权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Generating spatial and functional maps of cell-to-cell interactions in MS lesions

生成多发性硬化症病变中细胞间相互作用的空间和功能图

基本信息

批准号：
10365983
负责人：
David Pitt
金额：
$ 59.1万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-03-15 至 2026-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10365983
关键词：
Accounting Acute Antibodies Astrocytes Atlases Biological Cell Communication Cell Nucleus Cells Chronic Complex Computing Methodologies Data Data Analyses Data Set Demyelinations Disease Environment Evaluation Exhibits Frequencies Gene Expression Profile Genetic Transcription Heterogeneity Histology Image Imaging Techniques In Situ In Vitro Indirect Immunofluorescence Inflammation Inflammatory Lesion Ligands Lymphocyte Maps Microglia Multiple Sclerosis Multiple Sclerosis Lesions Myeloid Cells Neurons Nuclear Oligodendroglia Organ Pathologic Pathology Population Population Heterogeneity Preparation Protocols documentation Recovery Relapse Resolution Resources Sampling Signal Transduction Sorting - Cell Movement Spatial Distribution Structure Techniques Testing Tissues Tumor-infiltrating immune cells base cell preparation cell type computerized tools data visualization denoising genomic platform histological image histological stains imaging approach imaging modality improved innovation insight multiplexed imaging novel strategies oligodendrocyte precursor population based precursor cell receptor receptor expression remyelination therapeutic target tissue repair tool transcriptome transcriptome sequencing transcriptomics white matter

项目摘要

Generating spatial and functional maps of cell-to-cell interactions in MS lesions Single nucleus RNA sequencing (sNuc-Seq) studies have greatly advanced our understanding of cellular heterogeneity in multiple sclerosis (MS) lesions. However, current CNS sNuc-Seq protocols selectively under-sample astrocyte and microglia nuclei, resulting in low resolution of population heterogeneity. Moreover, sNuc-Seq does not capture spatial information, such as distribution and interactions of cell populations within the MS lesion environment. Here, we propose to use a novel approach to sNuc-Seq of MS lesion tissue, enrichment for unrepresented/rare nuclei such as astrocytes, microglia and infiltrating immune cells through Flow sorting. We will combine this approach with advanced computational tools for denoising, imputation and batch correction to improve recovery of biological signal and resolution of cellular heterogeneity in acutely demyelinating, chronic active and remyelinating MS lesions. We will leverage the subpopulation-specific transcriptomes to computationally predict possible interactions between cell populations, based on expression of receptor-ligand pairs. We will further use a highly multiplexed histology imaging approach to localize cellular subpopulations and confirm co-localization of receptor-ligand pairs in MS lesions. We will finally conduct in vitro studies to elucidate the functional impact of selected receptor-ligand interactions. Our study will identify the constituent subpopulations and receptor-ligand interactomes that are associated with acute demyelination, chronic low-grade inflammation and remyelination. These interactions or combinations of interactions can be targeted to reduce inflammation or to enhance neurorepair in MS. Moreover, our datasets will provide a rich resource that will guide more functional studies on disease mechanisms.

生成MS病变中细胞间相互作用的空间和功能图单核RNA测序(SNUC-Seq)的研究极大地促进了我们对多发性硬化症(MS)病变的细胞异质性。然而，当前的CNS SNUC-Seq 方案选择性地低于样本的星形胶质细胞和小胶质细胞核，导致低分辨率种群异质性。此外，SNUC-Seq不捕获空间信息，例如多发性硬化症病变环境中细胞群的分布和相互作用。在这里，我们建议使用一种新的方法来检测多发性硬化症病变组织的SNUC-SEQ，为未见/罕见的核，如星形胶质细胞、小胶质细胞和通过血流渗透的免疫细胞分类。我们将把这种方法与先进的去噪计算工具结合起来，补偿和批量校正提高生物信号的恢复和细胞的分辨率急性脱髓鞘、慢性活动性和复髓鞘多发性硬化症病变的异质性。我们会利用亚群特定的转录本来计算预测可能的可能性细胞群体之间的相互作用，基于受体-配体对的表达。我们会进一步使用高度多元化的组织成像方法来定位细胞亚群并证实受体-配体对在MS病变中的共定位。我们最终将在体外进行研究以阐明选定的受体-配体相互作用的功能影响。我们的研究将确定组成亚群和受体-配体相互作用与急性脱髓鞘、慢性低度炎症和再髓鞘有关。这些相互作用或相互作用的组合可以有针对性地减少炎症或增强此外，我们的数据集将提供丰富的资源，将指导更多疾病机制的功能研究。