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 metabolites which might contaminate the labeled media. Culturing cells in dialyzed supplement prior to the real experiment is recommended to ensure cells are growing normally in the medium. Supplements are dialyzed in 0.15 M NaCl solution overnight using snake skin dialysis tubing.</li>
		<li>At the day of extraction discard culture media, rinse wells twice with 500 &#181;L cold HBSS and then discard it. 
		NOTE: Here use HBSS containing 40% U-13C-Glucose since it is also in the culture media.</li>
		<li>Add 600 &#181;L 100% methanol pre-cooled on dry ice.</li>
		<li>Transfer the dish to dry ice and remove cell material with a cell scraper.</li>
		<li>Carefully pipette the cell extracts to a microcentrifuge tube and store at -80 &#176;C until mass spectrometry analysis.</li>
	</ol>
	</li>
	<li>Extraction of mock sorted cells
	<ol>
		<li>Culture cells in a 100 mm dish in triplicates in stable isotope labeled culture media + dialyzed supplements. 
		NOTE: Here culture HeLa cells for 48 h in 100 mm dish because a high number of cells (~4 x 106) are needed to obtain 500,000 sorted cells. This number of HeLa cells extract was required to obtain good measurement of metabolites. The culture media used was RPMI containing 40% U-13C-Glucose and 70% U-13C, 15N2-Glutamine and 5% dialyzed FBS.</li>
		<li>At the day of extraction, discard culture media, rinse wells with 1.5 mL warm HBSS and then discard it.</li>
		<li>Detach cells by adding 1.5 mL trypsin/EDTA for 4 min at 37 &#176;C. Perform the following steps in 4 &#176;C or in ice.</li>
		<li>Deactivate trypsin by adding 3 mL ice cold HBSS (Hank&#39;s Balanced Salt Solution) + dialyzed supplement.</li>
		<li>Collect cells in a 15 mL tube and centrifuge at 750 x g for 3 min.</li>
		<li>Resuspend the pellet in HBSS + dialyzed supplement + 1 mM EDTA at a concentration 1-2 x 106 cells/mL, pass through 40 &#181;m cell strainers to obtain single cells, and transfer to a 5 mL tube.</li>
		<li>Sort cells through cell sorter gating only for singlets, and centrifuge sorted cells at 750 x g for 3 min at 4 &#176;C. 
		NOTE: Here sort HeLa cells at a rate 1,000 events/s, with instrument pressure 27 psi, and using a 100 &#181;m nozzle. HeLa cells are big so they should be sorted at a slow event rate and large nozzle to get as intact pellet as possible. Keep the cells in cold blocks throughout sorting to decrease the metabolism. A thorough description of sorting procedure is described previously12.</li>
		<li>Discard the supernatant and resuspend the pellet in 50 &#181;L ice cold dH2O to obtain a homogenous pellet before adding methanol. Addition of cold methanol directly to pellet forms a solid pellet which is hard to resuspend.</li>
		<li>Extract metabolites by adding 540 &#181;L methanol kept in dry ice and keep extracts at -80 &#176;C until liquid chromatography &#8211; high resolution mass spectrometry (LC-HRMS) analysis.</li>
	</ol>
	</li>
	<li>Extraction of cell cycle sorted cells
	<ol>
		<li>Culture cells in a 100 mm dish in triplicates in culture media + dialyzed supplements. 
		NOTE: Here culture HeLa cells containing Geminin Fucci Green (mAG1-hGem) probe13 which allows for sorting of G1 (negative) and SG2M (positive) cells. Cells can be cultured in stable isotope tracing media for as long as required. Here we have cultured them for 46 h in unlabeled media, then we have switched to RPMI containing 40% U-13C-Glucose and 70% U-13C, 15N2-Glutamine 2 h before starting sorting. This was done in order to be able to study the cell cycle phases which requires a short pulse labeling.</li>
		<li>At the day of extraction, discard culture media, rinse wells with 1.5 mL warm HBSS and then discard it.</li>
		<li>Detach cells by adding 1.5 mL trypsin/EDTA for 4 min at 37 &#176;C. Perform the following steps in 4 &#176;C or in ice.</li>
