lunes, 21 de agosto de 2017

NIAID Researchers Pioneer Robust New 3D Tissue Imaging Technique | NIH: National Institute of Allergy and Infectious Diseases

NIAID Researchers Pioneer Robust New 3D Tissue Imaging Technique | NIH: National Institute of Allergy and Infectious Diseases

NIH: National Institute of Allergy and Infectious Diseases

NIAID Researchers Pioneer Robust New 3D Tissue Imaging Technique

tissue clearing image 2



NIAID researchers have developed a new method for visualizing in great detail the distribution of cell types in complex tissues, like tumors. The method, called Clearing-enhanced 3D microscopy, or Ce3D, may help researchers evaluate how well immunotherapies target hard-to-treat cancers without many of the limitations associated with related, earlier methods that are currently in use. The findings were described online today in the Proceedings of the National Academy of Sciences.
This video features Clearing-enhanced 3D, or Ce3D, images of a mouse brain. Ce3D is a technology pioneered by NIAID scientists that allows researchers to obtain high resolution 3D images of tissues while differentiating multiple cell types.
When researchers or hospital laboratories seek detailed images of tissue samples, especially from tumors, chemical "tissue clearing" techniques allow them to make dense, opaque tissue transparent. This transparency then allows scientists to use advanced microscopes to identify, count, and determine the distribution of cells of interest that have been marked with fluorescent compounds or distinguishable antibodies.
Currently available tissue clearing methods have substantial limits to how many cell types can be characterized and are often very difficult to use, hampering researchers' ability to obtain a comprehensive understanding of how a patient's immune system is affecting the tumor. Other current methods permit users to count many different cell types present in tissues, but require slicing or grinding up the tissue, losing critical information about the 3D organization of tumor and immune cells in the cancer.
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Ce3D allows scientists to "clear" tissues for easier analysis.
By contrast, Ce3D allows researchers to keep the biopsied tissue intact, mark a large number of different cell types with various tracking techniques, and view the results in 3D. 
The medical community's response to cancerous growths, both in the lab and in the clinic, is becoming increasingly tailored to the nature of individual tumor. Ce3D is a sophisticated way to obtain a lot of information about a particular tumor, which is critical for both researchers trying to evaluate therapies in animal models and physicians evaluating their patients.
tissue clearing figure 2
Ce3D imaging allows scientists to view multiple cell types, shown here marked with assorted colors, that make up complex tissues like this lymph node in three dimensions.
This new development was the result of a collaboration in the laboratory of Ronald N. Germain, M.D., Ph.D., chief of the Laboratory of Systems Biology in NIAID's Division of Intramural Research. Using lymphoid tissues of mice, collaborators Michael Gerner, Ph.D., and Weizhe Li, Ph.D., screened various reagents to achieve the optimal combination needed for the new technique. They assessed lymphoid tissue because of its inherent complexity and the level of detail that is needed to accurately interpret how this tissue responds to medication and immunotherapy. After arriving at the components of Ce3D, the researchers also tested the method on lung, intestine, liver, muscle and thymus tissue and produced clear, comprehensive 3D images of each tissue type. Because it uses relatively inexpensive substances and existing lab instruments, the method will not only provide more information but also be more scalable and cost-effective than current tissue clearing methods.


These images of the lymphoid tissue of mice were captured with Ce3D. Each color highlights a different type of immune cell, which can reveal vital information, such as how well a tumor is responding to immunotherapy.
To learn more, read the paper in PNAS:

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