Name: using real-time cell metabolic flux analyzer to monitor osteoblast bioenergetics
Uploaded: 2022-03-01T12:45:00
Description: Watch this Scientific Journal Video about Using Real-Time Cell Metabolic Flux Analyzer to Monitor Osteoblast Bioenergetics at JoVE.com

This work was supported by the National Institute of Health (NIH) National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) Grant AR072123 and National Institute on Aging (NIA) Grant AG069795 (to ERR).

All the procedures were based on the guidelines and approval of the Institutional Animal Care and Use Committee at Vanderbilt University Medical center.
1. Preparation of reagents and assay setup
<ol>
	<li>Isolation and culturing of bone marrow stromal cells (also see the previous article30).
	<ol>
		<li>Prepare complete alpha minimum essential media (&#945;MEM) cell culture media by supplementing minimum essential media with alpha modification with 1...

<ol>
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B., Nichols, N., Nichols, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolic+studies+of+bone+in+vitro:+II.+The+metabolic+patterns+of+accretion+and+resorption.">Metabolic studies of bone in vitro: II. The metabolic patterns of accretion and resorption.</a> Journal of Biological Chemistry. 235, 1211-1214 (1960).</li><li>Adamek, G., Felix, R., Guenther, H. L., Fleisch, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fatty+acid+oxidation+in+bone+tissue+and+bone+cells+in+culture.+Characterization+and+hormonal+influences.">Fatty acid oxidation in bone tissue and bone cells in culture. Characterization and hormonal influences.</a> The Biochemical Journal. 248 (1), 129-137 (1987).</li><li>Frey, J. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wnt-Lrp5+signaling+regulates+fatty+acid+metabolism+in+the+osteoblast.">Wnt-Lrp5 signaling regulates fatty acid metabolism in the osteoblast.</a> Molecular and Cellular Biology. 35 (11), 1979-1991 (2015).</li><li>Romero, N., Rogers, G., Neilson, A., Dranka, B. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Quantifying cellular ATP production rate using agilent seahorse XF technology. , (2018).</li><li>vander Windt, G., Chang, C., Pearce, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+bioenergetics+in+T+cells+using+a+Seahorse+Extracellular+Flux+Analyzer.">Measuring bioenergetics in T cells using a Seahorse Extracellular Flux Analyzer.</a> Current Protocols in Immunology. 113, 1 (2016).</li><li>Traba, J., Miozzo, P., Akkaya, B., Pierce, S. K., Akkaya, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+optimized+protocol+to+analyze+glycolysis+and+mitochondrial+respiration+in+lymphocytes.">An optimized protocol to analyze glycolysis and mitochondrial respiration in lymphocytes.</a> Journal of Visualized Experiments:JoVE. (117), e54918 (2016).</li><li>Noel, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preparation+and+metabolic+assay+of+3-dimensional+spheroid+co-cultures+of+pancreatic+cancer+cells+and+fibroblasts.">Preparation and metabolic assay of 3-dimensional spheroid co-cultures of pancreatic cancer cells and fibroblasts.</a> Journal of Visualized Experiments:JoVE. (126), e56081 (2017).</li><li>Nicholls, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bioenergetic+profile+experiment+using+C2C12+myoblast+cells.">Bioenergetic profile experiment using C2C12 myoblast cells.</a> Journal of Visualized Experiments: JoVE. (46), e2511 (2010).</li><li>Sakamuri, S. S. V. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+respiratory+function+in+isolated+cardiac+mitochondria+using+Seahorse+XFe24+Analyzer:+applications+for+aging+research.">Measurement of respiratory function in isolated cardiac mitochondria using Seahorse XFe24 Analyzer: applications for aging research.</a> GeroScience. 40 (3), 347-356 (2018).</li><li>. What are the advantages of using Seahorse XF technology Available from: <a target="_blank" href="https://wwwagilent.com/en/support/cell-analysis/advantages-of-using-xf-tech">https://wwwagilent.com/en/support/cell-analysis/advantages-of-using-xf-tech</a> (2018)</li><li>Horan, M. P., Pichaud, N., Ballard, J. W. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review:+Quantifying+mitochondrial+dysfunction+in+complex+diseases+of+aging.">Review: Quantifying mitochondrial dysfunction in complex diseases of aging.</a> Journals of Gerontology - Series A Biological Sciences and Medical Sciences. 67 (10), 1022-1035 (2012).</li><li>. XF cell energy phenotype test Available from: <a target="_blank" href="https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740884">https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740884</a> (2021)</li><li>Leung, D. T. H., Chu, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+oxidative+stress:+Mitochondrial+function+using+the+seahorse+system.">Measurement of oxidative stress: Mitochondrial function using the seahorse system.</a> Methods in Molecular Biology. 1710, 285-293 (2018).</li><li>. XF ATP rate assay Available from: <a target="_blank" href="https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740889">https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740889</a> (2021)</li><li>. XF cell mito stress test Available from: <a target="_blank" href="https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740885">https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740885</a> (2021)</li><li>. XF cell mito fuel flex test Available from: <a target="_blank" href="https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740888">https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-assay-kits-reagents-cell-assay-media/seahorse-xf-cell-energy-phenotype-test-kit-740888</a> (2021)</li><li>Maridas, D. E., Rendina-Ruedy, E., Le, P. T., Rosen, C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolation,+culture,+and+differentiation+of+bone+marrow+stromal+cells+and+osteoclast+progenitors+from+mice.">Isolation, culture, and differentiation of bone marrow stromal cells and osteoclast progenitors from mice.</a> Journal of Visualized Experiments: JoVE. 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N., Jastroch, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+and+interpretation+of+microplate-based+oxygen+consumption+and+pH+data.">Analysis and interpretation of microplate-based oxygen consumption and pH data.</a> Methods in Enzymology. 547, 309-354 (2014).</li><li>Kam, Y., Jastromb, N., Clayton, J., Held, P., Dranka, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Normalization of agilent seahorse XF data by in-situ cell counting using a BioTek cytation 5 application note. , (2017).</li></ol>

