glial cells and blood vessels, it is well positioned to link neuronal information in different spatial-temporal dimensions to achieve higher level brain integration. Indeed, neuron-astrocyte communication at synapses regulates breathing, memory formation, motor function, and sleep, and are implicated in many neuropsychiatric disorders. All these results provide strong rationale for studying astrocyte function, which will provide unprecedented insights to our understanding how astrocytes function to regulate and protect brain and how these functions can be exploited for astrocyte-based therapeutic targets. Although there is a moderate understanding of functional significance of astrocytes, a mechanistic and comprehensive understanding of the active functional roles of astrocytes in neural circuitry and behaviors is largely lacking. One major challenge in deciphering the functional roles of astrocyte is its complex signaling patterns resided in both spatial and temporal domains. Funded by last award, we have developed an event- decomposition framework and the method AQuA (Astrocyte Quantification and Analysis) to model the complex astrocyte signaling. AQuA was considered as a paradigm shift and turning point for astrocyte analysis by multiple review papers and is now widely used by many labs in the world. With the technical advances largely enabled by BRAIN Initiative, large-scale, multiplex imaging and manipulation of multiple circuit components in astrocyte-neuron network are now feasible. The increased complexity and amount of imaging dataset demand further development of powerful computational tools beyond AQuA. The large volume whole-brain activity data and the new imaging capability of signals beyond Ca2+ require significant improvements in speed, scalability, accuracy, and flexibility. The simultaneous recording of multiple intra/extra- cellular signals calls for new modeling framework and computational methods. Thus, building on our previous success, the overarching goal of this renewal project is to further develop novel computational methods and analytical tools to decode the functional roles of astrocytes in neural circuits and behavior. We will team up with experimental biologists to prototype, validate and integrate our computational tools with wet-lab experiments across species and biological questions. We expect a team science of close collaborations between computational and experimental scientists will enable new discoveries. Ultimately, a successful outcome will significantly enhance our mechanistic and theoretical understanding of astrocyte function in neural circuitry and behaviors. These understandings will be essential to development of new therapeutic drugs and strategies, which haven’t been changed in the past 30 years for neurological and neuropsychiatric disorders.

星形胶质细胞是人脑中数量最多的神经胶质细胞，其数量远远超过神经元。一直被认为

项目成果

Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data.

• DOI: 10.3389/fninf.2017.00048
• 发表时间: 2017
• 期刊: Frontiers in neuroinformatics
• 影响因子: 3.5
• 作者: Wang Y;Shi G;Miller DJ;Wang Y;Wang C;Broussard G;Wang Y;Tian L;Yu G
• 通讯作者: Yu G

DETECTION AND TRACKING OF MIGRATING OLIGODENDROCYTE PROGENITOR CELLS FROM IN VIVO FLUORESCENCE TIME-LAPSE IMAGING DATA.

从体内荧光延时成像数据检测和跟踪迁移的少突胶质细胞祖细胞。

• DOI: 10.1109/isbi.2018.8363730
• 发表时间: 2018
• 期刊: Proceedings. IEEE International Symposium on Biomedical Imaging
• 作者: Wang,Yinxue;Ali,Maria;Wang,Yue;Kucenas,Sarah;Yu,Guoqiang
• 通讯作者: Yu,Guoqiang

Asymmetric independence modeling identifies novel gene-environment interactions.

不对称独立模型识别新的基因-环境相互作用。

• DOI: 10.1038/s41598-019-38983-z
• 发表时间: 2019
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Yu,Guoqiang;Miller,DavidJ;Wu,Chiung-Ting;Hoffman,EricP;Liu,Chunyu;Herrington,DavidM;Wang,Yue
• 通讯作者: Wang,Yue

SynQuant: an automatic tool to quantify synapses from microscopy images

SynQuant：一种从显微镜图像中量化突触的自动工具

• DOI: 10.1093/bioinformatics/btz760
• 发表时间: 2019
• 期刊: Bioinformatics
• 影响因子: 5.8
• 作者: Wang, Yizhi;Wang, Congchao;Ranefall, Petter;Broussard, Gerard Joey;Wang, Yinxue;Shi, Guilai;Lyu, Boyu;Wu, Chiung-Ting;Wang, Yue;Tian, Lin
• 通讯作者: Tian, Lin