Single cell multiomic and spatial atlas of acute and chronic kidney injury

急慢性肾损伤的单细胞多组学和空间图谱

基本信息

批准号：
10703444
负责人：
Sanjay Jain
金额：
$ 86.04万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-15 至 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10703444
关键词：
3-Dimensional ATAC-seq Acute Acute Renal Failure with Renal Papillary Necrosis Adult Atlases Automobile Driving Benchmarking Binding Bioinformatics Biological Biological Assay Biopsy Catalogs Cell Communication Cell Nucleus Cells Cellular biology Chromatin Chronic Chronic Kidney Failure Clinical Collaborations Complex Controlled Vocabulary Cytometry Data Data Set Development Diagnosis Diagnostic Disease Disease Outcome Endothelium Ensure Environment Epigenetic Process Ethnic Origin Evaluation Extracellular Matrix Fostering Freezing Gene Expression Gene Expression Regulation Genes Genetic Genomics Histologic Human Human BioMolecular Atlas Program Immune Infrastructure Injury Injury to Kidney Institution Joints Kidney Kidney Diseases Knowledge Measures Methods Modality Molecular Molecular Biology Molecular Profiling Neighborhoods Nephrology Nephrons Nerve Organ Participant Pathologic Pathology Patient Care Patients Phase Process Production Proteins Protocols documentation Publications Quality Control RNA Race Recommendation Regulation Reporting Research Personnel Resolution SNAP receptor Sampling Science Sex Differences Site Small Nuclear RNA Specimen Handling Stromal Cells Technology Text Tissue Embedding Tissue atlas Tissues Translational Research Transposase Tubular formation Urine Validation XCL1 gene biobank cell type clinical care data integration data sharing design epigenome epigenomics flexibility insight interstitial kidney biopsy kidney cell knowledge integration large scale data molecular phenotype multimodal data multimodality multiple omics nephrogenesis new technology novel patient oriented research precision medicine prognosis biomarker programs racial diversity sex single cell technology single nucleus RNA-sequencing single-cell RNA sequencing spatial relationship synergism therapeutic target tissue processing tongue papilla transcription factor transcriptome transcriptomics

项目摘要

(PLEASE KEEP IN WORD, DO NOT PDF) Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We pioneered the development of novel tissue processing methods in the KPMP that uses a limited amount of human kidney biopsy tissue for single nucleus (sn) omics and spatial technologies across institutions while allowing parallel histological evaluation. Using our TISAC-approved snRNA-seq assay on reference, AKI and CKD biopsies, we generated a snRNA atlas from 200K nuclei covering cortex to papilla and revealed 53 healthy and 47 altered cell states. These represent cycling, degenerative, adaptive/maladaptive and transitioning cells in tubular and interstitial compartments. We augmented these efforts by integrating these data with newer technologies that measure RNA and epigenome in the same nucleus and defined key transcription factors associated with gene expression changes in transition of healthy cell to altered cell states. In a collaborative effort in KPMP and HuBMAP, we integrated snRNA-seq, scRNA-seq, SNARE-seq2, two different spatial transcriptomic technologies and 3D cytometry. From this we were able to define biologically meaningful cell-cell interactions, cognate molecular interactions and genes associated with adaptive states that correlate with worse CKD outcomes. Deeper sampling and integrated analyses ensuring tissue economy of AKI and CKD biopsies is still needed to overcome gaps in clinicopathological-molecular determinants, and to assess effect of race, sex, ethnicity, clinical attributes, mechanisms of gene regulation, shifts in cell states, and characterization of biologically relevant niches. To this end we will use paired snRNA-seq and snATAC-seq (chromatin accessibility) to define mechanisms associated with altered state transitions, which will enable discovery of potential causative epigenetic factors driving RNA or protein changes in disease (Aim 1). To further define the spatial contexts of injury niches for biological insights, we will evaluate and implement highly multiplexed spatial transcriptomics technologies (Aim 2) and integrate knowledge from our transcriptomic and epigenomic atlas with other orthogonal technologies in the KPMP and other consortia (Aim 3). This collective effort will enable the creation of a high resolution spatial molecular atlas of healthy and diseased kidneys that can be used as a benchmark to interrogate and interpret molecular information in a single patient’s biopsy that can inform clinical care.

（请以 WORD 形式保存，请勿以 PDF 形式保存）在此输入您的申请的新摘要信息的文本。此部分的文本长度不得超过 30 行。了解肾脏疾病依赖于定义细胞类型和状态的复杂性、其相关分子谱以及组织邻域内的相互作用。我们率先在 KPMP 中开发了新型组织处理方法，该方法使用有限数量的人类肾活检组织进行单核。跨机构的 (sn) 组学和空间技术，同时允许对参考、AKI 和 CKD 活检进行并行组织学评估，我们生成了覆盖皮质到 20 万个细胞核的 snRNA 图谱。我们通过将这些数据与测量同一细胞核中的 RNA 和表观基因组的新技术相结合，增强了这些工作。定义了与健康细胞向改变的细胞状态转变过程中基因表达变化相关的关键转录因子。在 KPMP 和 HuBMAP 的合作中，我们整合了 snRNA-seq、scRNA-seq、 SNARE-seq2、两种不同的空间转录组学技术和 3D 细胞术，由此我们能够定义具有生物学意义的细胞间相互作用、同源分子相互作用以及与较差 CKD 结果相关的适应状态相关的基因，并进行更深入的采样和综合分析，确保组织。仍然需要 AKI 和 CKD 活检的经济性，以克服临床病理分子决定因素的差距，并评估种族、性别、民族、临床属性、基因调控机制、细胞状态的变化和为此，我们将使用配对的 snRNA-seq 和 snATAC-seq（染色质可及性）来定义与改变的状态转换相关的机制，这将能够发现驱动疾病中 RNA 或蛋白质变化的潜在致病因素。目标 1）为了进一步定义损伤生态位的空间背景以获得高度生物学见解，我们将评估和实施多重空间转录组学技术（目标 2）并整合来自我们的转录组和表观基因组图谱的知识。与 KPMP 和其他联盟的其他正交技术相结合（目标 3），这项集体努力将能够创建健康和患病肾脏的高分辨率空间分子图谱，该图谱可用作查询和解释单个分子信息的基准。患者的活检可为临床护理提供信息。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Computational Pathology Fusing Spatial Technologies.

融合空间技术的计算病理学。

DOI：
10.2215/cjn.0000000000000146
发表时间：
2023
期刊：
Clinical journal of the American Society of Nephrology : CJASN
影响因子：
0
作者：
Border,Samuel;Lucarelli,Nicholas;Eadon,MichaelT;El-Achkar,TarekM;Jain,Sanjay;Sarder,Pinaki
通讯作者：
Sarder,Pinaki