		<li>Deactivate trypsin by adding 3 mL ice cold HBSS + dialyzed supplement.</li>
		<li>Collect cells in a 15 mL tube and centrifuge at 750 x g for 3 min.</li>
		<li>Resuspend the pellet in HBSS + dialyzed supplement + 1 mM EDTA at a concentration 1-2 x 106 cells/mL, pass through 40 &#181;m cell strainers to obtain single cells, and transfer to a 5 mL tube.</li>
		<li>Sort cells through the cell sorter gating out debris and doublets, then gating for the cell marker of interest, and centrifuge sorted cells at 750 x g for 3 min at 4 &#176;C. 
		NOTE: Here sort HeLa cells at a rate 1,000 events/s, with instrument pressure 27 psi, and using a 100 &#181;m nozzle. Keep the cells in cold blocks throughout sorting to decrease the metabolism rate.</li>
		<li>Discard the supernatant and resuspend the pellet in 50 &#181;L ice cold dH2O to obtain a homogenous pellet before adding methanol. Addition of cold methanol directly to pellet forms a solid pellet which is hard to resuspend.</li>
		<li>Extract the metabolites by adding 540 &#181;L methanol kept in dry ice and keep extracts at -80 &#176;C until LC-HRMS analysis.</li>
	</ol>
	</li>
</ol>
2. Mass Spectrometry Analysis
Note: Here we describe the protocol for analyzing cell extracts on a LC-HRMS system. Any metabolomics methods for analysis of cell extracts can be used. Full scan analysis might be useful for detecting a wide range of metabolites.
<ol>
	<li>Calibrate the instrument using a mass spectrometry reference calibration mix.</li>
	<li>Thaw cell extracts on ice for 30 min and vortex for 15 s.</li>
	<li>Transfer 100 &#181;L of the cell extract to a spin filter and centrifuge for 10 min at 13,000 x g at 4 &#176;C.</li>
	<li>Inject 12.5 &#181;L of the filtrate onto the LC-HRMS system.</li>
	<li>Separate metabolites using a Zwitterionic Hydrophilic Interaction Liquid Chromatography (ZIC-HILIC) column (150 mm x 4.6 mm, 5 &#181;m particle size) fitted with a ZIC-HILIC guard column (20 mm &#215; 2.1 mm) using a gradient elution of 0.1% formic acid in water (solvent A) and acetonitrile (solvent B). Start the gradient elution at 20% of solvent A and increase up to 80% in 17 min. Maintain this percentage during 4 min with a flow of 400 &#181;L min-1 and column temperature and sample tray at 23 &#176;C and 4 &#176;C, respectively.</li>
	<li>Use an instrument coupled to the chromatographic separation for metabolites detection, a heated electrospray (H-ESI II) in both positive and negative modes as ionization source, and a full scan acquisition mode at a mass resolving power of 70,000 Full Width Half Maximum (FWHM) (m/z 200).</li>
	<li>Use nitrogen (purity &#62;99.995%) for the sheath gas and auxiliary gas at a flow rate of 45 and 10 a.u. (arbitrary units) and set vaporizer temperature at 350 &#176;C and the electrospray voltage at 4 kV in positive mode and -3.5 kV in negative mode.</li>
</ol>
3. Data Analysis
<ol>
	<li>Select a number of metabolites for which standards are available and which show good quality peaks in the samples. Good quality peaks have high signal to noise ratio. It is important to verify peak quality and make sure not to include false isotopes. Isotopic peaks which differ in shape and/or retention time are likely false.</li>
	<li>For isotope-labeled samples calculate mass isotopomer (MI) fractions by dividing the peak area of each MI with total peak areas of all MIs.</li>
	<li>Calculate the labeled carbon/nitrogen fractions, enrichment of 13C and 15N, respectively, as 
	<img alt="Equation 1" src="/files/ftp_upload/55011/55011eq1.jpg" /> 
	where n is the total number of carbons (or nitrogens, respectively) in the metabolite, and MIx is the MI fraction of x. 
	NOTE: All calculations can be performed using programming languages.</li>
</ol>

