Photocleavable Mass-Tags for Spatial Multiomics of Alzheimer’s Brain Tissue

摘要/摘要 阿尔茨海默病（Alzheimer's Disease，AD）是一种慢性神经退行性疾病， 痴呆AD目前影响美国超过620万人，全球约3000万人， 65岁以上的占70%。到2050年，AD的公共卫生总成本预计将超过20万亿美元。尽管 广泛努力开发AD疗法，包括小分子、单克隆抗体和基于肽的 药物，只有aducanumab，其疗效值得怀疑，自2004年以来已被FDA批准。一项重大挑战 正在阐明AD的分子病理学，以开发有效的早期诊断和药物。 虽然由于不同Aβ-肽的聚集而形成淀粉样斑块一直是一个重要的焦点，但无数的 其他分子包括tau、神经元和神经胶质受体、内体-溶酶体相关蛋白，聚糖， 磷脂、胆固醇和代谢物也与AD病理学有关。为了获得详细的 了解这些不同分子种类的可能作用以及候选药物的分子靶向 药物，迫切需要开发足够强大的，高度多路复用和多组学的组织成像 技术，可以映射在细胞分辨率的二维空间分布和这些不同的，AD 分子玩家拟议的第二阶段项目旨在通过采用一种新的高度- 多重靶向方法称为质谱成像免疫组织化学（MSI-IHC™）。MSI- IHC™基于AmberGen开发的新型光可裂解质量标签（PC-MT）的使用， 与抗体或凝集素探针的结合使得能够在质谱图像中识别目标生物分子。这 这种方法大大超过了荧光免疫组织化学（IHC）和以前的多重能力， 通常限于5种生物标志物或需要大量循环的基于可裂解质量标签的方法 在荧光的情况下的程序。此外，将联合收割机MSI-IHC™与无标记、非靶向的免疫组织化学方法结合的能力， 小分子质谱成像（MSI）以及荧光IHC成像，在同一样品上， 扩展它的力量。这是可能的，使用独特的双标记荧光-PC-MT探针，并进行2轮 关于MSI总之，这些创新可以提供一个更全面的多组学图片的作用， AD病理学中的各种分子。在第一阶段，我们已经证明了这种方法在小鼠身上的可行性， 人脑组织样本，包括同时成像多种AD相关分子的能力。在 第二阶段，我们将在此基础上，将MSI-IHC™应用于人类和转基因AD小鼠脑组织 从合作者和商业来源获得。一个目标，与R. A.教授合作。纽约大学的尼克松 领导AD研究人员，将调查神经元内体功能障碍的作用，最早已知的 AD特有的病理生物学使用新的统计物理和AI方法进行图像分析 以前开发用于AD组织和脑成像。

Summary/Abstract Alzheimer's Disease (AD) is a chronic neurodegenerative disorder characterized by progressively worsening dementia. AD currently affects over 6.2 million persons in the U.S. and approximately 30 million world-wide with 70% over the age of 65. The total public health cost of AD is expected to reach over $20 trillion by 2050. Despite extensive efforts to develop AD therapies including small molecules, monoclonal antibodies and peptide-based drugs, only aducanumab, whose efficacy is in doubt, has been approved by the FDA since 2004. A major challenge is elucidating the molecular pathology involved in AD in order to develop effective early diagnostics and drugs. While amyloid plaque formation due to aggregation of different Aβ-peptides has been an important focus, a myriad of other molecules including tau, neuronal and glial receptors, endosomal-lysosomal related proteins, glycans, phospholipids, cholesterol and metabolites have also been implicated in AD pathology. In order to obtain a detailed understanding of the possible role of these diverse molecular species as well as the molecular targeting of candidate drugs, there is an urgent need to develop sufficiently powerful, highly multiplexed and multiomic tissue imaging techniques that can map at cellular resolution the 2D-spatial distribution and association of these diverse, AD molecular players. The proposed Phase II project seeks to address this challenge by applying a new highly- multiplexed, targeted method termed mass spectrometric imaging immunohistochemistry (MSI-IHC™). MSI- IHC™ is based on the use of novel photocleavable mass-tags (PC-MTs) developed by AmberGen which when linked to antibody or lectin probes enable targeted biomolecules to be identified in the mass spectrometric image. This approach significantly exceeds the multiplex capability of fluorescence immunohistochemistry (IHC) and previous cleavable mass-tag based methods which are generally limited to 5 biomarkers or require extensive cycling procedures in the case of fluorescence. In addition, the ability to combine MSI-IHC™ with label-free, untargeted small molecule mass spectrometric imaging (MSI) as well as fluorescence IHC imaging, on the same sample, greatly extends its power. This is possible using unique double-labeled fluorescent-PC-MT probes and performing 2 rounds of MSI. Together, these innovations can provide a much more comprehensive multiomic picture of the role of various molecules in AD pathology. In Phase I, we have demonstrated the feasibility of this approach on mouse and human brain tissue specimens including the ability to image simultaneously a variety of AD related molecules. In Phase II we will build on this progress by applying MSI-IHC™ to human and transgenic AD mouse brain tissue obtained from collaborators and commercial sources. One goal, in collaboration with Prof. R.A. Nixon at NYU, a leading AD researcher, will be to investigate the role of neuronal endosomal dysfunction, the earliest known pathobiology specific to AD. Image analysis with be performed using novel statistical physics and AI methods previously developed for AD tissue and brain imaging.