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Tissue libraries enable rapid determination of conditions that preserve antibody labeling in cleared mouse and human tissue.
Zwang, Theodore J; Bennett, Rachel E; Lysandrou, Maria; Woost, Benjamin; Zhang, Anqi; Lieber, Charles M; Richardson, Douglas S; Hyman, Bradley T.
Afiliação
  • Zwang TJ; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, United States.
  • Bennett RE; Harvard Medical School, Boston, United States.
  • Lysandrou M; Massachusetts Alzheimer's Disease Research Center, Charlestown, United States.
  • Woost B; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, United States.
  • Zhang A; Harvard Medical School, Boston, United States.
  • Lieber CM; Massachusetts Alzheimer's Disease Research Center, Charlestown, United States.
  • Richardson DS; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, United States.
  • Hyman BT; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, United States.
Elife ; 122023 01 19.
Article em En | MEDLINE | ID: mdl-36656755
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 0.5-1.0 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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento Tridimensional / Anticorpos Limite: Animals / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento Tridimensional / Anticorpos Limite: Animals / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article