<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. M., Lannigan, J., Macara, I. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Does+FACS+perturb+gene+expression.">Does FACS perturb gene expression.</a> Cytom. Part A. 87 (2), 166-175 (2015).</li><li>Moussaieff, 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=High-resolution+metabolic+mapping+of+cell+types+in+plant+roots.">High-resolution metabolic mapping of cell types in plant roots.</a> Proc. Natl. Acad. Sci. U. S. A. 110 (13), E1232-E1241 (2013).</li><li>Johnson, C., 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=A+metabolic+signature+of+colon+cancer+initiating+cells.">A metabolic signature of colon cancer initiating cells.</a> Cancer Metab. 2, 32 (2014).</li><li>Roci, I., 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=Metabolite+Profiling+and+Stable+Isotope+Tracing+in+Sorted+Subpopulations+of+Mammalian+Cells.">Metabolite Profiling and Stable Isotope Tracing in Sorted Subpopulations of Mammalian Cells.</a> Anal. 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><tbody><tr><td>HBSS</td><td>Sigma</td><td>H6648</td><td></td></tr><tr><td>INFLUX (inFlux v7 Sorter)</td><td>BD Biosciences</td><td></td><td></td></tr><tr><td>U-&lt;sup&gt;13&lt;/sup&gt;C-Glucose</td><td>Cambridge isotopes</td><td>40762-22-9 / GLC-018</td><td></td></tr><tr><td>U-&lt;sup&gt;13&lt;/sup&gt;C,&lt;sup&gt;15&lt;/sup&gt;N2-Glutamine</td><td>Cambridge isotopes</td><td>CNLM-1275-H-0.1</td><td></td></tr><tr><td>Methanol (JT Baker), HPLC grade</td><td>VWR</td><td>BAKR8402.2500</td><td></td></tr><tr><td>Ultrafree - MC - VV centrifugal Filters. Durapore PVDF 0.1 &amp;micro;m</td><td>Millipore</td><td>UFC30VV00</td><td></td></tr><tr><td>Ultimate 3,000 UHPLC</td><td>Thermo Fisher scientific</td><td></td><td></td></tr><tr><td>Q-Exactive Orbitrap Mass spectrometer</td><td>Thermo Fisher scientific</td><td></td><td></td></tr><tr><td>Merk-Sequant ZIC HILIC column (150 mm x 4.6&amp;nbsp;mm, 5 &amp;micro;m)</td><td>Merck KGaA</td><td>1.50444.0001</td><td></td></tr><tr><td>Merk-Sequant ZIC HILIC guard column (20 mm x 2.1 mm)</td><td>Merck KGaA</td><td></td><td></td></tr><tr><td>Acetonitrile Optima LC-MS, amber glass</td><td>Fisher Scientific</td><td>A955-212</td><td></td></tr><tr><td>Milli-Q water</td><td>Millipore</td><td></td><td>Produced with a Milli-Q Gradient system</td></tr><tr><td>Myrsyra 99.5% Optima (Formic acid)</td><td>Fisher Scientific</td><td>11423423</td><td></td></tr><tr><td>X100 Screw Vial 1.5 ml, 8-425 32x11.6 mm, amber, 100 units</td><td>Thermo Fisher scientific</td><td>10560053</td><td></td></tr><tr><td>X100 Lock Skruv Vitt PTFE Packing 8-425 (Screw caps)</td><td>Thermo Fisher scientific</td><td>12458636</td><td></td></tr><tr><td>ProteoMass LTQ/FT-Hybrid ESI Pos. Mode Cal Mix</td><td>Sigma-Aldrich</td><td>MSCAL5</td><td>Calibration kit</td></tr><tr><td>SNAKESKIN 10K MWCO&amp;nbsp;</td><td>Thermo Fisher scientific</td><td>88245</td><td></td></tr><tr><td>Mathematica v.10&amp;nbsp;</td><td>Wolfram Research</td><td></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. ...

