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. 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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. 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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.

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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)

MDSC are a heterogeneous population of immature macrophages, dendritic cells and granulocytes that accumulate in lymphoid organs in pathological conditions including parasitic infection, inflammation, traumatic stress, graft-versus-host disease, diabetes and cancer1-7. In mice, MDSC express Mac-1 (CD11b) and Gr-1 (Ly6G and Ly6C) surface antigens7. It is important to note that MDSC are well studied in various tumor-bearing hosts where they are significantly expanded and suppress anti-tumor immune responses compared to na&iuml;ve counterparts7-10. However, depending on the pathological condition, there are different subpopulations of MDSC with distinct mechanisms and targets of suppression11,12. Therefore, effective methods to isolate viable MDSC populations are important in elucidating their different molecular mechanisms of suppression in vitro and in vivo.
Recently, the Ghansah group has reported the expansion of MDSC in a murine pancreatic cancer model. Our tumor-bearing MDSC display a loss of homeostasis and increased suppressive function compared to na&iuml;ve MDSC 13. MDSC percentages are significantly less in lymphoid compartments of na&iuml;ve vs. tumor-bearing mice. This is a major caveat, which often hinders accurate comparative analyses of these MDSC. Therefore, enriching Gr-1+ leukocytes from na&iuml;ve mice prior to Fluorescence Activated Cell Sorting (FACS) enhances purity, viability and significantly reduces sort time. However, enrichment of Gr-1+ leukocytes from tumor-bearing mice is optional as these are in abundance for quick FACS sorting. Therefore, in this protocol, we describe a highly efficient method of immunophenotyping MDSC and enriching Gr-1+ leukocytes from spleens of na&iuml;ve mice for sorting MDSC in a timely manner. Immunocompetent C57BL/6 mice are inoculated with murine Panc02 cells subcutaneously whereas na&iuml;ve mice receive 1XPBS. Approximately 30 days post inoculation; spleens are harvested and processed into single-cell suspensions using a cell dissociation sieve. Splenocytes are then Red Blood Cell (RBC) lysed and an aliquot of these leukocytes are stained using fluorochrome-conjugated antibodies against Mac-1 and Gr-1 to immunophenotype MDSC percentages using Flow Cytometry. In a parallel experiment, whole leukocytes from na&iuml;ve mice are stained with fluorescent-conjugated Gr-1 antibodies, incubated with PE-MicroBeads and positively selected using an automated Magnetic Activated Cell Sorting (autoMACS) Pro Separator. Next, an aliquot of Gr-1+ leukocytes are stained with Mac-1 antibodies to identify the increase in MDSC percentages using Flow Cytometry. Now, these Gr1+ enriched leukocytes are ready for FACS sorting of MDSC to be used in comparative analyses (na&iuml;ve vs. tumor- bearing) in in vivo and in vitro assays.

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

This is a rapid and comprehensive method of immunophenotyping Myeloid Derived Suppressor Cells (MDSC) and enriching Gr-1+ leukocytes from mouse spleens. This method uses flow cytometry and AutoMACS Cell Sorting to enrich for viable Gr-1+ leukocytes prior to FACS sorting of MDSC for use in vivo and in vitro assays.

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

Molecular Imaging to Target Transplanted Muscle Progenitor Cells

Duchenne muscular dystrophy (DMD) is a severe genetic neuromuscular disorder that affects 1 in 3,500 boys, and is characterized by progressive muscle degeneration1, 2. In patients, the ability of resident muscle satellite cells (SCs) to regenerate damaged myofibers becomes increasingly inefficient4. Therefore, transplantation of muscle progenitor cells (MPCs)/myoblasts from healthy subjects is a promising therapeutic approach to DMD. A major limitation to the use of stem cell therapy, however, is a lack of reliable imaging technologies for long-term monitoring of implanted cells, and for evaluating its effectiveness. Here, we describe a non-invasive, real-time approach to evaluate the success of myoblast transplantation. This method takes advantage of a unified fusion reporter gene composed of genes (firefly luciferase [fluc], monomeric red fluorescent protein [mrfp] and sr39 thymidine kinase [sr39tk]) whose expression can be imaged with different imaging modalities9, 10. A variety of imaging modalities, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and high frequency 3D-ultrasound are now available, each with unique advantages and limitations11. Bioluminescence imaging (BLI) studies, for example, have the advantage of being relatively low cost and high-throughput. It is for this reason that, in this study, we make use of the firefly luciferase (fluc) reporter gene sequence contained within the fusion gene and bioluminescence imaging (BLI) for the short-term localization of viable C2C12 myoblasts following implantation into a mouse model of DMD (muscular dystrophy on the X chromosome [mdx] mouse)12-14. Importantly, BLI provides us with a means to examine the kinetics of labeled MPCs post-implantation, and will be useful to track cells repeatedly over time and following migration. Our reporter gene approach further allows us to merge multiple imaging modalities in a single living subject; given the tomographic nature, fine spatial resolution and ability to scale up to larger animals and humans10,11, PET will form the basis of future work that we suggest may facilitate rapid translation of methods developed in cells to preclinical models and to clinical applications.

