Improved methods for rapid and scalable tissue clearing and labeling

• Main Author: Murray, Evan (Evan T.)
• Other Authors: Kwanghun Chung.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2017
• Subjects: Brain and Cognitive Sciences.
• Online Access: http://hdl.handle.net/1721.1/107879

Thesis: S.M. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 55-58). === Combined measurement of diverse molecular and anatomical traits that span multiple levels remains a major challenge in biology. Here, we introduce a simple method that enables proteomic imaging for scalable, integrated, high-dimensional phenotyping of both animal tissues and human clinical samples. This method, termed SWITCH, uniformly secures tissue architecture, native biomolecules, and antigenicity across an entire system by synchronizing the tissue preservation reaction. The heat- and chemical-resistant nature of the resulting framework permits multiple rounds (>20) of relabeling. We have performed 22 rounds of labeling of a single tissue with precise co-registration of multiple datasets. Furthermore, SWITCH synchronizes labeling reactions to improve probe penetration depth and uniformity of staining. With SWITCH, we performed combinatorial protein expression profiling of the human cortex and also interrogated the geometric structure of the fiber pathways in mouse brains. Such integrated high-dimensional information may accelerate our understanding of biological systems at multiple levels. === by Evan Murray. === S.M. in Neuroscience