Name: molecular probe optimization to determine cell mortality in a photosynthetic organism (microcystis aeruginosa) using flow cytometry
Uploaded: 2016-01-29T13:00:00
Description: Watch this Scientific Journal Video about Molecular Probe Optimization to Determine Cell Mortality in a Photosynthetic Organism Microcystis aeruginosa Using Flow Cytometry at JoVE.com

The authors would like to acknowledge PhD student Dave Hartnell and&#160;&#160;Bournemouth University for support and funding for the research and facilities.

1. Preparation of the Molecular Probe and Flow Cytometer
<ol>
	<li>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.</li>
	<li>Store the nucleic acid probes in dark conditions between -5 oC and - 25 oC until use.</li>
	<li>Turn on the flow cytometer and load software package (see table of Materials/Equipment for FCM specifications).</li>
	<li>Place an empt...

<ol>
	<li>Kell, D. B., Kaprelyants, A. S., Weichart, D. H., Harwood, C. R., Barer, M. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Viability+and+Activity+in+Readily+Culturable+Bacteria:+A+Review+and+Discussion+of+the+Practical+Issues.">Viability and Activity in Readily Culturable Bacteria: A Review and Discussion of the Practical Issues.</a> Anton. Leeuw. Int. J. G. 73, 169-187 (1998).</li><li>Adams, D. G., Duggan, P. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tansley+Review+No.+107.+Heterocyst+and+Akinete+Differentiation+in+cyanobacteria.">Tansley Review No. 107. Heterocyst and Akinete Differentiation in cyanobacteria.</a> New Phytol. 144 (1), 3-33 (1999).</li><li>Lidstrom, M. E., Konopka, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Role+of+Physiological+Heterogeneity+in+Microbial+Population+Behavior.">The Role of Physiological Heterogeneity in Microbial Population Behavior.</a> Nat. Chem. Biol. 6 (10), 705-712 (2010).</li><li>Dagnino, D., de Abreu Meireles, D., de Aquino Almeida, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+of+Nutrient-Replete+Microcystis.+PCC+7806+Cultures+is+Inhibited+by+an+Extracellular+Signal+Produced+by+Chlorotic+Cultures.">Growth of Nutrient-Replete Microcystis. PCC 7806 Cultures is Inhibited by an Extracellular Signal Produced by Chlorotic Cultures.</a> Environ. Microbiol. 8 (1), 30-36 (2006).</li><li>Davey, H. M., Kell, D. B., Weichart, D. H., Kaprelyants, A. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+Microbial+Viability+Using+Flow+Cytometry.">Estimation of Microbial Viability Using Flow Cytometry.</a> Curr. Protoc. Cytom. Chapter. Chapter 11, (2004).</li><li>Davey, H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Life,+Death,+and+In-Between:+Meanings+and+Methods+in+Microbiology.">Life, Death, and In-Between: Meanings and Methods in Microbiology.</a> Appl. Environ. Microb. 77 (16), 5571-5576 (2011).</li><li>Shapiro, H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+7,+Parameters+and+Probes.">Chapter 7, Parameters and Probes.</a> Practical Flow Cytometry. , 273-410 (2003).</li><li>Hammes, F., Berney, M., Wang, Y., Vital, M., K&#246;ster, O., Egli, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow-Cytometric+Total+Bacterial+Cell+Counts+as+a+Descriptive+Microbiological+Parameter+for+Drinking+Water+Treatment+Processes.">Flow-Cytometric Total Bacterial Cell Counts as a Descriptive Microbiological Parameter for Drinking Water Treatment Processes.</a> Water Res. 42 (1-2), 269-277 (2008).</li><li>Wang, Y., Hammes, F., De Roy, K., Verstraete, W., Boon, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Past,+Present+and+Future+Applications+of+Flow+Cytometry+in+Aquatic+Microbiology.">Past, Present and Future Applications of Flow Cytometry in Aquatic Microbiology.</a> Trends Biotechnol. 28 (8), 416-424 (2010).</li><li>Shapiro, H. M., Nebe-von-Caron, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiparameter+Flow+Cytometry+of+Bacteria.">Multiparameter Flow Cytometry of Bacteria.</a> Methods. Mol. Biol. 263, 33-44 (2004).</li><li>Peperzak, L., Brussaard, C. P. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+Cytometric+Applicability+of+Fluorescent+Vitality+Probes+on+Phytoplankton.">Flow Cytometric Applicability of Fluorescent Vitality Probes on Phytoplankton.</a> J. Phycol. 47 (3), 692-702 (2011).</li><li>Roth, B. L., Poot, M., Yue, S. T., Millard, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacterial+Viability+and+Antibiotic+Susceptibility+Testing+with+SYTOX+Green+Nucleic+Acid+Stain.">Bacterial Viability and Antibiotic Susceptibility Testing with SYTOX Green Nucleic Acid Stain.</a> Appl. Environ. Microbiol. 63 (6), (1997).</li><li>Franklin, D., Airs, R., Fernandes, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+Senescence+and+Death+in+Emiliania+huxleyi.+and+Thalassiosira+pseudonana.">Identification of Senescence and Death in Emiliania huxleyi. and Thalassiosira pseudonana.</a> Cell Staining, Chlorophyll Alterations, and Dimethylsulfoniopropionate (DMSP) Metabolism. Limnol. Oceanogr. 57 (1), 305-317 (2012).