The authors would like to thank Dr. Anas Kamleh for valuable help with optimizing mass spectrometry methods, and Annika von Vollenhoven for assistance with cell sorting. This research was supported by the Swedish Foundation for Strategic Research (grant no. FFL12-0220) and the Strategic Programme in Cancer Research (IR, RN); the Swedish Heart-Lung Foundation (CEW, HG); and Mary Kay Foundation (JW, MJ).

1. Metabolite Extraction
<ol>
	<li>Extraction from dish
	<ol>
		<li>Culture cells in a 6-well plate in triplicates in stable isotope labeled culture media + dialyzed supplements (serum or other growth supplements) until cells become 75% confluent. 
		NOTE: Here culture HeLa cells for 48 h in RPMI containing 40% U-13C-Glucose and 70% U-13C, 15N2-Glutamine and 5% dialyzed FBS (Fetal Bovine Serum). Dialyzed FBS is used to get rid of the small molecular weight metaboli...

<ol>
	<li>Gregersen, P. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell+type-specific+eQTLs+in+the+human+immune+system.">Cell type-specific eQTLs in the human immune system.</a> Nat. Genet. 44 (5), 478-480 (2012).</li><li>Heppner, G. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor+heterogeneity.">Tumor heterogeneity.</a> Cancer Res. 44 (6), 2259-2265 (1984).</li><li>Prat, A., 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=Characterization+of+cell+lines+derived+from+breast+cancers+and+normal+mammary+tissues+for+the+study+of+the+intrinsic+molecular+subtypes.">Characterization of cell lines derived from breast cancers and normal mammary tissues for the study of the intrinsic molecular subtypes.</a> Breast Cancer Res. Treat. 142 (2), 237-255 (2013).</li><li>Magistretti, P. J., Allaman, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Cellular+Perspective+on+Brain+Energy+Metabolism+and+Functional+Imaging.">A Cellular Perspective on Brain Energy Metabolism and Functional Imaging.</a> Neuron. 86 (4), 883-901 (2015).</li><li>Angelini, G., 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=Antigen-presenting+dendritic+cells+provide+the+reducing+extracellular+microenvironment+required+for+T+lymphocyte+activation.">Antigen-presenting dendritic cells provide the reducing extracellular microenvironment required for T lymphocyte activation.</a> Proc. Natl. Acad. Sci. U. S. A. 99, 1491-1496 (2002).</li><li>Koukourakis, M. I., Giatromanolaki, A., Harris, A. L., Sivridis, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+metabolic+pathways+between+cancer+cells+and+stromal+cells+in+colorectal+carcinomas:+A+metabolic+survival+role+for+tumor-associated+stroma.">Comparison of metabolic pathways between cancer cells and stromal cells in colorectal carcinomas: A metabolic survival role for tumor-associated stroma.</a> Cancer Res. 66 (2), 632-637 (2006).</li><li>Hollenbaugh, J. A., Munger, J., Kim, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolite+profiles+of+human+immunodeficiency+virus+infected+CD4++T+cells+and+macrophages+using+LC-MS/MS+analysis.">Metabolite profiles of human immunodeficiency virus infected CD4+ T cells and macrophages using LC-MS/MS analysis.</a> Virology. 415 (2), 153-159 (2011).</li><li>Richardson, G. 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Chem. 88 (5), 2707-2713 (2016).</li><li>Shapiro, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Practical flow cytometry. , (2003).</li><li>Sakaue-Sawano, A., 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=Visualizing+spatiotemporal+dynamics+of+multicellular+cell-cycle+progression.">Visualizing spatiotemporal dynamics of multicellular cell-cycle progression.</a> Cell. 132 (3), 487-498 (2008).</li><li>Noack, S., Wiechert, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+metabolomics:+A+phantom.">Quantitative metabolomics: A phantom.</a> Trends Biotechnol. 32 (5), 238-244 (2014).</li></ol>

The authors have nothing to disclose.

Our method is based on the principle that MIDs in cellular metabolites reflect the &#34;history&#34; of metabolic activities of a cell. This makes it possible to investigate metabolic activities in subpopulation of cells, as they occurred in the complex community of cells, prior to the cell sorting procedure. In contrast, peak areas of metabolites differ markedly between extracts of sorted cells and direct extraction from the culture dish11. In part this is because the different chemical compositi...

