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de Leeuw SM, Nuriel T. Intracellular cholesterol visualization in brain tissue using D4H ∗. STAR Protoc 2024; 5:102779. [PMID: 38100357 PMCID: PMC10762518 DOI: 10.1016/j.xpro.2023.102779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 10/31/2023] [Accepted: 11/30/2023] [Indexed: 12/17/2023] Open
Abstract
Studying cholesterol biology in the brain has been greatly hindered by the lack of adequate cholesterol visualization techniques. Here, we present a protocol for using a high-affinity cholesterol probe D4H∗-mCherry as a histology reagent in mouse or human brain tissue. We describe steps for D4H∗ tissue treatment and crosslinking leading to stable labeling of intracellular membrane cholesterol. Furthermore, co-labeling with Rab5 endosomal marker and optimized buffers to reduce background enable punctate cholesterol visualization within the organelle membranes.
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Affiliation(s)
- Sherida M de Leeuw
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, 630 West 168th Street, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, 630 West 168th Street, New York, NY 10032, USA.
| | - Tal Nuriel
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, 630 West 168th Street, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, 630 West 168th Street, New York, NY 10032, USA.
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Liu B, Li Y, Ren M, Li X. Targeted approaches to delineate neuronal morphology during early development. Front Cell Neurosci 2023; 17:1259360. [PMID: 37854514 PMCID: PMC10579594 DOI: 10.3389/fncel.2023.1259360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 09/18/2023] [Indexed: 10/20/2023] Open
Abstract
Understanding the developmental changes that affect neurons is a key step in exploring the assembly and maturation of neural circuits in the brain. For decades, researchers have used a number of labeling techniques to visualize neuronal morphology at different stages of development. However, the efficiency and accuracy of neuronal labeling technologies are limited by the complexity and fragility of neonatal brains. In this review, we illustrate the various labeling techniques utilized for examining the neurogenesis and morphological changes occurring during the early stages of development. We compare the advantages and limitations of each technique from different aspects. Then, we highlight the gaps remaining in our understanding of the structure of neurons in the neonatal mouse brain.
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Affiliation(s)
- Bimin Liu
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Yuxiao Li
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Miao Ren
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Xiangning Li
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
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