</li><li>Lebaron, P., Catala, P., Parthuisot, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effectiveness+of+SYTOX+Green+Stain+for+Bacterial+Viability+Assessment.">Effectiveness of SYTOX Green Stain for Bacterial Viability Assessment.</a> Appl. Environ. Microbiol. 64 (7), 2697-2700 (1998).</li><li>Mikula, P., Zezulka, S., Jancula, D., Marsalek, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolic+Activity+and+Membrane+Integrity+Changes+in+Microcystis+aeruginosa.-+New+Findings+on+Hydrogen+Peroxide+Toxicity+in+Cyanobacteria.">Metabolic Activity and Membrane Integrity Changes in Microcystis aeruginosa.- New Findings on Hydrogen Peroxide Toxicity in Cyanobacteria.</a> Eur. J. Phycol. 47 (July), 195-206 (2012).</li><li>Regel, R. H., Brookes, J. D., Ganf, G. G., Griffiths, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Influence+of+Experimentally+Generated+Turbulence+on+the+Mash01+Unicellular+Microcystis+aeruginosa+Strain.">The Influence of Experimentally Generated Turbulence on the Mash01 Unicellular Microcystis aeruginosa Strain.</a> Hydrobiologia. 517 (1-3), 107-120 (2004).</li><li>Kameyama, K., Sugiura, N., Inamori, Y., Maekawa, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characteristics+of+Microcystin+production+in+the+Cell+Cycle+of+Microcystis+viridis.">Characteristics of Microcystin production in the Cell Cycle of Microcystis viridis.</a> Environ. toxicol. 19 (1), 20-25 (2004).</li><li>Gustafsson, S., Hultberg, M., Figueroa, R. I., Rengefors, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+Control+of+HAB+Species+using+Low+Biosurfactant+Concentrations.">On the Control of HAB Species using Low Biosurfactant Concentrations.</a> Harmful Algae. 8 (6), 857-863 (2009).</li><li>Bouchard, J. N., Purdie, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+Elevated+Temperature,+Darkness,+and+Hydrogen+Peroxide+Treatment+on+Oxidative+Stress+and+Cell+Death+in+the+Bloom-Forming+Toxic+Cyanobacterium+Microcystis.">Effect of Elevated Temperature, Darkness, and Hydrogen Peroxide Treatment on Oxidative Stress and Cell Death in the Bloom-Forming Toxic Cyanobacterium Microcystis.</a> J. Phycol. 47 (6), 1316-1325 (2011).</li><li>Reynolds, C. S., Jaworski, G. H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enumeration+of+Natural+Microcystis+Populations.">Enumeration of Natural Microcystis Populations.</a> Br. Phycol. J. 13 (3), 269-277 (1978).</li><li>Marie, D., Simon, N., Vaulot, D., Andersen, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phytoplankton+Cell+Counting+by+Flow+Cytometry.">Phytoplankton Cell Counting by Flow Cytometry.</a> Algal culturing techniques. , 253-268 (2005).</li><li>Assun&#231;ao, P., Antuees, N. T., Rosales, R. S., de la Fe, C., Poveda, C., Poveda, J. B., Davey, H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+cytometric+method+for+the+assessment+of+the+minimal+inhibitory+concentrations+of+antibacterial+agents+to+Mycoplasma+agalactiae.">Flow cytometric method for the assessment of the minimal inhibitory concentrations of antibacterial agents to Mycoplasma agalactiae.</a> Cytom Part A. 69, 1071-1076 (2006).</li><li>Davey, H. M., Kell, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+Cytometry+and+Cell+Sorting+of+Heterogeneous+Microbial+Populations:+The+Importance+of+Single-Cell+Analyses.">Flow Cytometry and Cell Sorting of Heterogeneous Microbial Populations: The Importance of Single-Cell Analyses.</a> Microbiol. rev. 60 (4), 641-696 (1996).</li><li>Franklin, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Explaining+the+Causes+of+Cell+Death+in+Cyanobacteria:+What+Role+for+Asymmetric+Division?.">Explaining the Causes of Cell Death in Cyanobacteria: What Role for Asymmetric Division?.</a> J. Plankton Res. 36 (1), 11-17 (2013).</li><li>Kaprelyants, A. S., Mukamolova, G. V., Davey, H. M., Kell, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+Analysis+of+the+Physiological+Heterogeneity+within+Starved+Cultures+of+Micrococcus+luteus.+by+Flow+Cytometry+and+Cell+Sorting.">Quantitative Analysis of the Physiological Heterogeneity within Starved Cultures of Micrococcus luteus. by Flow Cytometry and Cell Sorting.</a> Appl. Environ. Microbiol. 62 (4), 1311-1316 (1996).</li><li>Waggoner, A., Melamed, M. R., Lindmo, T., Mendelsohn, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescent+probes+for+cytometry.">Fluorescent probes for cytometry.</a> Flow cytometry and sorting. , 209-225 (1990).</li><li>Gray, J. V., Petsko, G. A., Johnston, G. C., Ringe, D., Singer, R. A., Werner-washburne, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=&#34;Sleeping+Beauty&#34;:+Quiescence+in+Saccharomyces+cerevisiae.">&#34;Sleeping Beauty&#34;: Quiescence in Saccharomyces cerevisiae.</a> Microbiol. Mol. Biol. Rev. 68 (2), 187-206 (2004).</li><li>Keer, J. T., Birch, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+Methods+for+the+Assessment+of+Bacterial+Viability.">Molecular Methods for the Assessment of Bacterial Viability.</a> J. Microbiol. Methods. 53 (2), 175-183 (2003).</li></ol>

