Dual excitation multi-fluorescence flow cytometry for detailed analyses of viability and apoptotic cell transition
AbstractThe discrimination of live/dead cells as well as the detection of apoptosis is a frequent need in many areas of experimental biology. Cell proliferation is linked to apoptosis and controlled by several genes. During the cell life, specific events can stimulate proliferation while others may trigger the apoptotic pathway. Very few methods (i.e. TUNEL) are now available for studies aimed at correlation between apoptosis and proliferation. Therefore, there is interest in developing new methodological approaches that are able to correlate apoptosis to the cell cycle phases. Recently new approaches have been proposed to detect and enumerate apoptotic cells by flow cytometry. Among these, the most established and applied are those based on the cell membrane modifications induced in the early phases of the apoptotic process. The dye pair Hoechst 33342 (HO) and Propidium Iodide (PI), thanks to their peculiar characteristics to be respectively permeable and impermeable to the intact cell membrane, seems to be very useful. Unfortunately the spectral interaction of these dyes generates a consistent “energy transfer” from HO to PI. The co-presence of the dyes in a nucleus results in a modification in the intensity of both the emitted fluorescences. In order to designate the damaged cells (red fluorescence) to the specific cell cycle phases (blue fluorescence), we have tested different staining protocols aimed to minimize the interference of these dyes as much as possible. In cell culture models, we are able to detect serum-starved apoptotic cells as well as to designate their exact location in the cell cycle phases using a very low PI concentration. Using a Partec PAS flow cytometer equipped with HBO lamp and argon ion laser, a double UV/blue excitation has been performed. This analytical approach is able to discriminate live blue cells from the damaged (blue-red) ones even at 0.05 ?g/mL PI. The same instrumental setting allows performing other multi-colour analyses including AnnexinV-FITC as well as the possibility to make a correlated analysis to phenotype markers.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2009 G Mazzini, C Ferrari, E Erba
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.