Background

When a cell dies and loses the integrity of the cell membrane, electrolytes, such as K⁺ ions, leak out of the cell. Thus, we can use the amount of electrolytes leaked from a tissue as a proxy for the extent of cell death in the tissue. A simple way to quantify such electrolytes leaked from a tissue is to measure the increase in electrolytic conductivity of water that contains the tissue with dying cells. This electrolyte leakage assay has been applied to plant tissues to assess the relative quantity of cells that died in response to biotic and abiotic stresses, such as pathogen challenge, insect herbivory, wounding, UV radiation, oxidative stress, salinity, drought, cold and heat stress (Demidchik et al., 2014).

The original method was designed to measure the conductivity of the aqueous bathing solution containing plant tissues before and after boiling it, in which the conductivity after boiling was used to normalize tissue size differences (Whitlow et al., 1992). Here we describe a procedure to dynamically monitor electrolyte leakage from leaf disks by measuring at multiple time points the electrolytic conductivity of water on which the leaf disks float in a 12-well plate. It is reasonable to assume that the total amount of electrolytes from tissue samples of the same size, such as disks of the same area punched out from leaves of a similar developmental stage, is comparable and that it is not necessary to measure the electrolytic conductivity after boiling the tissues. We inoculated leaves with the bacterial pathogen, Pseudomonas syringae pv. tomato DC3000 pVSP61-avrRpt2 (Pto DC3000 avrRpt2) in order to trigger a type of programmed cell death, known as hypersensitive cell death. The protocol presented here has been applied to our studies (Igarashi et al., 2013; Bethke et al., 2016; Hatsugai et al., 2016; Hatsugai et al., 2017) and could also be used to quantify plant cell death triggered by any other stimuli. If detailed comparisons of the time courses of the electrolyte leakage are needed, fitting polynomial regression to the time courses is possible (Van Poecke et al., 2007; Qi et al., 2010), as it is easy to obtain electrolytic conductivity measurements at many time points with many replicates.