Flow cytometric method for the detection and quantification of retinal cell death and oxidative stress
Retinal cell death is the major cause of vision loss in many forms of blinding retinal disease. A plethora of research is focused on understanding the mechanisms of retinal cell death to identify potential neuroprotective strategies that prevent vision loss in these diseases. Traditionally, histolog...
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Veröffentlicht in: | Experimental eye research 2023-08, Vol.233, p.109563-109563, Article 109563 |
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Zusammenfassung: | Retinal cell death is the major cause of vision loss in many forms of blinding retinal disease. A plethora of research is focused on understanding the mechanisms of retinal cell death to identify potential neuroprotective strategies that prevent vision loss in these diseases. Traditionally, histological techniques have been used to determine the type and extent of cell death in the retina. These techniques, such as TUNEL labeling and immunohistochemistry, are laborious and time consuming, resulting in low throughput and variable results depending on the experimenter. To increase throughput and reduce variability, we developed several flow cytometry-based assays to detect and quantify retinal cell death. The methods and accompanying data presented demonstrate that flow cytometry can readily detect both retinal cell death and oxidative stress and importantly, the efficacy of neuroprotective agents. These methods will be of interest to investigators looking to increase throughput and efficiency without compromising sensitivity as the methods herein reduce analysis time from several months to less than a week. As such, the flow cytometry methods presented have the potential to expedite research efforts focused on developing novel strategies for retinal cell neuroprotection.
•Flow cytometry can reliably detect and quantitate cell death markers in dissociated retinal cells.•Neuroprotective strategies can be quickly assessed for efficacy using flow cytometry.•Oxidative stress markers in retinal cells can be efficiently quantified using flow cytometry. |
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ISSN: | 0014-4835 1096-0007 1096-0007 |
DOI: | 10.1016/j.exer.2023.109563 |