Higher organisms contain complex communities of distinct cell types that collaborate to bring about more complex functions. For example, tumors contain not only cancerous cells, but also fibroblasts, cells that constitute blood vessels, and often immune cell infiltrates1; blood contains a complex mixture of dozens of immune cell subtypes2; and even cultured cell lines may consist of multiple subpopulations, such as the luminal and basal subtypes of breast cancer cells3. Moreover, distinct cell types that coexist can exhibit metabolic &#34;collaboration&#34;. For example, in the brain, astrocytes are thought to convert glucose to lactate, which is then &#34;fed&#34; to neurons that oxidize this substrate4; T lymphocytes are in some contexts dependent on adjacent dendritic cells as a source of cysteine5; and cancer cells may collaborate with associated fibroblasts in tumors6. To understand the metabolic behavior of such systems, it is essential to separate and measure the metabolic activities of the various cell types present.
By far the most widely used method for separating cell types is fluorescence-activated cell sorting. This method is broadly applicable, provided that the cell type or state of interest can be &#34;labeled&#34; using fluorescent antibodies, expression of engineered fluorescent proteins, or other dyes. One option is to initially separate cells types through a cell sorter, re-culture the individual cell types obtained, and then perform metabolism studies of these cultures7. However, this is only feasible if the cell type or phenotype is stable in culture conditions, and cannot capture transient behavior such as cell cycle states, nor the metabolic cooperation in co-cultures. For such cases, metabolism must be measured directly on sorted cells. This is challenging since the cell sorting procedure subjects cells to stresses that may distort their metabolism8, and we are aware of only a few studies taking this approach9,10. In particular, we have found that major metabolites such as amino acids may leak from cells kept in cell sorting buffer, so that measurements of absolute metabolite abundance are no longer reliable11 (although relative comparison between sorted fractions may still be valuable).
To circumvent these issues, we label cells with stable isotopes prior to sorting, and focus on the MIDs in cellular metabolites, rather than metabolite abundances. Since MIDs are formed over longer time scales, they should be less affected by short-term exposure to sorting conditions. We quantify MIDs using full-scan high-resolution mass spectrometry, which is sensitive enough to provide data on hundreds of metabolites starting from around 500,000 sorted cells, requiring about 30-60 min of cell sorting time. A comparison between a &#34;mock sorted&#34; control (cells passed through the cell sorter instrument without gating any specific population) and metabolite extraction directly from the culture dish is made to ensure that the observed MIDs are representative of those in the original culture. Depending on the choice of stable isotope tracers, various metabolic pathways can be studied with this method.

<table border="0" cellpadding="0" cellspacing="0" width="1001">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:420px;">HBSS</td>
			<td style="width:165px;">Sigma</td>
			<td style="width:139px;">H6648</td>
			<td style="width:279px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">INFLUX (inFlux v7 Sorter)</td>
			<td style="width:165px;">BD Biosciences</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">U-13C-Glucose</td>
			<td>Cambridge isotopes</td>
			<td>40762-22-9 / GLC-018</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">U-13C,15N2-Glutamine</td>
			<td>Cambridge isotopes</td>
			<td>CNLM-1275-H-0.1</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Methanol (JT Baker), HPLC grade</td>
			<td style="width:165px;">VWR</td>
			<td style="width:139px;">BAKR8402.2500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Ultrafree - MC - VV centrifugal Filters. Durapore PVDF 0.1 &#181;m</td>
			<td style="width:165px;">Millipore</td>
			<td style="width:139px;">UFC30VV00</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Ultimate 3,000 UHPLC</td>
			<td style="width:165px;">Thermo Fisher scientific</td>
			<td style="width:139px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Q-Exactive Orbitrap Mass spectrometer</td>
			<td style="width:165px;">Thermo Fisher scientific</td>
			<td style="width:139px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Merk-Sequant ZIC HILIC column (150 mm x 4.6 mm, 5 &#181;m)</td>
			<td style="width:165px;">Merck KGaA</td>
			<td style="width:139px;">1.50444.0001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Merk-Sequant ZIC HILIC guard column (20x2.1 mm)</td>
			<td style="width:165px;">Merck KGaA</td>
			<td style="width:139px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Acetonitrile Optima LC-MS, amber glass</td>
			<td style="width:165px;">Fisher Scientific</td>
			<td style="width:139px;">A955-212</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Milli-Q water</td>
			<td style="width:165px;">Millipore</td>
			<td style="width:139px;"></td>
			<td>Produced with a Milli-Q Gradient system</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MYRSYRA 99.5% OPTIMA (Formic acid)</td>
			<td style="width:165px;">Fisher Scientific</td>
			<td style="width:139px;">11423423</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">X100 Screw Vial 1.5ml, 8-425 32x11.6mm,amber, 100 units</td>
			<td style="width:165px;">Thermo Fisher scientific</td>
			<td style="width:139px;">10560053</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">X100 LOCK SKRUV VITT PTFE PACKNING 8-425 (Screw caps)</td>
			<td style="width:165px;">Thermo Fisher scientific</td>
			<td style="width:139px;">12458636</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">ProteoMass LTQ/FT-Hybrid ESI Pos. Mode Cal Mix</td>
			<td style="width:165px;">Sigma-Aldrich</td>
			<td style="width:139px;">MSCAL5</td>
			<td>Calibration kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SNAKESKIN 10K MWCO&#160;</td>
			<td style="width:165px;">Thermo Fisher scientific</td>
			<td style="width:139px;">88245</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Mathematica v.10&#160;</td>
			<td style="width:165px;">Wolfram Research</td>
			<td style="width:139px;"></td>
			<td></td>
		</tr>
	</tbody>
</table>

