Assessing how ocular surface nerves, immune cells, and epithelial cells communicate to encourage neuro-immune homeostasis

项目摘要 眼表神经的性质和功能在维持眼表健康方面起着关键作用， 预防疾病。眼表感觉神经的破坏可导致致盲性角膜炎、移植排斥， 干眼病和眼表疼痛。“组学”研究的出现为我们提供了一个平台， 了解眼表神经如何参与眼部健康和疾病的更广泛的背景。在这里， 我们概述了一个提议，该提议将创建详细描述眼表面神经支配的性质的大数据集。我们将 采用系统级方法，使用生物信息学和机器学习分析我们的数据 平台，使我们能够获得一个实际的了解眼表环境在健康和 疾病具体来说，这项建议将解决如何眼表神经，上皮细胞，免疫细胞， 互动.我们招募了一个多学科的研究团队，包括眼科专家， 神经免疫学、神经学、蛋白质组学、系统免疫学和生物信息学。有了这个团队，我们计划 全面分析RFA中概述的所有三个层次的研究，其中包括解剖学和 形态学表征，定义神经元和非神经元细胞的细胞和分子特性 类型，并评估神经元和非神经元细胞的功能特性。因为神经支配模式 和功能随疾病而变化，我们将使用多种眼表疾病模型（病毒性角膜炎和 为了更好地了解神经元、上皮细胞和免疫细胞如何影响神经元的功能， 功能和随后的疾病。我们将通过追求四个具体目标来实现我们的目标：1）我们将 对角膜和眼表神经支配的神经元和非神经元细胞进行单细胞（sc）组学 神经节这些数据将表征神经元身份并描述其在疾病期间的功能。 此外，我们将能够从分子上表征影响免疫系统的免疫细胞和上皮细胞。 疾病期间眼表面传入神经的功能。2)我们将用质谱分析法来分析 健康和疾病期间角膜的蛋白质组特征。一个不带偏见的散弹枪接近， 针对神经营养因子的靶向方法将被用于鉴定影响眼部的蛋白质， 表面神经功能3)我们将使用我们的成像技术和组织细胞计数， 分析角膜内神经元和非神经元细胞的位置和形态，以便我们可以 能够得出关于神经，上皮细胞和免疫细胞如何在近距离相互作用的结论。 眼表4)我们将使用DREADD（设计师受体专门由设计师药物激活）技术 扰乱神经元的敏感性，这样我们就可以评估改变神经元对刺激的反应如何可能 影响眼表稳态和疾病进展。对我们的观测结果进行系统级分析 使用机器学习和生物信息学将导致预测新的相互作用网络， 在未来的研究中进行调查。所有数据将被存入我们将开发的门户网站。

PROJECT SUMMARY The nature and function of ocular surface nerves play a critical role in maintaining ocular surface health while preventing disease. Disruption of ocular surface sensory nerves can lead to blinding keratitis, graft rejection, dry eye disease, and ocular surface pain. The advent of “-omics” studies have provided a platform to understand how ocular surface nerves participate in the broader context of ocular health and disease. Here, we outline a proposal that will create large datasets detailing the nature of ocular surface innervation. We will take a systems-level approach towards analyzing our data using bioinformatics and machine learning platforms, so that we can gain a practical understanding of the ocular surface environment during health and disease. Specifically, this proposal will address how ocular surface nerves, epithelial cells, and immune cells interact. We have recruited a multidisciplinary research team that consists experts in ophthalmology, neuroimmunology, neurology, proteomics, systems immunology, and bioinformatics. With this team, we plan to comprehensively analyze all three levels of research outlined in the RFA, which includes anatomical and morphological characterization, defining cellular and molecular properties of neuronal and non-neuronal cell types, and assessing functional properties of neuronal and non-neuronal cells. Because innervation patterns and functionality changes with disease, we will use multiple ocular surface disease models (viral keratitis and aqueous dry eye disease) to better understand how neurons, epithelial cells, and immune cells affect neuronal functionality and subsequent disease. We will achieve our goal by pursuing four specific aims: 1) We will perform single-cell (sc)-omics on neuonrs and non-neuronal cells of the cornea and ocular surface innervating ganglia. These data will characterize neuronal identities and describe their functionality during disease. Additionally, we will be able to molecularly characterize immune and epithelial cells that influence the functionality of ocular surface afferents during disease. 2) We will use mass spectrometry to analyze the proteomic signatures of the cornea during health and disease. An unbiased shotgun approaches and a targeted approach focusing on neurotrophic factors will be used to identify proteins that influence ocular surface nerve functionality. 3) We will use our imaging techniques and histocytometry to comprehensively analyze the location and morphology of neuronal and non-neuronal cells within the cornea, so that we may be able to make conclusions about how nerves, epithelial, and immune cells interact in close proximity at the ocular surface. 4) We will use DREADD (designer receptor exclusively activated by designer drugs) technology to perturb neuronal sensitivity, so that we can assess how altering neuronal responsiveness to stimuli may affect the ocular surface homeostasis and progress of disease. A systems-level analysis of our observations using machine-learning and bioinformatics will lead to the prediction of novel interaction networks that can be interrogated in future studies. All data will be deposited into a web portal that we will develop.