Collaborative Research: Control of Information Processing and Learning in Neuronal Networks through Light-mediated Programming of Genomic Networks

合作研究：通过基因组网络的光介导编程控制神经网络的信息处理和学习

• 批准号: 2039189
• 负责人: Josep Jornet
• 金额: $ 23.32万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039189&HistoricalAwards=false
• 关键词: Collaborative; Research; Control; Information; Processing

Communication and networking play a key role in the development and functioning of living organisms. The physical DNA interactions within the genome, or network of genes, determine gene activities and thereby the development and function of cells, similarly as the software determines the operation of the hardware in a computer. Therefore, being able to program genomic interactions and thereby the development of communicating neuronal networks is at the basis of transformative applications. In this direction, optogenomics, or the control of the genome function through light, is proposed. Optogenomics offers an unprecedented means to control organ and specifically brain development and functions, or even new corrective treatments of cancer and other diseases. Such control will be enabled through development of novel directional light emitting nano-devices. The goal of this inter-disciplinary project is to study information processing and learning (and, thus, ultimately memory) in neuronal networks orchestrated by the light manipulation of the genome. For this, new photonic and electronic tools will be developed to program the genome in neurons and to study both the resulting changes in the structure and activity in networks of living neurons. This project will provide inter-disciplinary training opportunities for graduate and undergraduate students, who will become versed in both nanophotonics and nanoelectronics as well as neuronal cell studies.Beyond optogenetic platforms, which are aimed at the use of light to control cell-cell interactions, optogenomic systems allow the control of DNA interactions in the genome and, thus, the programming of the cell development and function. In this project, new optogenomic tools will be developed to control the development and information processing and learning in neuronal networks. In the proposed system, neural stem cells will be transfected with optimized optogenomic constructs that combine light-activated algae proteins and mammalian genome regulators. As the input to the system, the constructs will be activated globally across the cell culture through LED-based homogeneous illumination. The light-induced changes in the genome 3D structure and function will be analyzed using Chromatin Conformation Capture HiC/HiChIP, Atomic Force Microscopy, and RNAseq with the NextGene global genome sequencing. The output of the system will be the opto-electrophysiological analysis of signal processing in optogenomically constructed neuronal networks, with innovative transparent flexile beamforming nanophotonic devices combined with flexible high-density microelectrode arrays, using metrics like Spike-Timing-Dependent Plasticity, Hebbian learning and network science. An integrated Genome-Neuronal Function Model will be developed for the first time by correlating genomic topological networks to the functional gene networks and ultimately to the properties of the resultant neuronal network as they form in 3D model of the human brain – cerebral organoids.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

通信和网络在生物体的发展和运作中发挥着关键作用。基因组或基因网络中的物理DNA相互作用决定了基因的活动，从而决定了细胞的发育和功能，就像软件决定了计算机中硬件的运行一样。因此，能够对基因组相互作用进行编程，从而开发通信神经网络是变革性应用的基础。在这个方向上，提出了光基因组学，或通过光控制基因组功能。光基因组学提供了一种前所未有的手段来控制器官，特别是大脑的发育和功能，甚至是癌症和其他疾病的新的矫正治疗。这种控制将通过开发新的定向发光纳米器件来实现。这个跨学科项目的目标是研究由基因组的光操纵所编排的神经元网络中的信息处理和学习（以及最终的记忆）。为此，将开发新的光子和电子工具来编程神经元中的基因组，并研究活神经元网络中结构和活动的变化。该项目将为研究生和本科生提供跨学科的培训机会，他们将精通纳米光子学和纳米电子学以及神经元细胞研究。除了旨在利用光控制细胞间相互作用的光遗传学平台外，光基因组学系统还可以控制基因组中的DNA相互作用，从而编程细胞发育和功能。在这个项目中，将开发新的光基因组学工具来控制神经网络的发育和信息处理和学习。在所提出的系统中，神经干细胞将转染优化的光基因组结构，结合联合收割机光激活藻类蛋白和哺乳动物基因组调节。作为系统的输入，构建体将通过基于LED的均匀照明在整个细胞培养物中被全局激活。将使用染色质构象捕获HiC/HiChIP，原子力显微镜和RNAseq与NextGene全球基因组测序分析基因组3D结构和功能的光诱导变化。该系统的输出将是光基因组学构建的神经元网络中信号处理的光电生理分析，创新的透明柔性波束形成纳米光子设备与灵活的高密度微电极阵列相结合，使用Spike-Timing-Dependent Plasticity，Hebbian学习和网络科学等指标。通过将基因组拓扑网络与功能基因网络相关联，并最终与人脑3D模型中形成的所得神经元网络的特性相关联，将首次开发出一个集成的基因组-神经元功能模型。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.

项目成果

Brain Organoids – expanding on understanding human brain development, schizophrenia and 'Phase Zero' therapies

脑类器官 — 加深对人类大脑发育、精神分裂症和“零阶段”疗法的理解

• 发表时间: 2021
• 期刊: 13th INAR conference and 7th International Conference
• 作者: Stachowiak, MK

Model-based investigation of elasticity and spectral exponent from atomic force microscopy and electrophysiology in normal versus Schizophrenia human cerebral organoids

基于模型的原子力显微镜和电生理学研究正常与精神分裂症人脑类器官的弹性和光谱指数

• DOI: 10.1109/embc48229.2022.9871376
• 发表时间: 2022
• 期刊: 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC
• 作者: Dutta, Anirban;Biber, John;Bae, Yongho;Augustyniak, Justyna;Liput, Michal;Stachowiak, Ewa;Stachowiak, Michal K.
• 通讯作者: Stachowiak, Michal K.

Joint Nanoscale Communication and Sensing Enabled by Plasmonic Nano-antennas

等离子纳米天线实现联合纳米级通信和传感

• DOI: 10.1145/3477206.3477447
• 发表时间: 2021
• 期刊: Proceedings of the Eight Annual ACM International Conference on Nanoscale Computing and Communication
• 作者: Sangwan, Amit;Jornet, Josep Miquel
• 通讯作者: Jornet, Josep Miquel

Beamforming optical antenna arrays for nano-bio sensing and actuation applications

• DOI: 10.1016/j.nancom.2021.100363
• 发表时间: 2021-09
• 期刊: Nano Commun. Networks
• 作者: A. Sangwan;J. Jornet

Multi-physics Analysis of Electromagnetic Wave Propagation and Photothermal Heating in Human Tissues at Terahertz and Optical Frequencies

• DOI: 10.1109/dcoss54816.2022.00064
• 发表时间: 2022-05
• 期刊: 2022 18th International Conference on Distributed Computing in Sensor Systems (DCOSS)
• 作者: I. Reddy;J. Jornet