Neurodifferentiation/Stem Cell Unit
神经分化/干细胞单位
基本信息
- 批准号:10916077
- 负责人:
- 金额:$ 89.58万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:
- 资助国家:美国
- 起止时间:至
- 项目状态:未结题
- 来源:
- 关键词:2019-nCoV3-DimensionalAdoptedAdultAgreementAnimal ModelAstrocytesBindingBiological AssayBlood - brain barrier anatomyBrainCD34 geneCOVID-19 testCell LineCellsClinicalCoculture TechniquesCollaborationsCommunicable DiseasesCongressesDevelopmentDiagnosisDiseaseEndogenous RetrovirusesEndothelial CellsEndotheliumEpigenetic ProcessEquipmentExtramural ActivitiesFibroblastsFutureGenerationsGenesGeneticGenetic TranscriptionGenetic studyGlioblastomaGoalsGrowthHomeHospitalsHumanIn VitroIndiaInduced pluripotent stem cell derived neuronsInfectionInflammationInflammatoryMacaca mulattaMethodsMicrofluidic MicrochipsMicrogliaMitochondriaModelingMolecular TargetMotor NeuronsNational Institute of Neurological Disorders and StrokeNeoplasm MetastasisNerve DegenerationNeurodevelopmental DisorderNeuronsNeurosciencesOrganoidsPathogenesisPatientsPeripheralPeripheral Blood Mononuclear CellPlasmidsPluripotent Stem CellsPredispositionProtocols documentationPublicationsReportingResearch PersonnelRhesusRoleSARS-CoV-2 infectionSARS-CoV-2 spike proteinSamplingShapesSkinSpainStainsStudy modelsTechniquesTherapeutic InterventionTrainingTransfectionTumorigenicityUnited States National Institutes of HealthVariantVirionVirus Activationcell typedensitydesigndopaminergic neuroninduced pluripotent stem cellmotor neuron degenerationnerve stem cellnervous system disorderneuralneural modelneurodevelopmentneurogenesisneuroimmunologyneurotoxicitynovelpreclinical studyreconstitutionresearch and developmentscreeningstem cellsstemnesstherapeutic developmentthree-dimensional modelingtranslational neurosciencetumorigenesis
项目摘要
Specific aim 1:
To develop in vitro 2D neuronal and 3D brain organoid models derived from human adult peripheral CD34+ cells to study neural development and degeneration and infectious diseases involving human brain. We set up a new brain-on-the-chip microfluidic culture equipment into our unit, we now can reconstitute 3D brain cultures in a precise way by combining four types of essential cells in the brain: neurons, microglia, astroglia and endothelial cells. This approach, in additional to our existing 3D brain organoid models, is very useful to delineate the role of specific cell types in the neural development or neurodegeneration. In the preliminary study, we have used iPSC-derived neurons and commercially obtained primary astroglia, endothelial cells and a microglial cell line to make the mixed brain-on-the-chip successfully. We also optimized protocols to successfully generate microglia, astrocyte and endothelial cells from iPSCs and will use these methods to generate disease-specific brain-on-the-chip in the future study. In addition, we used the home developed endothelial incorporated 3D brain model to test if SARS-CoV2 can directly infect it. Using a pseudo-virus with SARS-CoV2 spike protein, we found that the SARS-CoV2 pseudo-virus can hardly infect the brain organoids, with only scarce weak positive cells along endothelial linings, not in the inner neuronal mass. This result is agreed to the clinical observation that SARS-CoV2 is seldom detected from neurons in patient brains. Although this is different with other reports which used traditional brain organoids to show high levels of SARS-CoV2 infections. These conflicts may be due to the existence of endothelial cells and blood-brain-barrier. We have been invited to present the model and findings in the upcoming 11th IBRO World Congress of Neuroscience, Granada, Spain.
Specific aim 2: To study the roles of HERV-K on brain development and tumorigenicity. We continued the collaboration with Dr. Ashish Shah on studying the mechanism of HERV-K on the pathogenesis of glioblastoma. We used the human CD34-derived neural stem cells to generate a 3D model for astroglial growth. In transfected astroglia with plasmid containing HERV-K we detected higher level of gene transcription responsible for stemness and tumorigenesis and the organoids grow faster than controls with an irregular shape, indicating a potential for easier metastasis. These results contributed to a new publication.
Specific aim 3: To study the association of HERV-K and motor neuron degeneration like ALS. We continued our study of retro virus activation and motor neuron degeneration. For functional study, we collaborated with Dr. InHong Yang from UNC to use mitotrackers to stain the mitochondria of motor neurons. Use this method, we counted mitochondrial density from both ALS neurons and controls. While our preliminary result indicated a difference of mitochondrial staining between the two groups, more studied using rigor differentiation conditions are needed to confirm the result. We also used specifically designed ASO targeting HERV-K Env to study the effect of 3D brain development and motor neuron degeneration, we observed that ASO resulted in slower growth of 3D organoids as expected. We also used an in vitro neural culture derived from rhesus skin fibroblasts to study its susceptibility of HERV-K infection, in collaboration with Dr. Dr. Catherine Demarino from SINS, NINDS. We found that NSC derived from Rhesus skin fibroblasts express HERV-K Env binding target and high titer of HERV-K virions infects the NSC, indicating Rhesus monkey could be used as the animal model for studying HERV-K infection and neurodegeneration.
