Molecular Probe Optimization to Determine Cell Mortality in a Photosynthetic Organism (Microcystis aeruginosa) Using Flow Cytometry

Microbial sub populations in field and laboratory studies have been shown to display high heterogeneity in morphological and physiological parameters. Determining the real time state of a microbial cell goes beyond live or dead categories, as microbes can exist in a dormant state, whereby cell division and metabolic activities are reduced. Given the need for detection and quantification of microbes, flow cytometry (FCM) with molecular probes provides a rapid and accurate method to help determine overall population viability. By using SYTOX Green and SYTOX Orange in the model cyanobacteria Microcystis aeruginosa to detect membrane integrity, we develop a transferable method for rapid indication of single cell mortality. The molecular probes used within this journal will be referred to as green or orange nucleic acid probes respectively (although there are other products with similar excitation and emission wavelengths that have a comparable modes of action, we specifically refer to the fore mentioned probes). Protocols using molecular probes vary between species, differing principally in concentration and incubation times. Following this protocol set out on M.aeruginosa the green nucleic acid probe was optimized at concentrations of 0.5 μM after 30 min of incubation and the orange nucleic acid probe at 1 μM after 10 min. In both probes concentrations less than the stated optimal led to an under reporting of cells with membrane damage. Conversely, 5 μM concentrations and higher in both probes exhibited a type of non-specific staining, whereby 'live' cells produced a target fluorescence, leading to an over representation of 'non-viable' cell numbers. The positive controls (heat killed) provided testable dead biomass, although the appropriateness of control generation remains subject to debate. By demonstrating a logical sequence of steps for optimizing the green and orange nucleic acid probes we demonstrate how to create a protocol that can be used to analyse cyanobacterial physiological state effectively