a method for measuring metabolism in sorted subpopulations of complex cell communities using stable isotope tracing

Mammalian cell types exhibit specialized metabolism, and there is ample evidence that various co-existing cell types engage in metabolic cooperation. Moreover, even cultures of a single cell type may contain cells in distinct metabolic states, such as resting or cycling cells. Methods for measuring metabolic activities of such subpopulations are valuable tools for understanding cellular metabolism. Complex cell populations are most commonly separated using a cell sorter, and subpopulations isolated by this method can be analyzed by metabolomics methods. However, a problem with this approach is that the cell sorting procedure subjects cells to stresses that may distort their metabolism.
To overcome these issues, we reasoned that the mass isotopomer distributions (MIDs) of metabolites from cells cultured with stable isotope-labeled nutrients are likely to be more stable than absolute metabolite concentrations, because MIDs are formed over longer time scales and should be less affected by short-term exposure to cell sorting conditions. Here, we describe a method based on this principle, combining cell sorting with liquid chromatography-high resolution mass spectrometry (LC-HRMS). The procedure involves analyzing three types of samples: (1) metabolite extracts obtained directly from the complex population; (2) extracts of "mock sorted" cells passed through the cell sorter instrument without gating any specific population; and (3) extracts of the actual sorted populations. The mock sorted cells are compared against direct extraction to verify that MIDs are indeed not altered by the cell sorting procedure itself, prior to analyzing the actual sorted populations. We show example results from HeLa cells sorted according to cell cycle phase, revealing changes in nucleotide metabolism.

As an example, here we describe an experiment investigating the metabolism of HeLa cells sorted according to cell cycle phase. To label a wide range of central metabolites on both carbons and nitrogens, we cultured cells for 48 h using U-13C-glucose and U-13C, 15N-glutamine as tracers. To obtain rich MIDs for the validation experiment, we here chose a mixture of 40% U-13C-Glucose and 70% U-13C,15N2-Glutamine, as intermediat...

Watch this Scientific Journal Video about A Method for Measuring Metabolism in Sorted Subpopulations of Complex Cell Communities Using Stable Isotope Tracing at JoVE.com

A Method for Measuring Metabolism in Sorted Subpopulations of Complex Cell Communities Using Stable Isotope Tracing

This article describes a method for studying cellular metabolism in complex communities of multiple cell types, using a combination of stable isotope tracing, cell sorting to isolate specific cell types, and mass spectrometry.

Mammalian cell types exhibit specialized metabolism, and there is ample evidence that various co-existing cell types engage in metabolic cooperation. ...