The real-time cell metabolic flux analyzer can be used to explore cellular energetics under different conditions. The protocol illustrates the efficient isolation of BMSCs, culturing cells in appropriate cell culture plates, and their differentiation to mature osteoblasts, which can be used for various assays using the extracellular flux analyzer. Further, the critical steps of real-time cell metabolic flux assay, including hydration of sensor cartridges, loading of the injection ports, performing the assay, normalizatio...

The formation of bone by the osteoblast is accompanied by coordinated destruction or resorption of bones by osteoclasts. The balance between osteoblastic bone formation and osteoclast resorption is a coupled process describing bone turnover or remodeling, which is essential for skeletal homeostasis. Osteoblast dysfunction leads to impaired bone formation and results in various diseases, including osteoporosis1,2,3. Ex vivo/in vitro differentiation of bone marrow stromal stem cells (BMSCs) to osteoblast precursors and mature osteoblasts results in the formation and deposition of the mineralized bone matrix in the culture vessel over time4,5,6. This bone formation by the osteoblast requires a significant amount of cellular energy. Specifically, collagen synthesis and secretion have been shown to rely heavily on cellular ATP: ADP ratios, and presumably, mineralized vesicle trafficking and secretion require additional ATP7,8,9,10,11. Many researchers have demonstrated that the process of osteoblastogenesis and osteoblast function requires an adequate supply of energy to meet the metabolic demand of bone formation12,13,14,15,16. Therefore, the goal of this method is to characterize the bioenergetic status of primary, murine stromal cells throughout osteoblast differentiation using the real-time cell metabolic flux analyzer. These techniques aid in developing a better understanding of skeletal homeostasis, which may ultimately lead to the development of novel therapeutic options capable of improving skeletal disorders.
The real-time cell metabolic flux analyzer can be used to measure the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) of live osteoblasts, which corresponds to mitochondrial and glycolytic ATP production, respectively. Fundamental to this methodology is the fact that one H+ ion per lactate is released during glycolysis in the conversion of glucose to lactate, which alters media pH reflected in the ECAR values. Conversely, during the TCA (tricarboxylic acid) cycle, oxidative phosphorylation via the mitochondria produces CO2 by utilizing or consuming oxygen, and therefore monitoring OCR is reflective of this metabolic process. The analyzer measures both OCR and ECAR in the extracellular microenvironment simultaneously and in real-time, which allows for tremendous potential when studying cellular bioenergetics6,17. Additionally, performing these assays is relatively straightforward and easily customizable depending on the experimental goal. Similar techniques have been employed to further understand T-cell metabolic regulation of the immune system18,19, cancer initiation, and progression20, along with multiple other cell types contributing to metabolic syndromes21,22.
The advantages of Real-time metabolic flux analyzer over alternative techniques include (1) the capability to measure cellular bioenergetics of live cells in real-time, (2) ability to perform assay with a relatively small number of cells (requires as low as 5,000 cells), (3) injection ports to parallelly manipulate multiple treatments in a high-throughput 96-well system, (4) use of radioactive label-free automated cell imager for normalization18,23,24. The following methods aim to provide a generalized but detailed description of monitoring cellular bioenergetics in murine BMSCs throughout osteoblast differentiation using the analyzer. It will include routinely performed assays; however, as with many techniques and methods, it is highly encouraged that individual labs determine specific details for their experiments.
Selection of assay and different types of assays available: A wide variety of assay kits and reagents are available to study the bioenergetics of cells while ensuring the reliability and consistency of the experimental results. Additionally, the desktop software also offers assay templates that can be easily customized. The assay can be defined based on the user&#39;s needs to measure different metabolic parameters. These assays can be modified in various ways based on the experimental goal and/or scientific question. For example, with four injection ports, multiple compounds can be injected into the assay media to analyze the cellular response specific to each metabolic pathway.
Cell energy phenotype test: This assay measures the live cells&#39; metabolic phenotype and metabolic potential. This assay is also recommended as the first step to get a generalized idea of pathway-specific metabolism. A mixture of oligomycin A-an inhibitor of ATP synthase and Carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (FCCP)-a mitochondrial uncoupling agent is injected to understand the cell energy potential. The injection of oligomycin A inhibits the synthesis of ATP, resulting in an increase in the rate of glycolysis (ECAR) to enable the cells to meet their energy demands; on the other hand, the injection of FCCP results in higher OCR due to depolarization of the mitochondrial membrane. Essentially, this assay depicts basal metabolic respiration, and following the dual injections, pushes, or stresses, the metabolic response. Based on these parameters, the software then plots OCR and ECAR of the cells by classifying the cells as aerobic, quiescent, glycolytic, or energetic state over time25,26.
ATP real-time production rate assay: This measures the cellular ATP production simultaneously from glycolysis and mitochondrial respiration. This assay quantitatively measures the metabolic shifts from the two energy pathways and provides data on the mitochondrial and glycolytic ATP production rates over time. The assay obtains basal OCR and ECAR data followed by calculating mitochondrial ATP production rate through injection of oligomycin A and glycolytic ATP production rate through injection of rotenone + antimycin A mixture (total inhibition of mitochondrial function), resulting in mitochondrial acidification17,27.
