A versatile approach for highly multiplexed, high-resolution imaging of endogenous molecules

一种对内源性分子进行高度多重、高分辨率成像的通用方法

基本信息

批准号：
10505946
负责人：
LINNAEA E OSTROFF
金额：
$ 224.25万
依托单位：
UNIVERSITY OF CONNECTICUT STORRS
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2025-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10505946
关键词：
3-Dimensional Antibodies Array tomography Biological Models Brain Brain Mapping Cells Complex Data Data Analyses Data Collection Data Set Detection Devices Electron Microscopy Ensure Fluorescent in Situ Hybridization Gene Expression Goals Heterogeneity Image Image Analysis Imaging Device Immunoelectron Microscopy Impairment Individual Label Laboratories Manuals Maps Methods Microscopy Molecular Neurons Neurosciences Pattern Periodicity Plant Resins Preparation Procedures Process Proteins Protocols documentation RNA RNA Probes Reagent Reproducibility Research Resolution Rodent Sampling Software Tools Specimen Stains Structure System Techniques Time Tissue Sample Tissues Training Validation artificial intelligence algorithm automated algorithm base brain cell brain tissue cost design experimental study high resolution imaging image registration imaging approach imaging modality innovation instrument large datasets microscopic imaging molecular marker multiplexed imaging neuronal cell body next generation novel novel strategies routine imaging tool transcriptomics user friendly software

项目摘要

Project Summary The quest to understand the brain’s complex structure has become more challenging as the high degree of molecular heterogeneity among brain cells has become evident in recent years. Mapping the brain in detail will require incorporating large amounts of molecular information into high-resolution imaging. Current imaging methods are limited by the number of distinguishable detection channels, so greater degrees of multiplexing entail repeated cycles of stripping and reapplying probes. These methods degrade tissue integrity and impair sensitivity, and do not address the other major challenge of multiplexing- incompatibility between protein and RNA labeling methods and the need to compromise both for simultaneous detection. We propose a novel imaging approach, Serial-section parallel immuno/ Fluorescence In Situ Hybridization (SpiFISH), whose core strategy is to physically subdivide specimens into sections two orders of magnitude smaller than a neuronal cell body. Each section is treated as a separate sample for labeling and imaging, so hundreds of discrete labeling experiments can be performed in parallel on a given neuron. The method is based on ultrathin sectioning, but unlike existing ultrathin sectioning methods such as electron microscopy (EM) and array tomography, SpiFISH does not use EM embedding resins. Without resin interfering, sensitive immunolabeling and RNA detection are possible. Each section is labeled and imaged separately, so that any given cell can be labeled with many different antibodies and RNA probes under conditions optimized for each. Sections are shelf-stable, so large datasets can be built up across time and even across laboratories. The method allows multiplexing of techniques as well as labels, so the same sample can be used with multiple imaging and staining platforms. The goal of this project is to develop robust, reproducible protocols and workflows from sample preparation through data analysis across scales. This will include small samples through whole rodent brains and streamlined methods for fully manual through fully automated data collection and analysis.

项目摘要随着高高高高，了解大脑复杂结构的追求变得更加挑战。最近，脑细胞之间的分子异质性程度已明显。细节将需要将大量分子信息纳入高分辨率成像中。成像方法受到可区分检测通道的数量的限制，因此更大的脱脂多重的剥离和重复探针的重复循环降低了组织完整性并损害敏感性，并且不会应对多样化不合适的另一个主要挑战我们提出的蛋白质和RNA标记方法和妥协一种新型的成像方法，位于现场的序列序列平行的imuno/荧光，其核心策略是针对物理细分标本分为各节的两个数量级，而不是一个数量级神经元细胞体。离散的标记实验可以在给定的神经元上并行进行。截面，但与现有的Ultratin截面方法不同，例如电子显微镜（EM）和阵列层析成像，spifish不使用EM嵌入树脂。 RNA检测是可以分别标记和成像的。标记了许多针对每个部分优化的抗体和RNA探针。货架稳定，因此大型数据集可以跨时间甚至在实验室中建立技术和标签的多路复用，因此可以将相同的样本用于多个成像和染色平台。通过跨量表进行样品分析。大脑和简化的方法，用于完全手动，尽管完全自动化的数据收集和分析。