Single Cell Resolution Omics Analysis of T1D islets

 描述（由申请人提供）：1型糖尿病（T1 D）是一种由产生胰岛素的胰腺β细胞的自身免疫性破坏引起的慢性疾病。尽管T1 D主要与免疫应答功能障碍相关，但对人类胰岛组织的接触增加已经揭示了T1 D患者中令人惊讶的短暂和异质水平的胰岛炎。此外，最近的全基因组关联研究（GWAS）已经确定，大量的T1 D相关基因在胰腺β细胞中表达。相应地，越来越多的迹象表明β细胞功能障碍发生在T1 D疾病过程的早期，甚至可能在启动自身免疫反应。还有越来越多的证据表明β细胞对T细胞介导的免疫攻击有不同的反应，这表明β细胞应激和功能障碍不仅可能导致β细胞死亡，而且可能导致β细胞可塑性增加和/或去分化。了解这些反应何时以及如何发生不仅可以识别T1 D的潜在新生物标志物，还可以促进新疗法的开发，以预防或阻断疾病进展。为了表征T1 D过程早期导致β细胞功能障碍和破坏的细胞和分子事件，需要开发可用于评估可用人体组织的新型基因组学和蛋白质组学技术。此外，考虑到与正常和遗传易感性T1 D胰岛相关的异质性，开发允许以单细胞和近单细胞分辨率详细表征人胰腺组织的分析工具将是至关重要的。根据该RFA的目标，该资助的目的是使用两个强大且互补的技术平台-- combFISH和nanoDESI --对人类胰腺组织进行原位单细胞分辨率组学分析，包括基因和蛋白质表达、代谢物水平和脂质表征，以提供对T1 D的重要见解。的 该提案汇集了一个强大的研究团队，他们具有相关和互补的研究专业知识：洛里·苏塞尔博士是β细胞生物学领域的领导者，查尔斯·安松博士和托马斯梅斯博士是蛋白质组学和代谢组学领域的专家。Julia Laskin博士是成像质谱领域的领导者，Galya Orr博士是定量超分辨率和单分子荧光成像方面的专家。Mark Atkinson博士是T1 D研究的领导者。这种结合的专业知识确保了这项研究计划的成功。该提案的目标是首先优化来自T1 D啮齿动物模型的胰岛的现有组学技术。该计划的主要目标是评估人类正常和T1 D胰岛，并将数据记录和传播给糖尿病社区。我们将通过以下目标来实现我们的目标：（1）T1 D啮齿动物模型的技术改进（2）技术在人类胰岛研究中的应用（3）管理数据和元数据，以促进数据集成和分析。

 DESCRIPTION (provided by applicant): Type 1 diabetes mellitus (T1D) is a chronic disease resulting from the autoimmune destruction of insulin- producing pancreatic beta cells. Although T1D is primarily associated with a dysfunctional immune response, increased access to human islet tissue has revealed surprisingly transient and heterogeneous levels of insulitis in T1D patients. Furthermore, recent genome-wide association studies (GWAS) have determined that a large number of T1D associated genes are expressed in pancreatic beta cells. Correspondingly, there is increasing indication of beta cell dysfunction occurring early in the T1D disease process and perhaps even in initiating the autoimmune response. There is also mounting evidence of diverse beta cell responses to the T-cell mediated immune attack, suggesting that beta cell stress and dysfunction may not only lead to beta cell death, but could possibly lead to increased beta cell plasticity and/or dedifferentiation. Understanding when and how these responses occur will not only identify potential new biomarkers of T1D, but will facilitate the development of nove therapies to prevent or block disease progression. To characterize the cellular and molecular events that are responsible for beta cell dysfunction and destruction early in the T1D process there is a need to develop novel genomics and proteomics technologies that can be used to evaluate available human tissues. Furthermore, given the heterogeneity associated with normal and genetically susceptible T1D islets, it will be critical to develop analytical tools that allow detailed characterization of human pancreatic tissues at single cell and near single cell resolution. In accordance with the goals of this RFA, the purpose of this grant is to use two powerful and complementary technology platforms - combFISH and nanoDESI - for in situ single cell resolution omics analyses of human pancreatic tissue that includes gene and protein expression, metabolite levels and lipid characterization to provide critical insights into T1D. The proposal brings together a strong team of investigators with relevant and complimentary areas of research expertise: Dr. Lori Sussel is a leader in the field of beta cell biology and Drs. Charls Ansong and Thomas Metz are experts in the field of proteomics and metabolomics. Dr. Julia Laskin is a leader in the field of imaging mass spectrometry and Dr. Galya Orr is an expert in quantitative super resolution and single-molecule fluorescence imaging. Dr. Mark Atkinson is a leader in T1D research. This combined expertise ensures the success of this research program. The goal of the proposal is to first optimize existing omics techniques on pancreatic islets derived from rodent models of T1D. The main thrust of the program will be to evaluate human normal and T1D islets and document and disseminate the data to the diabetes community. We will accomplish our goal through the following aims: (1) Technology Refinement in Rodent Models of T1D (2) Application of Technology to Human Islet Studies (3) Manage Data and Metadata to facilitate data integration and analysis.