The increased numbers of publications using molecular probes indicates that reliable and informative data can be obtained5,6,8-15,19,22,23. As of yet there is no perfect stain for cell viability that can be effective across all species with the same concentration and incubation time6,10. Even the same type of probe with altered fluorescence emissions shows a need to establish the correct concentration and incubation time (Tables 1 &#38; 3). As seen when using t...

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 conditions1-3. 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 population3,4.
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&#160;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 characterised1,5,6.
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 management8,9. 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 implementation6,10,11. 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 &#39;cell viability&#39; 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 eukaryotic11,13 and prokaryotic14,15 organisms. The binding of a nucleic acid probe to nucleic acids can result in up to a &#62;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&#160;- 30 min&#160;and concentration ranges from 0.1 &#181;M - 0.5 &#181;M in Microcystis experiments alone15-19.
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.

<table border="0" cellpadding="0" cellspacing="0" width="926">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:168px;">Cyanobacteria Media</td>
			<td style="width:135px;">Sigma-Aldrich</td>
			<td style="width:123px;">C3061-500ML</td>
			<td style="width:501px;">BG-11 Freshwater concentrated solution (x50 dilution)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Decontamination Fluid</td>
			<td>BD Biosciences</td>
			<td>653155</td>
			<td>Run for 2 mins when outputs are more than 12 events per second on fast or a flow rate of 66 &#181;L/min.&#160; Followed by 2mins of sheath H2O.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Flow Cytometer</td>
			<td>BD Biosciences</td>
			<td>N/A (by request)</td>
			<td>BD Accuri C6</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SYTOX Green</td>
			<td>Life Technologies</td>
			<td>S7020</td>
			<td>Nucleic acid stain &#8211; 5mM solution in DMSO</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SYTOX Orange</td>
			<td>Life Technologies</td>
			<td>S11368</td>
			<td>Nucleic acid stain &#8211; 5mM solution in DMSO</td>
		</tr>
	</tbody>
</table>

molecular probe optimization to determine cell mortality in a photosynthetic organism (microcystis aeruginosa) using flow cytometry

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 &#181;M after 30 min of incubation and the orange nucleic acid probe at 1 &#181;M after 10 min. In both probes concentrations less than the stated optimal led to an under reporting of cells with membrane damage. Conversely, 5 &#181;M concentrations and higher in both probes exhibited a type of non-specific staining, whereby &#39;live&#39; cells produced a target fluorescence, leading to an over representation of &#39;non-viable&#39; 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.