A non-invasive means to evaluate the success of myoblast transplantation is described. The method takes advantage of a unified fusion reporter gene composed of genes whose expression can be imaged with different imaging modalities. Here, we make use of a fluc reporter gene sequence to target cells via bioluminescence imaging.

Duchenne muscular dystrophy (DMD) is a severe genetic neuromuscular disorder that affects 1 in 3,500 boys, and is characterized by progressive muscle ...

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 that regulate HSCs. In these transplant model systems, the function of HSCs is determined by the ability of these cells to engraft and reconstitute lethally irradiated recipient mice. Commonly, the donor cell contribution/engraftment is measured by antibodies to donor- specific cell surface proteins using flow cytometry. However, this method heavily depends on the specificity and the ability of the cell surface marker to differentiate donor-derived cells from recipient-originated cells, which may not be available for all mouse strains. Considering the various backgrounds of genetically modified mouse strains in the market, this cell surface/ flow cytometry-based method has significant limitations especially in mouse strains that lack well-defined surface markers to separate donor cells from congenic recipient cells. Here, we reported a PCR-based technique to determine donor cell engraftment/contribution in transplant recipient mice. We transplanted male donor bone marrow HSCs to lethally irradiated congenic female mice. Peripheral blood samples were collected at different time points post transplantation. Bone marrow samples were obtained at the end of the experiments. Genomic DNA was isolated and the Y chromosome specific gene, Zfy1, was amplified using quantitative Real time PCR. The engraftment of male donor-derived cells in the female recipient mice was calculated against standard curve with known percentage of male vs. female DNAs. Bcl2 was used as a reference gene to normalize the total DNA amount. Our data suggested that this approach reliably determines donor cell engraftment and provides a useful, yet simple method in measuring hematopoietic cell reconstitution in murine bone marrow transplantation models. Our method can be routinely performed in most laboratories because no costly equipment such as flow cytometry is required.

Determining donor cell engraftment presents a challenge in mouse bone marrow transplant models that lack well-defined phenotypical markers. We described a methodology to quantify male donor cell engraftment in female transplant recipient mice. This method can be used in all mouse strains for the study of HSC functions.

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 in children and adults. These antibodies have been used to guide diagnosis and treatment. Cell-based assays have improved the detection of antibodies in patient serum. They are based on the surface expression of brain antigens on eukaryotic cells, which are then incubated with diluted patient sera followed by fluorochrome-conjugated secondary antibodies. After washing, secondary antibody binding is then analyzed by flow cytometry. Our group has developed a high-throughput flow cytometry live cell-based assay to reliably detect antibodies against specific neurotransmitter receptors. This flow cytometry method is straight forward, quantitative, efficient, and the use of a high-throughput sampler system allows for large patient cohorts to be easily assayed in a short space of time. Additionally, this cell-based assay can be easily adapted to detect antibodies to many different antigenic targets, both from the central nervous system and periphery. Discovering additional novel antibody biomarkers will enable prompt and accurate diagnosis and improve treatment of immune-mediated disorders.

Over the recent years, live cell-based assays have been used successfully to detect antibodies against surface and conformational antigens. Here, we describe a method using high-throughput flow cytometry enabling the analysis of large cohorts of patients. Detection of novel antibodies will improve diagnosis and treatment of immune-mediated disorders.

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

The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the presence of circulating tumor cells (CTCs). These rare cells have been demonstrated to be of clinical significance in metastatic breast, prostate, and colorectal cancers. The current gold standard in clinical CTC detection and enumeration is the FDA-cleared CellSearch system (CSS). This manuscript outlines the standard protocol utilized by this platform as well as two&#160;additional adapted protocols that describe the detailed process of user-defined marker optimization for protein characterization of patient CTCs and a comparable protocol for CTC capture in very low volumes of blood, using standard CSS reagents, for studying in vivo preclinical mouse models of metastasis. In addition, differences in CTC quality between healthy donor blood spiked with cells from tissue culture versus patient blood samples are highlighted. Finally, several commonly discrepant items that can lead to CTC misclassification errors are outlined. Taken together, these protocols will provide a useful resource for users of this platform interested in preclinical and clinical research pertaining to metastasis and CTCs.

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

Circulating tumor cells (CTCs) are prognostic in several metastatic cancers. This manuscript describes the gold standard CellSearch system (CSS) CTC enumeration platform and highlights common misclassification errors. In addition, two&#160;adapted protocols are described for user-defined marker characterization of CTCs and CTC enumeration in preclinical mouse models of metastasis using this technology.

The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with 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 growth potential, and the ability to form tumors in experimental animals1. In NIH 3T3 cells, the Ras signal transduction pathway is known to trigger many of these events, what is known as Ras transformation. The introduction of an overexpressed gene in NIH 3T3 cells may promote morphological transformation and loss of contact inhibition, which can help determine the oncogenic potential of that gene of interest. An assay that provides a straightforward method to assess one aspect of the transforming potential of an oncogene is the Focus Formation Assay (FFA)2. When NIH 3T3 cells divide normally in culture, they do so until they reach a confluent monolayer. However, in the presence of an overexpressed oncogene, these cells can begin to grow in dense, multilayered foci1 that can be visualized and quantified by crystal violet or Hema 3 staining. In this article we describe the FFA protocol with retroviral transduction of the gene of interest into NIH 3T3 cells, and how to quantify the number of foci through staining. Retroviral transduction offers a more efficient method of gene delivery than transfection, and the use of an ecotropic murine retrovirus provides a biosafety control when working with potential human oncogenes.

