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DOI 10.3791/59490

Медицинская библиотека · Journal of visualized experiments : JoVE · 2019

Capturing Small Molecule Communication Between Tissues and Cells Using Imaging Mass Spectrometry.

Zink Katherine E, Dean Matthew, Burdette Joanna E, Sanchez Laura M

СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАVideo-Audio MediaПеревод пока не подготовлен

Аннотация

Imaging mass spectrometry (IMS) has routinely been applied to three types of samples: tissue sections, spheroids, and microbial colonies. These sample types have been analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to visualize the distribution of proteins, lipids, and metabolites across the biological sample of interest. We have developed a novel sample preparation method that combines the strengths of the three previous applications to address an underexplored approach for identifying chemical communication in cancer, by seeding mammalian cell cultures into agarose in coculture with healthy tissues followed by desiccation of the sample. Mammalian tissue and cells are cocultured in close proximity allowing chemical communication via diffusion between the tissue and cells. At specific time points, the agarose-based sample is dried in the same manner as microbial colonies prepared for IMS analysis. Our method was developed to model the communication between high grade serous ovarian cancer derived from the fallopian tube as it interacts with the ovary during metastasis. Optimization of the sample preparation resulted in the identification of norepinephrine as a key chemical component in the ovarian microenvironment. This newly developed method can be applied to other biological systems that require an understanding of chemical communication between adjacent cells or tissues.

Для цитирования: Zink Katherine E, Dean Matthew, Burdette Joanna E, Sanchez Laura M. Capturing Small Molecule Communication Between Tissues and Cells Using Imaging Mass Spectrometry.. Journal of visualized experiments : JoVE. 2019. DOI: 10.3791/59490.

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