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...

Watch this Scientific Journal Video about Molecular Probe Optimization to Determine Cell Mortality in a Photosynthetic Organism Microcystis aeruginosa Using Flow Cytometry at JoVE.com

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

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.

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

Microbial subpopulations in field and laboratory studies have been shown to display high heterogeneity in morphological and physiological parameters. ...

The overall goal of this procedure is to demonstrate how to create a protocol that can analyze the cyanobacterial physiological state effectively, using flow cytometry and molecular probes. This protocol can help answer key questions about the cell physiology of microbial communities. The main advantage with this procedure is that an optimized fluorescent probe protocol can distinguish between the physiological states of cyanobacteria at the individual cell level in real-time.Demonstrating this procedure will be David Hartnell, a PhD student working the cytometry lab at Bournemouth University. Before beginning the experiment, place an empty hemolysis tube onto the sample injection probe. Click unclog.And then back flush to start the flow cytometry cleaning process. At the end of the back flush, load a new hemolysis tube containing two milliliters of ultra pure filtered water onto the sample injection probe, or SIP, and set the time limit to 10 to 15 minutes, and the fluidic speed to fast. Next, select a new data cell, and set the relevant fluorescence and light scatter thresholds to reduce the background noise.Then click run. If the total events per second are not less than the manufacturer's recommendation, run two milliliters of decontamination solution for two minutes on fast. And repeat the back flush and ultra pure water flushing steps.To prepare a primary M.aeruginosa monoculture, autoclave 98 milliliters of ultra pure filtered water, mixed with two milliliters of algal medium, in a 250-milliliter beaker for 20 minutes at 120 degrees Celsius. When a culture is in a high steady state density, disaggregate two milliliters of cells by vortexing. And then transfer the cells under the sample injection probe.Confirm that the cells are evenly dispersed by light microscopy. Then select a histogram plot on the flow cytometer software to record the forward light scatter data. And click log to view the data in a log scale on the x-axis.In a separate output, set another log axis histogram to record the natural fluorescence of the M.aeruginosa cells. Next, select a light source that can excite phycocyanin, and a detector that can filter the emissions from the resulting fluorescence. For recording at the highest resolution, select the settings closest to the core size of the target organism.And set a relatively slow flow rate. Before acquiring the data, set a threshold to gate out any light scatter and fluorescence signals caused by electronic background noise or cell sample debris. Then select a new data cell.Create a density plot with forward and side scatter parameters on a log scale, and click run. Now apply the forward light scatter and natural fluorescence gate to the forward by side scatter data to exclude any low-level scatter signals, and to include only the higher relative fluorescence phycocyanin signals. Then collect events until the sample is finished, and use the data to determine the initial cell count.To optimize the molecular probe cell uptake, expose half of the previously prepared monoculture to the appropriate conditions for generating a dead control. Check the variations in the sample micro environment to confirm the death of the culture. And then disaggregate the colony formation as just demonstrated.Next, select a 488-nanometer laser alongside a detector that can record fluorescence from the green and orange nucleic acid probes. And the 640-nanometer laser to record the phycocyanin signals through their respective detectors. In a new data sheet, set up a density plot with forward and side scatter parameters.Then create one histogram using the respective molecular probe optical detector channel. One histogram to detect the phycocyanin emissions, and one histogram for forward scatter events, all on a log scale. Run the cyanobacterial samples using different concentrations and incubation times.Create a gate in the forward scatter histogram to include events only with the target organism's cell size. And apply it to the corresponding fluorescence probe channel. Next, in the fluorescence probe channel, create another inclusive software gate against the highest peak in the histogram.And subsequently gate the corresponding positive probe fluorescence onto the density plot. Compare the number of fluorescence signals to the number of dead control cells, where the highest percentage of cell nucleic probe uptake that does not produce non-specific staining. For testing the fluorescence interference overlap from intrinsic or non-specific cell staining, select the 50 percent live and 50 percent dead mixed-culture data.And remove the fluorescent gates. Apply gates to include only the forward scatter histogram for the target organism's cell size on the phycocyanin channel histogram. Gating the highest and lowest phycocyanin peaks, and labeling them live'and dead, respectively.Then separately apply the gates to the live and dead phycocyanin signals. And record both mean wavelengths. To determine the protocol sensitivity, ratio the mean wavelengths of the positive dead molecular probe fluorescence, and the intrinsic non-specific live signal.Finally, select the optimized protocol where the highest amount of dead cells has been stained without the occurrence of non-specific staining. In these graphs, the representative forward and side light scatter outputs, for cellular size and internal complexity of an M.aeruginosa batch culture in the exponential phase are shown. Gating can be performed by refining the data between certain points of the forward light scatter output.Phycocyanin produces a strong signal when interrogated by a red light source, which can be used to further gate the populations of interest. From the forward light scatter and fluorescent signals, data can then be gated from the original output, to specific data on the M.aeruginosa sample for final cell counts. When live higher-pigmented, and dead lower-pigmented controls are mixed, the decreasing shift in auto fluorescence becomes clear.In membrane-compromised cells, the nucleic acid probes produce an additional signal that can be observed by flow cytometry and further confirmed by epifluorescence microscopy. Fluorescence discrimination between live and dead cells increases with time between the 0.05 and 0.5 micromolar concentrations, but decreases between the one and 100-micromolar concentrations for both probes. Indeed, the optimal concentration for the green nucleic acid probe appears to be 0.5 micromolar with an incubation time of 30 minutes.For the orange nucleic acid probe, the optimal concentration is one micromolar for a 10-minute incubation. Once mastered, for each molecular probe, optimization can be completed in a day, if it is performed properly. While attempting this procedure, it is important to remember to keep the probes in a stable environment, under the appropriate temperature, pH, and light conditions.After its development, this technique paved the way for researchers in the field of microbiology to explore community heterogeneity in phytoplankton. Having watched the video, you should now have a good understanding of how to develop an optimal protocol for assessing cellular physiology using flow cytometry and molecular probes. Don't forget that working with molecular probes and toxic organisms can be extremely hazardous, and that precautions such as wearing the appropriate P.P.E, and having the full understanding of COSHH materials, should always be taken while performing this procedure.

