Tissue libraries enable rapid determination of conditions that preserve antibody labeling in cleared mouse and human tissue

  1. Theodore J Zwang  Is a corresponding author
  2. Rachel E Bennett
  3. Maria Lysandrou
  4. Benjamin Woost
  5. Anqi Zhang
  6. Charles M Lieber
  7. Douglas S Richardson
  8. Bradley T Hyman
  1. Massachusetts General Hospital, United States
  2. Stanford University, United States
  3. Harvard University, United States

Abstract

Difficulty achieving complete, specific, and homogenous staining is a major bottleneck preventing the widespread use of tissue clearing techniques to image large volumes of human tissue. In this manuscript, we describe a procedure to rapidly design immunostaining protocols for antibody labeling of cleared brain tissue. We prepared libraries of .5-1.0 mm thick tissue sections that are fixed, pre-treated, and cleared via similar, but different procedures to optimize staining conditions for a panel of antibodies. Results from a library of mouse tissue correlate well with results from a similarly prepared library of human brain tissue, suggesting mouse tissue is an adequate substitute for protocol optimization. These data show that procedural differences do not influence every antibody-antigen pair in the same way, and minor changes can have deleterious effects, therefore, optimization should be conducted for each target. The approach outlined here will help guide researchers to successfully label a variety of targets, thus removing a major hurdle to accessing the rich 3D information available in large, cleared human tissue volumes.

Data availability

All data used in publication can be accessed at the BioImage Archive https://www.ebi.ac.uk/biostudies/studies/S-BIAD479All Matlab code and ImageJ macros used to quantify data can be accessed at https://github.com/tjzwang/IHC

The following data sets were generated

Article and author information

Author details

  1. Theodore J Zwang

    Department of Neurology, Massachusetts General Hospital, Boston, United States
    For correspondence
    tzwang@mgh.harvard.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6815-4482
  2. Rachel E Bennett

    Department of Neurology, Massachusetts General Hospital, Boston, United States
    Competing interests
    No competing interests declared.
  3. Maria Lysandrou

    Department of Neurology, Massachusetts General Hospital, Boston, United States
    Competing interests
    No competing interests declared.
  4. Benjamin Woost

    Department of Neurology, Massachusetts General Hospital, Boston, United States
    Competing interests
    No competing interests declared.
  5. Anqi Zhang

    Department of Chemical Engineering, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6121-8095
  6. Charles M Lieber

    Department of Chemistry and Chemical Biology, Harvard University, Cambridge, United States
    Competing interests
    No competing interests declared.
  7. Douglas S Richardson

    Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3189-2190
  8. Bradley T Hyman

    Department of Neurology, Massachusetts General Hospital, Boston, United States
    Competing interests
    Bradley T Hyman, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7959-9401

Funding

National Institute on Aging (NIA-K99AG068602)

  • Theodore J Zwang

Massachusetts General Hospital (Harrison Gardner,Jr Innovation Award)

  • Theodore J Zwang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Albert Cardona, University of Cambridge, United Kingdom

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the mice were handled according to approved institutional animal care and use committee (IACUC protocol # 2019N000026 and 2020N000069).

Human subjects: Autopsy tissue from human brains were collected at Massachusetts General hospital, with informed consent of patients or their relatives and approval of local institutional review boards. Human tissue was provided by the Massachusetts Alzheimer's Disease Research Center (ADRC) with approval from the Mass General Brigham IRB (1999P009556).

Version history

  1. Preprint posted: May 26, 2022 (view preprint)
  2. Received: October 11, 2022
  3. Accepted: January 18, 2023
  4. Accepted Manuscript published: January 19, 2023 (version 1)
  5. Version of Record published: January 31, 2023 (version 2)
  6. Version of Record updated: February 10, 2023 (version 3)
  7. Version of Record updated: March 3, 2023 (version 4)

Copyright

© 2023, Zwang et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Theodore J Zwang
  2. Rachel E Bennett
  3. Maria Lysandrou
  4. Benjamin Woost
  5. Anqi Zhang
  6. Charles M Lieber
  7. Douglas S Richardson
  8. Bradley T Hyman
(2023)
Tissue libraries enable rapid determination of conditions that preserve antibody labeling in cleared mouse and human tissue
eLife 12:e84112.
https://doi.org/10.7554/eLife.84112

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https://doi.org/10.7554/eLife.84112

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