a-method-for-measuring-metabolism-sorted-subpopulations-complex-cell

Universidad San Sebastian

Research

JoVE Journal

Biochemistry

8.2K Views.  Karolinska Institutet. 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.

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

Fatty Acid 13C Isotopologue Profiling Provides Insight into Trophic Carbon Transfer and Lipid Metabolism of Invertebrate Consumers

Fatty acids (FAs) are useful biomarkers in food web ecology because they are typically assimilated as a complete molecule and transferred into consumer tissue with minor or no modification, allowing the dietary routing between different trophic levels. However, the FA trophic marker approach is still hampered by the limited knowledge in lipid metabolism of the soil fauna. This study used entirely labelled palmitic acid (13C16:0, 99 atom%) as a tracer in fatty acid metabolism pathways of two widespread soil Collembola, Protaphorura fimata and Heteromurus nitidus. In order to investigate the fate and metabolic modifications of this precursor, a method of isotopologue profiling is presented, performed by mass spectrometry using single ion monitoring. Moreover, the upstream laboratory feeding experiment is described, as well as the extraction and methylation of dominant lipid fractions (neutral lipids, phospholipids) and the related formula and calculations. Isotopologue profiling does not only yield the overall 13C enrichment in fatty acids derived from the 13C labeled precursor but also produces the pattern of isotopologues exceeding the mass of the parent ion (i.e., the FA molecular ion M+) of each labeled FA by one or more mass units (M+1, M+2, M+3, etc.). This knowledge allows conclusions on the ratio of dietary routing of an entirely consumed FA in comparison to de novo biosynthesis. The isotopologue profiling is suggested as a useful tool for evaluation of fatty acid metabolism in soil animals to disentangle trophic interactions.

Fatty Acid 13C Isotopologue Profiling Provides Insight into Trophic Carbon Transfer and Lipid Metabolism of Invertebrate Consumers

The fatty acid trophic marker approach, i.e., the assimilation of fatty acids as entire molecule and transfer into consumer tissue with no or minor modification, is hampered by knowledge gaps in fatty acid metabolism of small soil invertebrates. Isotopologue profiling is provided as a valuable tool to disentangle trophic interactions.

Fatty acids (FAs) are useful biomarkers in food web ecology because they are typically assimilated as a complete molecule and transferred into consumer ...

Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry

Cell-free protein synthesis (CFPS) is an emerging technology in systems and synthetic biology for the in vitro production of proteins. However, if CFPS is going to move beyond the laboratory and become a widespread and standard just in time manufacturing technology, we must understand the performance limits of these systems. Toward this question, we developed a robust protocol to quantify 40 compounds involved in glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, energy metabolism and cofactor regeneration in CFPS reactions. The method uses internal standards tagged with 13C-aniline, while compounds in the sample are derivatized with 12C-aniline. The internal standards and sample were mixed and analyzed by reversed-phase liquid chromatography-mass spectrometry (LC/MS). The co-elution of compounds eliminated ion suppression, allowing the accurate quantification of metabolite concentrations over 2-3 orders of magnitude where the average correlation coefficient was 0.988. Five of the forty compounds were untagged with aniline, however, they were still detected in the CFPS sample and quantified with a standard curve method. The chromatographic run takes approximately 10 min to complete. Taken together, we developed a fast, robust method to separate and accurately quantify 40 compounds involved in CFPS in a single LC/MS run. The method is a comprehensive and accurate approach to characterize cell-free metabolism, so that ultimately, we can understand and improve the yield, productivity and energy efficiency of cell-free systems.

Here, we present a robust protocol to quantify 40 compounds involved in central carbon and energy metabolism in cell-free protein synthesis reactions. The cell-free synthesis mixture is derivatized with aniline for effective separation using reversed-phase liquid chromatography and then quantified by mass spectrometry using isotopically labelled internal standards.

Cell-free protein synthesis (CFPS) is an emerging technology in systems and synthetic biology for the in vitro production of proteins. However, if CFPS is ...

Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry

Mounting evidence has shown that the accumulation of senescent cells in the central nervous system contributes to neurodegenerative disorders such as Alzheimer&#39;s and Parkinson&#39;s diseases. Cellular senescence is a state of permanent cell cycle arrest that typically occurs in response to exposure to sub-lethal stresses. However, like other non-dividing cells, senescent cells remain metabolically active and carry out many functions that require unique transcriptional and translational demands and widespread changes in the intracellular and secreted proteomes. Understanding how protein synthesis and decay rates change during senescence can illuminate the underlying mechanisms of cellular senescence and find potential therapeutic avenues for diseases exacerbated by senescent cells. This paper describes a method for proteome-scale evaluation of protein half-lives in non-dividing cells using pulsed stable isotope labeling by amino acids in cell culture (pSILAC) in combination with mass spectrometry. pSILAC involves metabolic labeling of cells with stable heavy isotope-containing versions of amino acids. Coupled with modern mass spectrometry approaches, pSILAC enables the measurement of protein turnover of hundreds or thousands of proteins in complex mixtures. After metabolic labeling, the turnover dynamics of proteins can be determined based on the relative enrichment of heavy isotopes in peptides detected by mass spectrometry. In this protocol, a workflow is described for the generation of senescent fibroblast cultures and similarly arrested quiescent fibroblasts, as well as a simplified, single-time point pSILAC labeling time-course that maximizes coverage of anticipated protein turnover rates. Further, a pipeline is presented for the analysis of pSILAC mass spectrometry data and user-friendly calculation of protein degradation rates using spreadsheets. The application of this protocol can be extended beyond senescent cells to any non-dividing cultured cells such as neurons.