Research

JoVE Journal

Medicine

Preparation of Myeloid Derived Suppressor Cells (MDSC) from Naive and Pancreatic Tumor-bearing Mice using Flow Cytometry and Automated Magnetic Activated Cell Sorting (AutoMACS)

Preparation of Myeloid Derived Suppressor Cells MDSC from Naive and Pancreatic Tumor-bearing Mice using Flow Cytometry and Automated Magnetic Activated Cell Sorting AutoMACS

MDSC are a heterogeneous population of immature macrophages, dendritic cells and granulocytes that accumulate in lymphoid organs in pathological ...

Using Quantitative Real-time PCR to Determine Donor Cell Engraftment in a Competitive Murine Bone Marrow Transplantation Model

Murine bone marrow transplantation models provide an important tool in measuring hematopoietic stem cell (HSC) functions and determining genes/molecules ...

High-throughput Flow Cytometry Cell-based Assay to Detect Antibodies to N-Methyl-D-aspartate Receptor or Dopamine-2 Receptor in Human Serum

Over the recent years, antibodies against surface and conformational proteins involved in neurotransmission have been detected in autoimmune CNS diseases ...

Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications

The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the ...

A Modified In vitro Invasion Assay to Determine the Potential Role of Hormones, Cytokines and/or Growth Factors in Mediating Cancer Cell Invasion

A Modified In vitro Invasion Assay to Determine the Potential Role of Hormones, Cytokines and/or Growth Factors in Mediating Cancer Cell Invasion

Blood serum serves as a chemoattractant towards which cancer cells migrate and invade, facilitating their intravasation into microvessels. However, the ...

Focus Formation: A Cell-based Assay to Determine the Oncogenic Potential of a Gene

Malignant transformation of cells is typically associated with increased proliferation, loss of contact inhibition, acquisition of anchorage-independent ...

Performing Subretinal Injections in Rodents to Deliver Retinal Pigment Epithelium Cells in Suspension

The conversion of light into electrical impulses occurs in the outer retina and is accomplished largely by rod and cone photoreceptors and retinal pigment ...

Imaging- and Flow Cytometry-based Analysis of Cell Position and the Cell Cycle in 3D Melanoma Spheroids

Three-dimensional (3D) tumor spheroids are utilized in cancer research as a more accurate model of the in vivo tumor microenvironment, compared to ...

Electrophysiological Measurement of Noxious-evoked Brain Activity in Neonates Using a Flat-tip Probe Coupled to Electroencephalography

Pain is an unpleasant sensory and emotional experience. In non-verbal patients, it is very difficult to measure pain, even with pain assessment tools. ...