Cell mitochondria stress test (or cell mito stress test): This measures the mitochondrial function through ATP-linked respiration, quantifies cellular bioenergetics, identifies mitochondrial dysfunction, and measures cells&#39; response to stress. Various parameters, including basal and spare respiratory capacity, ATP-linked respiration, maximal respiration, and non-mitochondrial oxygen consumption, can be obtained in one assay. This assay involves sequential injections of oligomycin A, FCCP (mitochondrial uncoupling agent), a mixture of rotenone/antimycin A inhibitors to efficiently analyze the effect of these on the mitochondrial function28.
Flexibility mito fuel flex test: This measures the mitochondrial respiration rate by the oxidation of the three primary mitochondrial fuels by the presence and absence of their inhibitors. The sequential inhibition of glucose, glutamine, and fatty acids aids in measuring the dependency, capacity, and flexibility of cells and the dependency of the cells in various cellular pathways to meet the energy demand. When the mitochondria cannot meet the demands of the blocked pathway of interest by oxidizing other fuels, the cells enter a dependency state. The capacity of the cells is calculated by inhibition of the other two alternative pathways followed by the inhibition of the pathway of interest. The flexibility of cells helps in understanding the ability of mitochondria to compensate and meet the fuel needs of the inhibited pathway. It is calculated by subtracting the dependency of cells from the capacity of cells. Three different inhibitors are used independently or as a mixture of two to effectively calculate the assay parameters. 2-cyano-3-(1-phenyl-1H-indol-3-yl)-2-propenoic acid (UK5099) inhibits the oxidation of glucose by blocking the pyruvate carrier in glycolysis. Bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl) (BPTES) ethyl sulfide inhibits the glutamine oxidation pathway, and etomoxir inhibits the oxidation of long-chain fatty acids29.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63142/63142fig01.jpg" /> 
Figure 1: Schematic representation of the methodology for culturing and preparing osteoblasts for analysis. Murine BMSCs are isolated from long bones, cultured, and seeded in 96-well plates at 25,000 cells/well density. Culturing these cells in Osteoblast specific media is started when they reach&#160;80%-100% confluency to start their differentiation.&#160;The assays are performed at different stages of differentiation. The cartridge plates are hydrated one day prior to the assay. On the day of assay, different inhibitors are injected in the ports of the sensor cartridges based on the assay requirements, and a calibration buffer is added to the 96-well calibration plate. After calibration, the real-time cell metabolic flux assay is performed, followed by imaging the cell culture microplate using the microplate imager to normalize real-time cell metabolic flux analyzer data with cell count. <a href="https://www.jove.com/files/ftp_upload/63142/63142fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.25% Trypsin EDTA</td>
			<td>Sigma-Aldrich</td>
			<td>T4049</td>
			<td></td>
		</tr>
		<tr>
			<td>2-cyano-3-(1-phenyl-1H-indol-3-yl)-2-propenoic acid</td>
			<td>Sigma - Aldrich</td>
			<td>PZ0160</td>
			<td>UK5099</td>
		</tr>
		<tr>
			<td>Antimycin A</td>
			<td>Sigma - Aldrich</td>
			<td>A8674</td>
			<td></td>
		</tr>
		<tr>
			<td>Ascorbic acid</td>
			<td>Sigma-Aldrich</td>
			<td>A4544-100G</td>
			<td></td>
		</tr>
		<tr>
			<td>Bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide</td>
			<td>Sigma - Aldrich</td>
			<td>SML0601</td>
			<td>BPTES</td>
		</tr>
		<tr>
			<td>Carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone</td>
			<td>Sigma - Aldrich</td>
			<td>C2920</td>
			<td>FCCP</td>
		</tr>
		<tr>
			<td>Cytation 5 imaging reader</td>
			<td>BioTek</td>
			<td>N/A</td>
			<td>Microplate imager</td>
		</tr>
		<tr>
			<td>Etomoxir sodium salt hydrate</td>
			<td>Sigma - Aldrich</td>
			<td>E1905</td>
			<td></td>
		</tr>
		<tr>
			<td>Hoechst 33342 Solution (20 mM)</td>
			<td>Thermo Scientific</td>
			<td>62249</td>
			<td></td>
		</tr>
		<tr>
			<td>Insulin</td>
			<td>Sigma - Aldrich</td>
			<td>I6634</td>
			<td></td>
		</tr>
		<tr>
			<td>Oleic Acid-Albumin from bovine serum</td>
			<td>Sigma - Aldrich</td>
			<td>O3008</td>
			<td></td>
		</tr>
		<tr>
			<td>Oligomycin A - 5 mg</td>
			<td>Sigma - Aldrich</td>
			<td>75351</td>
			<td></td>
		</tr>
		<tr>
			<td>Rotenone</td>
			<td>Sigma - Aldrich</td>
			<td>R8875-1G</td>
			<td></td>
		</tr>
		<tr>
			<td>Seahorse XF 1.0 M Glucose Solution</td>
			<td>Agilent Technologies</td>
			<td>103577-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Seahorse XF 100mM Pyruvate Solution</td>
			<td>Agilent Technologies</td>
			<td>103578-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Seahorse XF 200mM Glutamine solution</td>
			<td>Agilent Technologies</td>
			<td>103579-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Seahorse XF DMEM media</td>
			<td>Agilent Technologies</td>
			<td>103575-100</td>
			<td>DMEM assay media eith 5mM HEPES, pH 7.4, without phenol red, sodium bicarbonate, glucose, pyruvate, and L-glutamine</td>
		</tr>
		<tr>
			<td>Seahorse XFe96 Analyzer</td>
			<td>Agilent Technologies</td>
			<td>S7800B</td>
			<td>Real- Time Metabolic flux analyzer</td>
		</tr>
		<tr>
			<td>Seahorse XFe96 FluxPak</td>
			<td>Agilent Technologies</td>
			<td>102416-100</td>
			<td>Includes XFe96 Sensor cartridges, Cell culture microplates, and Seahorse XF Calibrant solution</td>
		</tr>
		<tr>
			<td>The Cell imaging 1.1.0.11 software</td>
			<td>Agilent Technologies - BioTek</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Wave software 2.6.1</td>
			<td>Agilent Technologies</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>&#946;-glycerol phosphate</td>
			<td>Sigma-Aldrich</td>
			<td>G9422-50G</td>
			<td></td>
		</tr>
	</tbody>
</table>

