Background

Cyanobacteria are a monophyletic group of Gram-negative bacteria that are found in a variety of habitats and produce oxygen similar to higher plants during photosynthesis (Dvořák et al., 2017). Cyanobacteria have evolved different mechanisms to adapt to a wide range of environmental conditions. These ecologically important organisms are well-known for their significant contribution to global carbon dioxide and nitrogen fixation, and as a result, they contribute significantly to the productivity of ecosystems (Kanno et al., 2017). Cyanobacteria have shown their potential in bioenergy and valuable chemical production due to their minimal growth requirements, high photosynthetic efficiency, amenability to genetic modification, and installation of novel metabolic pathways in their primary metabolic chassis (Rajneesh et al., 2017a). However, oxidation and reduction processes related to photosynthesis and respiration are affected by changing environmental conditions such as light quality and quantity, pH, salinity, temperature, and nutrient limitation. Altered oxidation and reduction processes in cyanobacterial thylakoid membranes result in generation of reactive oxygen species (ROS), which consequently cause oxidative stress (Niyogi, 1999). Increased levels of ROS in cyanobacteria are known to damage lipids, DNA, RNA, pigments, and proteins. ROS also results in photoinhibition due to damage to the oxygen-evolving complex and the D2 protein of photosystem II (Niyogi, 1999; Latifi et al., 2009). As a result, the development, growth, and survival of cyanobacterial cells are impaired by high levels of ROS that are generated under fluctuating environmental conditions (Niyogi, 1999; Latifi et al., 2009). Therefore, rapid and accurate methods to measure ROS are required for monitoring the health of cyanobacterial cells in cultivation systems that are used in commercial setups as well as in basic biological studies.

Earlier, we developed a method to measure ROS levels in cyanobacteria using 2′,7′-dichlorodihydrofluorescein-diacetate (DCFH-DA), a live cell-permeable fluorescent probe that can be visualized by fluorescence microscopy (Rastogi et al., 2010; Rajneesh et al., 2017b). DCFH-DA is a well-known fluorescent probe for detecting ROS in live cells. It hydrolyzes inside the cell to DCFH by the activity of esterases. DCFH cannot cross the cell membrane, and it is mostly non-fluorescent, but it emits green fluorescence when oxidized to dichlorofluorescein (DCF) by intracellular ROS (Kalyanaraman et al., 2012). The intensity of green fluorescence can be measured at 530 nm after excitation at 485 nm. Previous methods have been widely used to measure ROS levels in various organisms in addition to cyanobacteria (Rastogi et al., 2010; Rajneesh et al., 2017b; Li et al., 2017; Basso et al., 2018). However, despite its wide application, fluorescence microscopy-based methods are limited to small sample sizes (the number of cells analyzed is an individual choice, but analysis of at least 50 cells per replicate is recommended), and therefore, the entire population is not well represented (Mondal et al., 2020). Also, imaging a large number of cells in the darkroom is not easy as it is a time-consuming process, and longer exposure of samples to excitation light could result in a high background of green fluorescence due to photooxidation of the dye. Regular imaging for longer periods can also cause dry, itchy, and weary eyes, as well as headaches. Cell morphology is another disadvantage of fluorescence microscopy-based ROS monitoring, as visualizing and estimating ROS in small spherical shape cells is not possible (Mondal et al., 2020). However, FCM-based ROS-monitoring methods overcome the abovementioned limitations of fluorescence microscopy-based methods and provide a high-throughput platform to monitor the ROS in a large number of cells of various morphology. Furthermore, it allows simultaneously recording data on cell size and shape, granularity, chlorophyll, and phycobiliproteins while monitoring the ROS levels. The forward scatter (FSC) parameter of FCM provides information about cell size and shape, while the internal complexity, i.e., granularity, of a cell can be determined by measuring side scatter. Granules and the nucleus are two cellular components that influence side scatter; however, the nucleus is absent in cyanobacteria. Similar to fluorescence microscopy-based ROS-detection methods described earlier (Rastogi et al., 2010; Rajneesh et al., 2017b), this protocol can be optimized for different organisms for successful monitoring of ROS.