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

Podsumowanie

Microbial populations contain substantial cell heterogeneity, which can dictate overall behavior. Molecular probe analysis through flow cytometry can determine physiological states of cells, however its application varies between species. This study provides a protocol to accurately determine cell mortality within a cyanobacterium population, without underestimating or recording false positive results.

Streszczenie

Microbial subpopulations 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.

Wprowadzenie

The cell is a complex system, which constantly responds to the environment by modifying physiological parameters and altering its function. The population dynamics of isogenic microbial populations both in nature and the laboratory are affected by the development of subpopulations, occurring even under relatively constant environmental conditions^1-3. The variability of natural microbial communities arises due to the highly variable nature of environmental conditions. These sometimes stochastic processes subsequently produce subpopulations that are very different to the population average. Recent evidence has revealed that these physiological subpopulations respond differently to environmental conditions and can produce signal compounds or inhibitors that dramatically affect and influence the overall population^3,4.

Establishing a method to define heterogeneity within a population is key to understanding the ecology of microbes in various environments and is essential when building knowledge of nuisance cyanobacteria, such as the toxic Microcystis, which impacts heavily on human water security. Species such as Anabaena display morphological heterogeneity in response to environmental fluctuations, developing specialised cells like heterocysts and akinetes². In contrast, Microcystis cells do not display obvious morphological heterogeneity during a stress response. The discrimination between viable and non-viable cells is the most important aspect of physiological differentiation and allows a better understanding of microbial population dynamics. However, the conceptual problem of bacterial viability itself remains difficult and poorly characterised^1,5,6.

Flow cytometry (FCM) is a reliable and rapid method of analysing individual cells. To increase the understanding of single cell physiology through FCM, molecular probes have been used to distinguish a number of metabolic and biochemical processes⁷. This has led to increased knowledge of species on a cellular and population level and in turn helped water resource management^8,9. However, organisms differ in terms of molecular probe uptake and efflux due to the pores and pumps in cellular walls and membranes, which have led to a number of molecular probe design and protocol implementation^6,10,11. Molecular probes available for commercial and research purposes are often supplied with a generic protocol which may be applicable to a very different cell type. One must be very cautious in transferring protocols developed for one cell type to another⁶, it is therefore an essential task to optimize molecular probes effectively before use.

The green and orange nucleic acid probes bind to both double and single stranded nucleic acids with minimal base selectivity and are used to assess the plasma membrane integrity of cells. The green nucleic acid probe has a markedly improved cell labelling fluorescence signal compared to other molecular probes, such as propidium iodide-based compounds¹², which can also act as an indicator of cell viability. The term 'cell viability' here assumes that DNA degradation occurs after the loss of plasma membrane integrity. The nucleic acid probes are unsymmetrical cyanine dyes with three positive charges and cannot enter cells with intact membranes under characterised concentrations, in both eukaryotic^11,13 and prokaryotic^14,15 organisms. The binding of a nucleic acid probe to nucleic acids can result in up to a >500 fold increase of fluorescence emissions from endogenous signals in cells that have their membrane integrity compromised. Although molecular probes such as the green nucleic acid probe can be a good indicator of single cell physiology, there is a need to optimize each probe with the intended target organism, as incubation times have varied from 7 min - 30 min and concentration ranges from 0.1 µM - 0.5 µM in Microcystis experiments alone^15-19.

Here we present a protocol to optimize the cytometric assays of green and the relatively new orange nucleic acid probes (which to date not been tested on the cyanobacterial species M.aeruginosa). The following developed methodology can then be transferred to other species and used as a platform for optimizing protocols in other molecular probes, thereby increasing the understanding of microbes and their ecological behavior.