using real-time cell metabolic flux analyzer to monitor osteoblast bioenergetics

Bone formation by osteoblasts is an essential process for proper bone acquisition and bone turnover to maintain skeletal homeostasis, and ultimately, prevent fracture. In the interest to both optimize peak bone mass and combat various musculoskeletal diseases (i.e., post-menopausal osteoporosis, anorexia nervosa, type 1 and 2 diabetes mellitus), incredible efforts have been made in the field of bone biology to fully characterize osteoblasts throughout their differentiation process. Given the primary role of mature osteoblasts to secrete matrix proteins and mineralization vesicles, it has been noted that these processes take an incredible amount of cellular energy, or adenosine triphosphate (ATP). The overall cellular energy status is often referred to as cellular bioenergetics, and it includes a series of metabolic reactions that sense substrate availability to derive ATP to meet cellular needs. Therefore, the current method details the process of isolating primary, murine bone marrow stromal cells (BMSCs) and monitoring their bioenergetic status using the Real-time cell metabolic flux analyzer at various stages in osteoblast differentiation. Importantly, these data have demonstrated that the metabolic profile changes dramatically throughout osteoblast differentiation. Thus, using this physiologically relevant cell type is required to fully appreciate how a cell's bioenergetic status can regulate the overall function.

<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/63142/63142fig06.jpg" /> 
Figure 6: Representative graphs for routinely performed assays to understand the cellular bioenergetic profile of control vs. treatment group with their respective standard errors. (A) The cell energy phenotype test. The plot represents the glycolysis (ECAR) vs. mitochondrial respiration (OCR) of the control vs. two trea...

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Using Real-Time Cell Metabolic Flux Analyzer to Monitor Osteoblast Bioenergetics

Real-time cell metabolic flux assay measures the oxygen consumption rate and extracellular acidification rate, which corresponds to mitochondrial and glycolytic adenosine triphosphate production, using pH and oxygen sensors. The manuscript explains a method to understand the energy status of osteoblasts and the characterization and interpretation of the cellular bioenergetic status.

Bone formation by osteoblasts is an essential process for proper bone acquisition and bone turnover to maintain skeletal homeostasis, and ultimately, ...

