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

摘要/摘要 阿尔茨海默病(AD)是一种以进行性恶化为特征的慢性神经退行性疾病 痴呆症。AD目前在美国影响着超过620万人，在全球范围内影响着大约3000万人 70%的人在65岁以上。预计到2050年，AD的公共卫生总成本将超过20万亿美元。尽管 广泛努力开发阿尔茨海默病治疗方法，包括小分子、单抗和多肽 自2004年以来，只有阿杜卡努单抗获得FDA批准，其疗效尚不确定。一项重大挑战 正在阐明阿尔茨海默病的分子病理学，以开发有效的早期诊断和药物。 而由于不同的Aβ多肽聚集而形成的淀粉样斑块一直是一个重要的焦点，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，多聚糖， 磷脂、胆固醇和代谢物也与AD的病理有关。为了获得一个详细的 了解这些不同分子物种的可能作用以及候选分子的靶向 药物，迫切需要发展足够强大、高度多元化和多组体的组织成像 可以在细胞分辨率下绘制这些不同AD的2D空间分布和关联的技术 分子玩家。拟议的第二阶段项目旨在通过应用新的高度- 多重、靶向的方法称为质谱学成像免疫组织化学(MSI-IHC™)。MSI- IHC™是基于AmberGen公司开发的新型可光裂解质量标签(PC-MT)的使用，当连接到 抗体或凝集素探针使目标生物分子能够在质谱学图像中被识别。这 这种方法大大超过了荧光免疫组织化学(IHC)和以前的 基于可切割质量标签的方法，通常限于5个生物标志物或需要广泛的循环 在荧光情况下的程序。此外，将msi-ihc™与无标签、无靶向的 小分子质谱学成像(MSI)和荧光IHC成像，在同一样品上，大大 扩展了它的力量。这是可能的，使用独特的双标记荧光PC-MT探针和执行2轮 MSI的一部分。总而言之，这些创新可以提供一个更全面的多元化的角色图景 AD病理中的各种分子。在第一阶段，我们已经证明了这种方法在鼠标和 人脑组织标本包括同时成像多种AD相关分子的能力。在……里面 第二阶段，我们将在这一进展的基础上，将msi-ihc™应用于人和转基因AD小鼠的脑组织 从合作者和商业来源获得。一个目标是，与纽约大学的R.A.尼克松教授合作， 领先的AD研究人员将调查神经元内体功能障碍的作用，这是已知的最早 阿尔茨海默病特有的病理生物学。使用新的统计物理和人工智能方法进行图像分析 之前为AD组织和大脑成像开发的。

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.