The overall goal of this method is to use isotope tracing to measure the metabolism of sorted populations of complex cell communities. So with this method, we can study the metabolic differences between subpopulations of complex cell communities, and also the metabolic collaboration between those subpopulations. The main advantage with this technique is that by combining isotope tracing with cell sorting, we can get a more reliable measure of metabolism, and also we can validate how reliable the method is.Visual demonstration of this method is critical, as it combine different techniques, and the way cells are handled and the length of the procedure might affect cell metabolism. For metabolite extraction from a dish, first culture cells in a six-well plate in stable isotope labeled culture medium containing dialyzed supplements. When the cells reach 75%confluency, rinse the wells two times with 500 microliters of cold HBSS containing uniformly labeled glucose.Then add 600 microliters of 100%dry ice precooled methanol to each well, and transfer the plate to the dry ice. Use a cell scraper to detach the cells and then carefully transfer the extracts from each well into individual microcentrifuge tubes. Store cells at minus 80 degrees Celsius until mass spectrometry analysis.For metabolite extraction of sorted cells, culture cells in a 100 millimeter dish in labeled culture medium with dialyzed supplements, so that they reach 75%confluency by the sorting day. For pulse labeling of cell cycle sorted cells, culture the cells in unlabeled medium containing dialyzed supplements until they reach 75%confluency. Then, pulse label the cells for two hours by replacing the medium with fresh labeled culture medium.Rinse the dish with warm HBSS containing uniformly labeled glucose, and detach the cells with 1.5 milliliters of trypsin EDTA at 37 degrees Celsius. After four minutes, deactivate the trypsin with three milliliters of ice cold HBSS containing labeled glucose and dialyzed supplements, and transfer the cells to a 15 milliliter conical tube for centrifugation. Resuspend the pellet in HBSS containing labeled glucose, dialyzed supplements, and EDTA at a one to two times 10 to the six cells per milliliter concentration, and filter the cells through a 40-micron strainer to obtain a single cell suspension.Transfer the cells into a five milliliter tube and sort them on a flow cytometer. For metabolite extraction from mock sorted cells, gait out the debris and sort only the singlets. For metabolite extraction from cell cycle sorted cells, gait out the debris and doublets, and sort cells into G1 and SG2M, based on the geminin probe fluorescence.At the end of the sort, collect the cells by centrifugation and resuspend the pellet in 50 microliters of ice cold distilled water to obtain a homogeneous pellet. Then quickly extract the metabolites by adding 540 microliters of dry ice cooled methanol. Store the sample at minus 80 degrees Celsius until LCMS analysis.The extraction of metabolites from sorted cells must be well planned in advance, with experimental work being completed as quickly as possible to minimize the metabolic alterations. For analysis of the extracted metabolites, first select a number of metabolites with corresponding available standards that exhibit good quality sample peaks. Next, verify the quality of the peaks, taking care not to include false isotopes.Calculate the mass isotope from our fractions for the isotope labeled samples by dividing the peak area of each mass isotope from our fraction by the total peak areas of all the mass isotopes from our fractions. Then, calculate the labeled carbon fractions for the enrichment of carbon-13 using the formula for carbon enrichment. Finally, calculate the labeled nitrogen fractions for the enrichment of nitrogen-15 using the formula for nitrogen enrichment.In this representative experiment, 66 metabolites selected from the data analysis were present in the mock sorted cells, 60 of which appeared to be labeled with similar mass isotope from our distributions between the dish extracts and the mock sorted cells. For example, the mass isotope from our distribution of glutamate is similar between the dish and mock sorted extracts, indicating that the glutamate mass isotope from our distribution is also reliable in sorted cell populations. Analysis of HELA cells sorted into either G0, G1, or SG2M cell cycle stages using the FUCCI geminin probe reveals cytidine labeling in both populations with a higher enrichment in the SG2M stage, consistent with an increased de novo synthesis of nucleotides during the S phase.In this experiment, the mass isotope from our distribution exhibited the same pattern in both of the cell cycle sorted fractions, suggesting that the same synthesis pathway is used, but is more active in the SG2M stage, demonstrating that metabolic differences are readily detectable by this method, even between closely related subpopulations. After watching this video, you should have a good grasp on how to extract metabolites from sorted fractions, and understand the caveats. While attempting this procedure, it's important to remember to handle the cells quickly during sorting and metabolite extraction, as the manner and the length of time cells are handled can affect their metabolism.Once mastered, this technique can be performed in five hours. This procedure can be applied to other cell types. For example, immune cell subsets in blood, or different types of cells within a tumor, using a variety of probes, antibodies, or staining methods for sorting.

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Biochemistry

8.1K Görüntüleme.  Karolinska Institutet. The overall goal of this method is to use isotope tracing to measure the metabolism of sorted populations of complex cell communities. So with this method, we can study the metabolic differences between subpopulations of complex cell communities, and also the metabolic collaboration between those subpopulations. The main advantage with this technique is that by combining isotope tracing with cell sorting, we can get a more reliable measure of metabolism, and also we can validate how reliable ...