This method is useful in determining cellular energetics, like ATP production rate, and also to determine cellular preference towards a particular metabolite on a real time basis. To begin, add 200 microliters of XF calibrant and incubate the utility plate for at least one hour before the assay. Prepare 80 milliliters of XF assay media using supplemented XF DMEM.Thaw oligomycin A, rotenone, and antimycin A on ice. Pipette the compounds up and down to solubilize them before use. Add three milliliters of prepared assay medium to each tube, labeled A and B.Add 26.4 microliters of 2.5 millimolar oligomycin A into tube A and 3.1 microliters of 12.67 millimolar rotenone, 4.1 microliters of 9.4 millimolar antimycin A, and 30 microliter Hook's stain into tube B.Load a 10x concentration of these inhibitors in the corresponding injection port.And finally, 20 microliters of these compounds will be loaded into the cells in 200 microliters of assay media. Remove the cell culture microplate from the 37 degrees Celsius incubator and observe the cells under the microscope. Remove the assay medium from the water bath.Gently wash the cells with 200 microliters of pre-warmed assay medium twice, and add 200 microliters of assay media per well. Check the cells under the microscope to ensure that the cells remain adhered to the wells. Ensure that the cells in D5 and E8 wells are adhered with a consistent monolayer and were not washed away during the washing step.Cell imaging software uses these two wells for setting the auto focus and auto exposure. Open the desktop software in the computer next to the equipment. Check the connection status in the lower left corner of the controller software.Go to Templates and select the XF ATP rate assay template or appropriate assay template. Select Group Definitions on the top of the screen and define the groups. select the plate map layout and assign the wells depending on the groups defined.Verify the instrument protocol. Ensure the compounds added are correctly listed and include the project information for future references. Click on Run Assay.This will prompt the selection of the result file storage location. Select the location to save the result file. Save the file with the assay date and click on Start Run.Place the sensor cartridge and the utility plate on the tray and click on I'm Ready to initiate the calibration. Open the cell imaging software on the computer. Ensure that the microplate imager is turned on and the ports are connected to the computer.Check the status bar in the bottom left of the screen to ensure that the temperature is set to 37 degrees Celsius and that the connection status should be highlighted in green as ready. Scan the plate barcode to initiate the imaging process. Provide a name to the cell plate and hit Save.Brightfield and fluorescent images will be saved here. Click on Perform Brightfield Scan and, in the next screen, Plate and Scan Menu show the options for imaging. Before the assay, select Start Brightfield Scan.Place the cell culture microplate and the plate cover on the tray holder and align well A1 with the A1 mark. Click on Close Tray. Brightfield image acquisition appears in the next screen with a plate map.Click on Scan All Wells and scan for 30 to 35 minutes. On completion of the calibration, the software displays the Load Cell Plate dialogue box. Then, click on Open Tray to replace the utility tray with a cell culture microplate.Note that the cell culture plate is in the microplate imager. After the scan, remove the cell culture microplate and place it in the analyzer to perform the assay. Then, click on Load Cell Plate to initiate the assay.Wait until the assay starts and display the estimated completion time. Upon completion of the assay, the software displays Unload Sensor Cartridge and Cell Plate dialogue box. Click on Eject and remove the cell culture microplate from the analyzer.Carefully remove the sensor cartridge and replace the cell plate lid. The Assay Complete dialogue box appears. Then, click on View Results to open the assay result file or to normalize the data.After the assay completion, scan the plate barcode with the handheld barcode reader. If the plate has already been imaged, it will not require a new name. Select Fluorescence and Cell Count.Place the cell plate on the tray holder and click on Close Tray. In the image acquisition window, select Scan All Wells to begin imaging. Review the fluorescent images and cell counts in the imaging and cell imaging application by randomly clicking on a couple of the wells.Once the fluorescence imaging is complete, export the images for additional references. Once the imaging and cell count is complete, open the results file and click on Normalize. Click on Import and select Apply for the desktop software to normalize the assay with cell count automatically.The oligomycin A and FCCP stressor mix injection increased the control group's baseline activity. Stressors showed a significantly high energy level in the control and treatment one groups. On the other hand, treatment two had a comparatively lower baseline activity, and the cells became more aerobic.The figure indicates both control and experimental cells uses glycolysis and mitochondrial oxidative phosphorylation for ATP generation. The experimental group displays a reduction in ATP generation via glycolysis and an increase in mitochondrial respiration. The basal respiration rate in the treatment group is comparatively less than the control group.The respiration and ATP production rates in both groups are decreased, along with the proton leak followed by an oligomycin A injection. The respiration rates of the cells rise back again to their maximal respiration after the injection of FCCP. The final injection of rotenone and antimycin A decreases the OCR again.After the third injection, the mitochondrial respiration is shut down by the combination of rotenone and antimycin A.Compared to the control group, the basal and maximal respiration of the treatment groups has relatively no change. The figure shows that the control group is highly dependent on the glucose pathway, while glutamine oxidation was efficient in the control group. The fatty acid pathway shows that the treatment has increased the overall capacity of the cells.The availability of multiple injection ports on the acid plate helps us to determine the effect of multiple drugs on cellular energetics at a single time point.

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Research

JoVE Journal

Biology

Combining QD-FRET and Microfluidics to Monitor DNA Nanocomplex Self-Assembly in Real-Time

Advances in genomics continue to fuel the development of therapeutics that can target pathogenesis at the cellular and molecular level. Typically functional inside the cell, nucleic acid-based therapeutics require an efficient intracellular delivery system. One widely adopted approach is to complex DNA with a gene carrier to form nanocomplexes via electrostatic self-assembly, facilitating cellular uptake of DNA while protecting it against degradation. The challenge lies in the rational design of efficient gene carriers, since premature dissociation or overly stable binding would be detrimental to the cellular uptake and therapeutic efficacy. Nanocomplexes synthesized by bulk mixing showed a diverse range of intracellular unpacking and trafficking behavior, which was attributed to the heterogeneity in size and stability of nanocomplexes. Such heterogeneity hinders the accurate assessment of the self-assembly kinetics and adds to the difficulty in correlating their physical properties to transfection efficiencies or bioactivities. We present a novel convergence of nanophotonics (i.e. QD-FRET) and microfluidics to characterize the real-time kinetics of the nanocomplex self-assembly under laminar flow. QD-FRET provides a highly sensitive indication of the onset of molecular interactions and quantitative measure throughout the synthesis process, whereas microfluidics offers a well-controlled microenvironment to spatially analyze the process with high temporal resolution (~milliseconds). For the model system of polymeric nanocomplexes, two distinct stages in the self-assembly process were captured by this analytic platform. The kinetic aspect of the self-assembly process obtained at the microscale would be particularly valuable for microreactor-based reactions which are relevant to many micro- and nano-scale applications. Further, nanocomplexes may be customized through proper design of microfludic devices, and the resulting QD-FRET polymeric DNA nanocomplexes could be readily applied for establishing structure-function relationships. 