The Focus Formation Assay provides a straightforward method to assess the transforming potential of a candidate oncogene.

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 epithelium (RPE) cells. RPE provide critical support for photoreceptors and death or dysfunction of RPE cells is characteristic of age-related macular degeneration (AMD), the leading cause of permanent vision loss in people age 55 and older. While no cure for AMD has been identified, implantation of healthy RPE in diseased eyes may prove to be an effective treatment, and large numbers of RPE cells can be readily generated from pluripotent stem cells. Several interesting questions regarding the safety and efficacy of RPE cell delivery can still be examined in animal models, and well-accepted protocols used to inject RPE have been developed. The technique described here has been used by multiple groups in various studies and involves first creating a hole in the eye with a sharp needle. Then a syringe with a blunt needle loaded with cells is inserted through the hole and passed through the vitreous until it gently touches the RPE. Using this injection method, which is relatively simple and requires minimal equipment, we achieve consistent and efficient integration of stem cell-derived RPE cells in between the host RPE that prevents significant amount of photoreceptor degeneration in animal models. While not part of the actual protocol, we also describe how to determine the extent of the trauma induced by the injection, and how to verify that the cells were injected into the subretinal space using in vivo imaging modalities. Finally, the use of this protocol is not limited to RPE cells; it may be used to inject any compound or cell into the subretinal space.

Here we present a community accepted protocol in multimedia format for subretinally injecting a bolus of RPE cells in rats and mice. This approach can be used for determining rescue potentials, safety profiles, and survival capacities of grafted RPE cells upon implantation in animal models of retinal degeneration.

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 traditional two-dimensional (2D) cell culture. The spheroid model is able to mimic the effects of cell-cell interaction, hypoxia and nutrient deprivation, and drug penetration. One characteristic of this model is the development of a necrotic core, surrounded by a ring of G1 arrested cells, with proliferating cells on the outer layers of the spheroid. Of interest in the cancer field is how different regions of the spheroid respond to drug therapies as well as genetic or environmental manipulation. We describe here the use of the fluorescence ubiquitination cell cycle indicator (FUCCI) system along with cytometry and image analysis using commercial software to characterize the cell cycle status of cells with respect to their position inside melanoma spheroids. These methods may be used to track changes in cell cycle status, gene/protein expression or cell viability in different sub-regions of tumor spheroids over time and under different conditions.

We describe two complementary methods using the fluorescence ubiquitination cell cycle indicator (FUCCI) and image analysis or flow cytometry to identify and isolate cells in the inner G1 arrested and outer proliferating regions of 3D 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. Those tools are subjective or determine secondary physiological indicators which also have certain limitations particularly when exploring the effectiveness of analgesia. As cortical processing is essential for pain perception, brain activity measures may provide a useful approach to assess pain in infants. Here we present a method to assess nociception with electrophysiological brain activity recordings optimized for the use in newborn infants. To produce highly standardized and reproducible noxious stimuli we applied mechanical stimulation with a flat-tip probe, e.g., PinPrick, which is not skin-breaking and does not cause behavioral distress. The noxious-evoked potential allows the objective measurement of nociception in non-verbal patients. This method can be used in newborn infants as early as 34 weeks of gestational age. Moreover, it could be applied in different situations such as measuring the efficacy of analgesic or anesthetic drugs.

Measuring pain in non-verbal patients is a challenge. In this study we combine EEG recording with stimulation using a flat-tip probe to detect noxious-evoked brain activity in an objective manner.

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

Characterization of Immune Cells in Human Adipose Tissue by Using Flow Cytometry

Infiltration of immune cells in the subcutaneous and visceral adipose tissue (AT) deposits leads to a low-grade inflammation contributing to the development of obesity-associated complications such as type 2 diabetes. To quantitatively and qualitatively investigate the immune cell subsets in human AT deposits, we have developed a flow cytometry approach. The stromal vascular fraction (SVF), containing the immune cells, is isolated from subcutaneous and visceral AT biopsies by collagenase digestion. Adipocytes are removed after centrifugation. The SVF cells are stained for multiple membrane-bound markers selected to differentiate between immune cell subsets and analyzed using flow cytometry. As a result of this approach, pro- and anti-inflammatory macrophage subsets, dendritic cells (DCs), B-cells, CD4+ and CD8+ T-cells, and NK cells can be detected and quantified. This method gives detailed information about immune cells in AT and the amount of each specific subset. Since there are numerous fluorescent antibodies available, our flow cytometry approach can be adjusted to measure various other cellular and intracellular markers of interest.

This article describes a method to analyze immune cell content of adipose tissue by isolation of immune cells from adipose tissue and subsequent analysis using flow cytometry.