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Protokół

1. Preparation of the Molecular Probe and Flow Cytometer

1. Dilute stock solutions of the nucleic acid probes, which are supplied as a 5 mM solution in dimethylsulfoxide (DMSO) to aliquots of required concentrations in ultrapure filtered H₂O.
2. Store the nucleic acid probes in dark conditions between -5 ^oC and - 25 ^oC until use.
3. Turn on the flow cytometer and load software package (see table of Materials/Equipment for FCM specifications).
4. Place an empty haemolysis tube (12 x 75 mm) on the sample injection probe (SIP), click unclog and then back flush to start the FCM cleaning process.
   NOTE: Some sample stages for the SIP can accommodate several types of tubes including microcentrifuge tubes.  The molecular probe diluent and sheath fluid used in the FCM apparatus is from an analytical grade “type 1” 0.22 µm membrane filtered source.
5. Place a fresh haemolysis tube with 2 ml of ultrapure filtered H₂O on the SIP, set a time limit for 10 - 15 min and a fluidic speed to fast (or a flow rate of >66 µl/min).
6. Select a new data cell, put on relevant thresholds for fluorescence and light scatter channels to reduce background noise and click 'run'.
7. If the total events per second are not below the manufacturers' recommendation, then run a 2 ml sample of decontamination solution for 2 min on fast and then repeat steps 1.4 & 1.5.
   NOTE: Please check manufacturers’ recommendations for FCM start-up cleaning protocols, as they can vary between models.  Testing for specific thresholds also needs to be in line with the FCM model as some equipment allows the user to apply voltages gains to the photomultiplier tubes (PMTs) enhancing or decreasing the electrical signal recorded from the optical detectors.  The FCM model used in this experiment has fixed voltage PMTs and used a threshold of 80,000 forward light scatter (FSC-H) to exclude particles smaller than 2.0 µm and electronic noise.

2. Preparation of Cultures and Initial Cell Counts

1. Autoclave 98 ml of ultrapure filtered H₂O and 2 ml of algal media (x50 concentration) in a 250 ml beaker for 20 min at 120 ^oC.
2. From an initial monoculture of M.aeruginosa (PCC 7806) in a high steady state density place 2 ml of the sample into a tube under the SIP. Disaggregate any colony formation by vortexing or sonication²⁰ and confirm evenly dispersed cells through light microscopy.
   NOTE: Excessive exposure to ultrasonic waves can lead to cell lysis and should be used with caution.  Since sonication can collapse gas vesicles (as found in species like M.aeruginosa) outputs such as side light scatter (SSC-H) intensity can become more sensitive.
3. Within the FCM software, select a histogram plot to record data from forward light scatter (FSC-H) and configure the plot specifications by clicking "log" to view in a log scale on the axis.
4. In a separate output, select another histogram (log axis) to record natural fluorescence such as the accessory photosynthetic pigment phycocyanin (FL4-H, 675 ± 12.5 nm), found in M.aeruginosa.
5. Use a light source that can excite phycocyanin and a detector which can filter the emissions from the resulting fluorescence.
   NOTE: Photosynthetic pigment such as chlorophyll can be excited with the commonly used 488 nm blue laser, whereas phycocyanin is excited over 600 nm and will only be detected with a red light source²¹.  Check with the flow cytometers manufacturer for excitation light sources and the spectra of emission detectors, here both a 488 nm and a 640 nm laser were used along with a 675 ± 12.5 nm optical filter.
6. For recording of the highest resolution select settings closest to the core size of the target organism (10 µm) and a relatively slow flow rate (14 µl/min).
   NOTE: For the best resolution samples should be run according to manufactures recommendation of events per second.
7. Before acquiring data use a threshold to gate out light scatter and / or fluorescence signals that are caused by electronic background noise or cell sample debris.
8. Select a new data cell, create a density plot with FSC-H and SSC-H parameters on a log scale and click run.
9. If sample density leads to an excessive event rate, dilution steps can be taken to increase accuracy and precision.
10. On the density plot apply software gates from the previous histogram to exclude low level scatter signals, produced by background noise or debris (FSC <320,000). Conversely gate the higher relative fluorescence phycocyanin signals from cells and only include these events (FL4, 56,000 - 1,950,000).
11. Use the number of cells recorded in the gated areas and divide it by the total volume of sample that has passed through the FCM, to work out how many cells per ml.
    NOTE: The FCM model used here has a microprocessor controlled peristaltic pump system allowing sample volume to be determined.  Other FCM equipment may require a calibrated bead suspension or a calculation of H₂O weight/volume differences to verify total sample volume.
12. Add the required volume of cells to the freshly prepared media in order to start a batch growth cycle (250,000 cells/ml) of M.aeruginosa.
    NOTE: Species will differ in growth rates depending on their in-situ environment parameters and nutrient availability, so a batch cycle should be pre-recorded to determine life cycle phases.