We present a novel and powerful integration of nanophotonics (QD-FRET) and microfluidics to investigate the formation of polyelectrolyte polyplexes, which is expected to provide better control and synthesis of uniform and customizable polyplexes for future nucleic acid-based therapeutics.

Advances in genomics continue to fuel the development of therapeutics that can target pathogenesis at the cellular and molecular level. Typically ...

Quantitative Real-Time PCR using the Thermo Scientific Solaris qPCR Assay

The Solaris qPCR Gene Expression Assay is a novel type of primer/probe set, designed to simplify the qPCR process while maintaining the sensitivity and accuracy of the assay. These primer/probe sets are pre-designed to &gt;98% of the human and mouse genomes and feature significant improvements from previously available technologies. These improvements were made possible by virtue of a novel design algorithm, developed by Thermo Scientific bioinformatics experts.
Several convenient features have been incorporated into the Solaris qPCR Assay to streamline the process of performing quantitative real-time PCR. First, the protocol is similar to commonly employed alternatives, so the methods used during qPCR are likely to be familiar. Second, the master mix is blue, which makes setting the qPCR reactions easier to track. Third, the thermal cycling conditions are the same for all assays (genes), making it possible to run many samples at a time and reducing the potential for error. Finally, the probe and primer sequence information are provided, simplifying the publication process.
Here, we demonstrate how to obtain the appropriate Solaris reagents using the GENEius product search feature found on the ordering web site (www.thermo.com/solaris) and how to use the Solaris reagents for performing qPCR using the standard curve method.

The Solaris qPCR Gene Expression Assays are novel pre-designed qPCR primer/probe combinations designed to simplify the qPCR process without sacrificing the specificity and robustness of the assay.

The Solaris qPCR Gene Expression Assay is a novel type of primer/probe set, designed to simplify the qPCR process while maintaining the sensitivity and ...

Stable Isotopic Profiling of Intermediary Metabolic Flux in Developing and Adult Stage Caenorhabditis elegans

Stable isotopic profiling has long permitted sensitive investigations of the metabolic consequences of genetic mutations and/or pharmacologic therapies in cellular and mammalian models. Here, we describe detailed methods to perform stable isotopic profiling of intermediary metabolism and metabolic flux in the nematode, Caenorhabditis elegans. Methods are described for profiling whole worm free amino acids, labeled carbon dioxide, labeled organic acids, and labeled amino acids in animals exposed to stable isotopes either from early development on nematode growth media agar plates or beginning as young adults while exposed to various pharmacologic treatments in liquid culture. Free amino acids are quantified by high performance liquid chromatography (HPLC) in whole worm aliquots extracted in 4% perchloric acid. Universally labeled 13C-glucose or 1,6-13C2-glucose is utilized as the stable isotopic precursor whose labeled carbon is traced by mass spectrometry in carbon dioxide (both atmospheric and dissolved) as well as in metabolites indicative of flux through glycolysis, pyruvate metabolism, and the tricarboxylic acid cycle. Representative results are included to demonstrate effects of isotope exposure time, various bacterial clearing protocols, and alternative worm disruption methods in wild-type nematodes, as well as the relative extent of isotopic incorporation in mitochondrial complex III mutant worms (isp-1(qm150)) relative to wild-type worms. Application of stable isotopic profiling in living nematodes provides a novel capacity to investigate at the whole animal level real-time metabolic alterations that are caused by individual genetic disorders and/or pharmacologic therapies.

Stable Isotopic Profiling of Intermediary Metabolic Flux in Developing and Adult Stage Caenorhabditis elegans

Stable isotopic profiling by gas chromatography mass spectrometric analysis of intermediary metabolic flux is described in the nematode, Caenorhabditis elegans. Methods are detailed for assessing isotopic enrichment in carbon dioxide, organic acids, and amino acids following isotope exposure either during development on agar plates or during adulthood in liquid culture.

Stable isotopic profiling has long permitted sensitive investigations of the metabolic consequences of genetic mutations and/or pharmacologic therapies in ...