Specific aim 4: To facilitate research and therapeutic developments for neurological disorders using our models and methods. We Generated a new iPSC line from fibroblast of a patient with a specific FRMD4 gene variation, in collaborated with Dr. Maria Isis Atallah Gonzalez, CHUV. We trained Dr. Sanjay Yadav, a collaborator from AIIMS Raebareli, India on generating dopaminergic neurons from patient PBMCs and since generated 4 lines of iPSCs from PD patients. We continued our collaborate with Dr. Youssef Kousa by providing material support and technique advice of the iNSC/iPSC generation and 3D modeling that he has adopted in his newly established lab in National Childrens Hospital.
具体目标1:
建立成人外周血CD 34+细胞的体外2D神经元和3D脑类器官模型,用于研究神经发育和变性以及涉及人脑的感染性疾病。我们在我们的单元中建立了一个新的脑芯片微流控培养设备,我们现在可以通过结合大脑中的四种基本细胞来精确地重建3D脑培养物:神经元,小胶质细胞,星形胶质细胞和内皮细胞。除了我们现有的3D脑类器官模型之外,这种方法对于描述特定细胞类型在神经发育或神经变性中的作用非常有用。在初步研究中,我们使用iPSC衍生的神经元和商业获得的原代星形胶质细胞,内皮细胞和小胶质细胞系成功地制作了混合脑芯片。我们还优化了方案,成功地从iPSC中生成小胶质细胞,星形胶质细胞和内皮细胞,并将在未来的研究中使用这些方法生成疾病特异性脑芯片。此外,我们还利用自行研制的内皮细胞结合的三维脑模型来检测SARS-CoV 2是否可以直接感染,利用带有SARS-CoV 2刺突蛋白的假病毒,我们发现SARS-CoV 2假病毒几乎不能感染脑类器官,只有少量弱阳性细胞沿着内皮细胞衬里,而不在内层神经元团中。这一结果与临床观察结果一致,即SARS-CoV 2很少从患者大脑的神经元中检测到。尽管这与其他使用传统脑类器官显示高水平SARS-CoV 2感染的报告不同。这些冲突可能是由于内皮细胞和血脑屏障的存在。我们已被邀请在即将举行的第11届IBRO世界神经科学大会,格拉纳达,西班牙提出的模型和研究结果。
具体目标2:研究HERV-K在脑发育和致瘤性中的作用。我们继续与Ashish Shah博士合作研究HERV-K对胶质母细胞瘤发病机制的影响。我们使用人CD 34衍生的神经干细胞来生成星形胶质细胞生长的3D模型。在用含有HERV-K的质粒转染的星形胶质细胞中,我们检测到更高水平的基因转录,负责干性和肿瘤发生,并且类器官比具有不规则形状的对照生长得更快,表明更容易转移的潜力。这些结果有助于新的出版物。
具体目标3:研究HERV-K与运动神经元变性(如ALS)的关系。我们继续研究逆转录病毒激活和运动神经元变性。在功能研究方面,我们与北京大学的杨仁宏博士合作,使用线粒体追踪器对运动神经元的线粒体进行染色。使用这种方法,我们计算了ALS神经元和对照的线粒体密度。虽然我们的初步结果表明两组之间的线粒体染色存在差异,但需要使用严格的分化条件进行更多的研究以确认结果。我们还使用专门设计的靶向HERV-K Env的阿索来研究3D大脑发育和运动神经元变性的影响,我们观察到阿索导致3D类器官的生长减慢,如预期的那样。我们还使用了来自恒河猴皮肤成纤维细胞的体外神经培养物来研究其对HERV-K感染的易感性,与NINDS的Catherine Demarino博士合作。我们发现恒河猴皮肤成纤维细胞来源的神经干细胞表达HERV-K Env结合靶点,且高滴度的HERV-K病毒粒子感染神经干细胞,表明恒河猴可作为研究HERV-K感染和神经退行性变的动物模型。
具体目标4:使用我们的模型和方法促进神经系统疾病的研究和治疗开发。我们与CHUV的Maria Isis Atallah Gonzalez博士合作,从具有特定FRMD 4基因变异的患者的成纤维细胞中产生了一种新的iPSC系。我们培训了来自印度AIIMS雷巴雷利的合作者Sanjay Yadav博士从患者PBMC产生多巴胺能神经元,并从PD患者产生了4系iPSC。我们继续与Youssef Kousa博士合作,为他在国立儿童医院新成立的实验室中采用的iNSC/iPSC生成和3D建模提供材料支持和技术建议。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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David Wang其他文献
David Wang的其他文献
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{{ truncateString('David Wang', 18)}}的其他基金
Developing Machine Learning Models for the Analysis of Splicing Data in Large Heterogeneous Cohorts
开发机器学习模型来分析大型异构队列中的拼接数据
- 批准号:
10506326 - 财政年份:2021
- 资助金额:
$ 89.58万 - 项目类别:
Developing Machine Learning Models for the Analysis of Splicing Data in Large Heterogeneous Cohorts
开发机器学习模型来分析大型异构队列中的拼接数据
- 批准号:
10672974 - 财政年份:2021
- 资助金额:
$ 89.58万 - 项目类别:
Developing Machine Learning Models for the Analysis of Splicing Data in Large Heterogeneous Cohorts
开发机器学习模型来分析大型异构队列中的拼接数据
- 批准号:
10315802 - 财政年份:2021
- 资助金额:
$ 89.58万 - 项目类别:
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