This protocol describes the workflow for metabolic labeling of senescent and non-dividing cells with pulsed SILAC, untargeted mass spectrometry analysis, and a streamlined calculation of protein half-lives.

Mounting evidence has shown that the accumulation of senescent cells in the central nervous system contributes to neurodegenerative disorders such as ...

Stable Isotope Tracing & LC-MS Analysis to Measure DHODH and SDH Activities

Oxygen-Independent Assays to Measure Mitochondrial Function in Mammals

The flow of electrons in the mitochondrial electron transport chain (ETC) supports multifaceted biosynthetic, bioenergetic, and signaling functions in mammalian cells. As oxygen (O2) is the most ubiquitous terminal electron acceptor for the mammalian ETC, the O2 consumption rate is frequently used as a proxy for mitochondrial function. However, emerging research demonstrates that this parameter is not always indicative of mitochondrial function, as fumarate can be employed as an alternative electron acceptor to sustain mitochondrial functions in hypoxia. This article compiles a series of protocols that allow researchers to measure mitochondrial function independently of the O2 consumption rate. These assays are particularly useful when studying mitochondrial function in hypoxic environments. Specifically, we describe methods to measure mitochondrial ATP production, de novo pyrimidine biosynthesis, NADH oxidation by complex I, and superoxide production. In combination with classical respirometry experiments, these orthogonal and economical assays will provide researchers with a more comprehensive assessment of mitochondrial function in their system of interest.

Author Spotlight: Oxygen-Independent Assays to Measure Mitochondrial Function in Mammals  

Here, we present a compilation of assays to directly measure mitochondrial function in mammalian cells independently of their ability to consume molecular oxygen.

The flow of electrons in the mitochondrial electron transport chain (ETC) supports multifaceted biosynthetic, bioenergetic, and signaling functions in ...

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Studies in the field of microbiology rely on the implementation of a wide range of methodologies. In particular, the development of appropriate methods substantially contributes to providing extensive knowledge of the metabolism of microorganisms growing in chemically defined media containing unique nitrogen and carbon sources. In contrast, the management through metabolism of multiple nutrient sources, despite their broad presence in natural or industrial environments, remains virtually unexplored. This situation is mainly due to the lack of suitable methodologies, which hinders investigations.
We report an experimental strategy to quantitatively and comprehensively explore how metabolism operates when a nutrient is provided as a mixture of different molecules, i.e., a complex resource. Here, we describe its application for assessing the partitioning of multiple nitrogen sources through the yeast metabolic network. The workflow combines information obtained during stable isotope tracer experiments using selected 13C- or 15N-labeled substrates. It first consists of parallel and reproducible fermentations in the same medium, which includes a mixture of N-containing molecules; however,a selected nitrogen source is labeled each time. A combination of analytical procedures (HPLC, GC-MS) is implemented to assess the labeling patterns of targeted compounds and to quantify the consumption and recovery of substrates in other metabolites. An integrated analysis of the complete dataset provides an overview of the fate of consumed substrates within cells. This approach requires an accurate protocol for the collection of samples&#8211;facilitated by a robot-assisted system for online monitoring of fermentations&#8211;and the achievement of numerous time-consuming analyses. Despite these constraints, it allowed understanding, for the first time, the partitioning of multiple nitrogen sources throughout the yeast metabolic network. We elucidated the redistribution of nitrogen from more abundant sources toward other N-compounds and determined the metabolic origins of volatile molecules and proteinogenic amino acids.

This protocol describes an experimental procedure to quantitatively and comprehensively investigate the metabolism of multiple nutrient sources. This workflow, based on a combination of isotopic tracer experiments and an analytical procedure, allows the fate of consumed nutrients and the metabolic origin of molecules synthetized by microorganisms to be determined.

Studies in the field of microbiology rely on the implementation of a wide range of methodologies. In particular, the development of appropriate methods ...

Bioengineering

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 ...

Biology

Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids

Microbes have complex metabolic pathways that can be investigated using biochemistry and functional genomics methods. One important technique to examine cell central metabolism and discover new enzymes is 13C-assisted metabolism analysis 1. This technique is based on isotopic labeling, whereby microbes are fed with a 13C labeled substrates. By tracing the atom transition paths between metabolites in the biochemical network, we can determine functional pathways and discover new enzymes. 
As a complementary method to transcriptomics and proteomics, approaches for isotopomer-assisted analysis of metabolic pathways contain three major steps 2. First, we grow cells with 13C labeled substrates. In this step, the composition of the medium and the selection of labeled substrates are two key factors. To avoid measurement noises from non-labeled carbon in nutrient supplements, a minimal medium with a sole carbon source is required. Further, the choice of a labeled substrate is based on how effectively it will elucidate the pathway being analyzed. Because novel enzymes often involve different reaction stereochemistry or intermediate products, in general, singly labeled carbon substrates are more informative for detection of novel pathways than uniformly labeled ones for detection of novel pathways3, 4. Second, we analyze amino acid labeling patterns using GC-MS. Amino acids are abundant in protein and thus can be obtained from biomass hydrolysis. Amino acids can be derivatized by N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide (TBDMS) before GC separation. TBDMS derivatized amino acids can be fragmented by MS and result in different arrays of fragments. Based on the mass to charge (m/z) ratio of fragmented and unfragmented amino acids, we can deduce the possible labeled patterns of the central metabolites that are precursors of the amino acids. Third, we trace 13C carbon transitions in the proposed pathways and, based on the isotopomer data, confirm whether these pathways are active 2. Measurement of amino acids provides isotopic labeling information about eight crucial precursor metabolites in the central metabolism. These metabolic key nodes can reflect the functions of associated central pathways.
13C-assisted metabolism analysis via proteinogenic amino acids can be widely used for functional characterization of poorly-characterized microbial metabolism1. In this protocol, we will use Cyanothece 51142 as the model strain to demonstrate the use of labeled carbon substrates for discovering new enzymatic functions.

Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids

13C-isotope labeling is a useful technique for determining the cell central metabolism for various types of microorganisms. After cells have been cultured with a specific labeled substrate, GC-MS measurement can reveal functional metabolic pathways based on unique labeling patterns in proteinogenic amino acids.

Microbes have complex metabolic pathways that can be investigated using biochemistry and functional genomics methods. One important technique to examine ...

Metabolic Analysis of Drosophila melanogaster Larval and Adult Brains

This protocol describes a method for measuring the metabolism in Drosophila melanogaster larval and adult brains. Quantifying metabolism in whole organs provides a tissue-level understanding of energy utilization that cannot be captured when analyzing primary cells and cell lines. While this analysis is ex vivo, it allows for the measurement from a number of specialized cells working together to perform a function in one tissue and more closely models the in vivo organ. Metabolic reprogramming has been observed in many neurological diseases, including neoplasia, and neurodegenerative diseases. This protocol was developed to assist the D. melanogaster community&#39;s investigation of metabolism in neurological disease models using a commercially available metabolic analyzer. Measuring metabolism of whole brains in the metabolic analyzer is challenging due to the geometry of the brain. This analyzer requires samples to remain at the bottom of a 96-well plate. Cell samples and tissue punches can adhere to the surface of the cell plate or utilize spheroid plates, respectively. However, the spherical, three-dimensional shape of D. melanogaster brains prevents the tissue from adhering to the plate. This protocol requires a specially designed and manufactured micro-tissue restraint that circumvents this problem by preventing any movement of the brain while still allowing metabolic measurements from the analyzer&#39;s two solid-state sensor probes. Oxygen consumption and extracellular acidification rates are reproducible and sensitive to a treatment with metabolic inhibitors. With a minor optimization, this protocol can be adapted for use with any whole tissue and/or model system, provided that the sample size does not exceed the chamber generated by the restraint. While basal metabolic measurements and an analysis after a treatment with mitochondrial inhibitors are described within this protocol, countless experimental conditions, such as energy source preference and rearing environment, could be interrogated.

Metabolic Analysis of Drosophila melanogaster Larval and Adult Brains

We present a protocol for measuring oxygen consumption and extracellular acidification in Drosophila melanogaster larval and adult brains. A metabolic analyzer is utilized with an adapted and optimized protocol. Micro-tissue restraints are a critical component of this protocol and were designed and created specifically for their use in this analysis.

This protocol describes a method for measuring the metabolism in Drosophila melanogaster larval and adult brains. Quantifying metabolism in whole organs ...

Neuroscience

Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose