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

Synapses are composed of a presynaptic active zone in the signaling cell and a postsynaptic terminal in the target cell. In the case of chemical synapses, messages are carried by neurotransmitters released from presynaptic terminals and received by receptors on postsynaptic cells. Our previous research in Caenorhabditis elegans has shown that VSM-1 negatively regulates exocytosis. Additionally, analysis of synapses in vsm-1 mutants showed that animals lacking a fully functional VSM-1 have increased synaptic connectivity. Based on these preliminary findings, we hypothesized that C. elegans VSM-1 may play a crucial role in synaptogenesis. To test this hypothesis, double-labeled microarray analysis was performed, and gene expression profiles were determined. First, total RNA was isolated, reversely transcribed to cDNA, and hybridized to the DNA microarrays. Then, in-silico analysis of fluorescent probe hybridization revealed significant induction of many genes coding for members of the major sperm protein family (MSP) in mutants with enhanced synaptogenesis. MSPs are the major component of sperm in C. elegans and appear to signal nematode oocyte maturation and ovulation . In fruit flies, Chai and colleagues 1 demonstrated that MSP-like molecules regulate presynaptic bouton number and size at the neuromuscular junction. Moreover, analysis performed by Tsuda and coworkers 2 suggested that MSPs may act as ligands for Eph receptors and trigger receptor tyrosine kinase signaling cascades. Lastly, real time PCR analysis corroborated that the gene coding for MSP-32 is induced in vsm-1(ok1468) mutants. Taken together, research performed by our laboratory has shown that vsm-1 mutants have a significant increase in synaptic density, which could be mediated by MSP-32 signaling.

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

Microarray analysis was conducted to determine genetic expression profiles in C. elegans, and real-time PCR was used to validate and quantify microarray data.

Synapses are composed of a presynaptic active zone in the signaling cell and a postsynaptic terminal in the target cell. In the case of chemical synapses, ...

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Streptomycetes are filamentous soil bacteria that are used in industry for the production of enzymes and antibiotics. When grown in bioreactors, these organisms form networks of interconnected hyphae, known as pellets, which are heterogeneous in size. Here we describe a method to analyze and sort mycelial pellets using a Complex Object Parametric Analyzer and Sorter (COPAS). Detailed instructions are given for the use of the instrument and the basic statistical analysis of the data. We furthermore describe how pellets can be sorted according to user-defined settings, which enables downstream processing such as the analysis of the RNA or protein content. Using this methodology the mechanism underlying heterogeneous growth can be tackled. This will be instrumental for improving streptomycetes as a cell factory, considering the fact that productivity correlates with pellet size.

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Liquid-grown Streptomyces cultures are characterized by mycelial pellets that are heterogeneous in size. We here describe a method to analyze and sort such pellets in a high-throughput manner. These pellets can be used for further analyses, which will provide leads to understand and control growth heterogeneity.

Streptomycetes are filamentous soil bacteria that are used in industry for the production of enzymes and antibiotics. When grown in bioreactors, these ...

Real Time Measurements of Membrane Protein:Receptor Interactions Using Surface Plasmon Resonance (SPR)

Protein-protein interactions are pivotal to most, if not all, physiological processes, and understanding the nature of such interactions is a central step in biological research. Surface Plasmon Resonance (SPR) is a sensitive detection technique for label-free study of bio-molecular interactions in real time. In a typical SPR experiment, one component (usually a protein, termed 'ligand') is immobilized onto a sensor chip surface, while the other (the 'analyte') is free in solution and is injected over the surface. Association and dissociation of the analyte from the ligand are measured and plotted in real time on a graph called a sensogram, from which pre-equilibrium and equilibrium data is derived. Being label-free, consuming low amounts of material, and providing pre-equilibrium kinetic data, often makes SPR the method of choice when studying dynamics of protein interactions. However, one has to keep in mind that due to the method's high sensitivity, the data obtained needs to be carefully analyzed, and supported by other biochemical methods. 
SPR is particularly suitable for studying membrane proteins since it consumes small amounts of purified material, and is compatible with lipids and detergents. This protocol describes an SPR experiment characterizing the kinetic properties of the interaction between a membrane protein (an ABC transporter) and a soluble protein (the transporter's cognate substrate binding protein).

Real Time Measurements of Membrane Protein:Receptor Interactions Using Surface Plasmon Resonance SPR

Surface Plasmon Resonance (SPR) is a label-free method for detecting bio-molecular interactions in real time. Herein, a protocol for a membrane protein:receptor interaction experiment is described, while discussing the pros and cons of the technique.

Protein-protein interactions are pivotal to most, if not all, physiological processes, and  understanding the nature of such interactions is a central ...

Real Time Analysis of Metabolic Profile in Ex Vivo Mouse Intestinal Crypt Organoid Cultures

The small intestinal mucosa exhibits a repetitive architecture organized into two fundamental structures: villi, projecting into the intestinal lumen and composed of mature enterocytes, goblet cells and enteroendocrine cells; and crypts, residing proximal to the submucosa and the muscularis, harboring adult stem and progenitor cells and mature Paneth cells, as well as stromal and immune cells of the crypt microenvironment. Until the last few years, in vitro studies of small intestine was limited to cell lines derived from either benign or malignant tumors, and did not represent the physiology of normal intestinal epithelia and the influence of the microenvironment in which they reside. Here, we demonstrate a method adapted from Sato et al. (2009) for culturing primary mouse intestinal crypt organoids derived from C57BL/6 mice. In addition, we present the use of crypt organoid cultures to assay the crypt metabolic profile in real time by measurement of basal oxygen consumption, glycolytic rate, ATP production and respiratory capacity. Organoids maintain properties defined by their source and retain aspects of their metabolic adaptation reflected by oxygen consumption and extracellular acidification rates. Real time metabolic studies in this crypt organoid culture system are a powerful tool to study crypt organoid energy metabolism, and how it can be modulated by nutritional and pharmacological factors.