3. Optimization of Molecular Probe Cell Uptake

1. Harvest half of the M.aeruginosa culture prepared in step 2 from an exponential phase and use as a 'live' control.
   NOTE: Samples diluted from a high density culture straight to an exponential phase may affect optimization results through dead cell turnover, compared to that of cultures inoculated from an initial lag / induction phase.
2. Prepare the other half as a 'dead' control by using methods such as 70% ethanol, heating samples at 60 ^oC for 1 hr, paraformaldehyde or 4% formaldehyde for 30 min^6,11,22. Check variations in the samples microenvironment (e.g., pH).
   NOTE: The positive, heat-killed, ‘dead’ control in M.aeruginosa is distinguished from a ‘live’ sample through its decrease in phycocyanin signals.  Inducing mortality by other methods may not cause the same output and will vary in species.
3. Set up mixed samples using different ratios of 'live' and 'dead' samples (e.g., 0%, 25%, 50%, 100%).
4. Disaggregate colony formation by vortexing or sonication and check pH.
5. Select a 488 nm laser alongside detectors which can record fluorescence from the green (FL1, 530 ± 15 nm) and orange (FL2, 585 ± 20 nm) nucleic acid probes and the 640 nm laser to record phycocyanin signals through its respective detector.
   NOTE: When bound to DNA, the green nucleic acid probe has an approximate fluorescence excitation wavelength of 504 nm and emission maxima of 523 nm, whilst the orange nucleic acid probe has an excitation wavelength of 547 nm and emissions maxima of 570 nm.  A 488 nm argon ion solid state laser can be employed to excite both molecular probes, however, a green laser (up to 547 nm) will produce a higher orange fluorescence.
6. As a starting point, introduce the molecular probe with manufacturers recommended concentration to the 50% 'live' and 50% 'dead' culture and incubate in the dark.
7. Select a new data cell, place the sample under the SIP with thresholds and triggers that will reduce background noise (FSC-H 80,000).
8. Create a density plot with FSC-H and SSC-H parameters, and three histograms. One histogram using the respective molecular probe optical detector channel (FL1 or 2), one to detect phycocyanin emissions (FL4-H) and the other FSC-H, all on a log scale.
9. Incubate the samples of M.aeruginosa with the nucleic acid probes in darkness for up to 60 min, recording in separate data cells, at a number of time points (1, 5, 10, 15, 30 and 60 min).
   NOTE: When adjusting parameters such as pH check with manufactures for potential reactions from certain chemicals (for the tested nucleic acid probes a buffer cannot contain phosphates or high levels of monovalent or divalent cations, as the binding with DNA will be reduced).
10. Apply a software gate to only include the FSC-H histogram (320,000 - 1,500,000) for the target organisms cell size, into the respective fluorescence probe channel histogram.
    NOTE: The concentrations used in this protocol were 0.05, 0.1, 0.5, 1, 5, 10, 50 and 100 µM, which can be altered by either increasing or decreasing the volume of M.aeruginosa sample or initial stock solution of nucleic probes.
11. In the fluorescence probe channel, apply another inclusive software gate to the highest peak in the histogram (green FL1-H, 240,000 - 1,650,000, orange FL2-H, 30,000 - 165,000) and subsequently gate that positive probe fluorescence into the density plot.
12. Run steps 3.1 - 3.11 with 100% "live", 100% 'dead' and all mixed culture samples, adjusting the molecular probe concentrations (e.g x 0.1 to x 10) and / or temperature and pH levels if necessary.
13. Compare the number of positive molecular probe fluorescence signals to the original cell density of 'dead' cells (taken from half total FSC-H or a 100% 'dead' culture) to find the total percentage of cells stained with the nucleic acid probes.
14. Do this for each time period within each concentration to find the optimal protocol for the highest percentage of cell nucleic probe uptake without producing non-specific staining (use the means in a One-Way ANOVA or Kruskal-Wallis one-way analysis of variance, if the data is non-parametric).

