Cellular High-Energy Cavitation Trauma - Description of a Novel In Vitro Trauma Model in Three Different Cell Types.
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Cao Y, Risling M, Malm E, Sondén A, Bolling MF, Sköld MK
Front Neurol 7 (-) 10 [2016-02-01; online 2016-02-01]
The mechanisms involved in traumatic brain injury have yet to be fully characterized. One mechanism that, especially in high-energy trauma, could be of importance is cavitation. Cavitation can be described as a process of vaporization, bubble generation, and bubble implosion as a result of a decrease and subsequent increase in pressure. Cavitation as an injury mechanism is difficult to visualize and model due to its short duration and limited spatial distribution. One strategy to analyze the cellular response of cavitation is to employ suitable in vitro models. The flyer-plate model is an in vitro high-energy trauma model that includes cavitation as a trauma mechanism. A copper fragment is accelerated by means of a laser, hits the bottom of a cell culture well causing cavitation, and shock waves inside the well and cell medium. We have found the flyer-plate model to be efficient, reproducible, and easy to control. In this study, we have used the model to analyze the cellular response to microcavitation in SH-SY5Y neuroblastoma, Caco-2, and C6 glioma cell lines. Mitotic activity in neuroblastoma and glioma was investigated with BrdU staining, and cell numbers were calculated using automated time-lapse imaging. We found variations between cell types and between different zones surrounding the lesion with these methods. It was also shown that the injured cell cultures released S-100B in a dose-dependent manner. Using gene expression microarray, a number of gene families of potential interest were found to be strongly, but differently regulated in neuroblastoma and glioma at 24 h post trauma. The data from the gene expression arrays may be used to identify new candidates for biomarkers in cavitation trauma. We conclude that our model is useful for studies of trauma in vitro and that it could be applied in future treatment studies.
Bioinformatics and Expression Analysis (BEA) [Service]
PubMed 26869990
DOI 10.3389/fneur.2016.00010
Crossref 10.3389/fneur.2016.00010