Real Time Analysis of Metabolic Profile in Ex Vivo Mouse Intestinal Crypt Organoid Cultures

Small intestinal crypt organoids cultured ex vivo provide a tissue culture system that recapitulates growth of crypts dependent on stem cells and their niche. We established a method to assay the metabolic profile in real time in primary mouse crypt organoids. We found organoids maintain physiological properties defined by their source.

The small intestinal mucosa exhibits a repetitive architecture organized into two fundamental structures: villi, projecting into the intestinal lumen and ...

Silencing of BRCA2 to Identify Novel BRCA2-regulated Biological Functions in Cultured Human Cells

Silencing of the tumor suppressor protein BRCA2 and its detection by conventional biochemical analyses represent a great technical challenge owing to the large size of the human BRCA2 protein (approximately 390 kDa). We report modifications of standard siRNA transfection and immunoblotting protocols to silence human BRCA2 and detect endogenous BRCA2 protein, respectively, in human epithelial cell lines. Key steps include a high siRNA to transfection reagent ratio and two subsequent rounds of siRNA transfection within the same experiment. Using these and other modifications to the standard protocol we consistently achieve more than 70% silencing of the human BRCA2 gene as judged by immunoblotting analysis with anti-BRCA2 antibodies. In addition, denaturation of the cell lysates at 55 &#176;C instead of the conventional 70-100 &#176;C and other technical optimizations of the immunoblotting procedure allow detection of intact BRCA2 protein even when very low amounts of starting material are available or when BRCA2 protein expression levels are very low. Efficient silencing of BRCA2 in human cells offers a valuable strategy to disrupt BRCA2 function in cells with intact BRCA2, including tumor cells, to examine new molecular pathways and cellular functions that may be affected by pathogenic BRCA2 mutations in tumors. Adaptation of this protocol for efficient silencing and analysis of other &#39;large&#39; proteins like BRCA2 should be readily achievable.

Silencing of BRCA2 to Identify Novel BRCA2-regulated Biological Functions in Cultured Human Cells

Gene silencing by siRNA represents a convenient experimental strategy to analyze BRCA2-dependent biological functions with immediate implications to better understand cancer biology. A method to efficiently silence BRCA2, along with the experimental procedure to detect and quantify changes in BRCA2 protein expression by immunoblotting in human cell lines, is presented.

Silencing of the tumor suppressor protein BRCA2 and its detection by conventional biochemical analyses represent a great technical challenge owing to the ...

Real-time Imaging of Plant Cell Surface Dynamics with Variable-angle Epifluorescence Microscopy

A plant&#8217;s cell surface is its interface for perceiving environmental cues; it responds with cell biological changes such as membrane trafficking and cytoskeletal rearrangement. Real-time and high-resolution image analysis of such intracellular events will increase the understanding of plant cell biology at the molecular level. Variable angle epifluorescence microscopy (VAEM) is an emerging technique that provides high-quality, time-lapse images of fluorescently-labeled proteins on the plant cell surface. In this article, practical procedures are described for VAEM specimen preparation, adjustment of the VAEM optical system, movie capturing and image analysis. As an example of VAEM observation, representative results are presented on the dynamics of PATROL1. This is a protein essential for stomatal movement, thought to be involved in proton pump delivery to plasma membranes in the stomatal complex of Arabidopsis thaliana. VAEM real-time observation of guard cells and subsidiary cells in A. thaliana cotyledons showed that fluorescently-tagged PATROL1 appeared as dot-like structures on plasma membranes for several seconds and then disappeared. Kymograph analysis of VAEM movie data determined the time distribution of the presence (termed &#8216;residence time&#8217;) of the dot-like structures. The use of VAEM is discussed in the context of this example.

The goal of this protocol is to demonstrate how to monitor fluorescently-tagged protein dynamics on plant cell surfaces with variable-angle epifluorescence microscopy, showing blinking dots of GFP-tagged PATROL1, a membrane trafficking protein, in the cell cortex of the stomatal complex in Arabidopsis thaliana.

A plant&#8217;s cell surface is its interface for perceiving environmental cues; it responds with cell biological changes such as membrane trafficking and ...

Mixed Primary Cultures of Murine Small Intestine Intended for the Study of Gut Hormone Secretion and Live Cell Imaging of Enteroendocrine Cells

The gut is the largest endocrine organ of the body, with hormone-secreting enteroendocrine cells located along the length of the gastrointestinal epithelium. Despite their physiological importance, enteroendocrine cells represent only a small fraction of the epithelial cell population and in the past, their characterization has presented a considerable challenge resulting in a reliance on cell line models. Here, we provide a detailed protocol for the isolation and culture of mixed murine small intestinal cells. These primary cultures have been used to identify the signaling pathways underlying the stimulation and inhibition of gut peptide secretion in response to a number of nutrients and neuropeptides as well as pharmacological agents. Furthermore, in combination with the use of transgenic fluorescent reporter mice, we have demonstrated that these primary cultures become a powerful tool for the examination of fluorescently-tagged enteroendocrine cells at the intracellular level, using methods such as patch clamping and single-cell calcium and cAMP-FRET imaging.

This protocol describes the isolation and culture of mixed murine small intestinal cells. These primary intestinal cultures enable the investigation of signaling pathways underlying gut peptide secretion using a number of techniques.