4. Molecular Probe Fluorescence Discrimination

1. For testing of fluorescence interference / overlap from intrinsic or non-specific cell staining select the 50% 'live' and 50% 'dead' mixed culture data and take off all gates.
2. Apply a software gate to only include the FSC-H histogram (320,000 - 1,500,000) for the target organisms cell size, into the phycocyanin channel histogram.
3. Gate the highest phycocyanin peak and label as 'live', with the addition of the lowest peak labelled as 'dead'.
4. Perform a further gate step into the respective molecular probe fluorescence histogram channel, using one at a time, the 'live' and then 'dead' phycocyanin (FL4) signals, recording both mean wavelengths.
   NOTE:  The mode for inducing mortality in this experiment was done by heat treatment, which under this protocol clearly decreases phycocyanin signals.  Other methods of producing populations of ‘dead’ cells may yield different outputs in the acquired runs.
5. Ratio the mean wavelengths of the positive molecular probe fluorescence ('dead') and the intrinsic / non-specific signal ('live') to determine protocol sensitivity.
   NOTE: To improve fluorescence discrimination of ‘live’ and ‘dead’ populations, increase the carbon source to active stain uptake in nutrient depleted cells or ethylenediaminetetraacetic acid (EDTA) to improve cell wall permeability and resulting fluorescence signals⁶.  Limited compensation in some FCM models for spectral overlap can be performed by user-manipulated pairwise correction during sample acquisition (PMT voltage changes) or from post-analytical specialised software.
6. Select the optimized protocol where the highest amount of 'dead' cells has been stained without the occurrence non-specific staining. If a number of test have similar results accept the protocol with the lowest concentration and incubation time, along with good fluorescence signal discrimination. Follow manufactures instructions for the cytometer shutdown procedure.

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Wyniki

Forward light scatter (FSC) and side light scatter (SSC) outputs from an M.aeruginosa batch culture in exponential phase provides information on cell size (diameter) and internal granularity respectively (Figure 1A). FSC can discriminate cells that are too large and / or small to be M.aeruginosa. This discrimination or gating can be done by refining data between certain points of a FSC output (Figure 1C). Phycocyanin, a major constitutio...

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Dyskusje

The increased numbers of publications using molecular probes indicates that reliable and informative data can be obtained^{5,6,8-15,19,22,23}. As of yet there is no perfect stain for cell viability that can be effective across all species with the same concentration and incubation time^6,10. Even the same type of probe with altered fluorescence emissions shows a need to establish the correct concentration and incubation time (Tables 1 & 3). As seen when using t...

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Materiały

Name	Company	Catalog Number	Comments
Cyanobacteria Media	Sigma-Aldrich	C3061-500ML	BG-11 Freshwater concentrated solution (x50 dilution)
Decontamination Fluid	BD Biosciences	653155	Run for 2 min when outputs are more than 12 events per second on fast or a flow rate of 66 µl/min.  Followed by 2 min of sheath H2O.
Flow Cytometer	BD Biosciences	by request	BD Accuri C6
SYTOX Green	Life Technologies	S7020	Nucleic acid stain – 5 mM solution in DMSO
SYTOX Orange	Life Technologies	S11368	Nucleic acid stain – 5 mM solution in DMSO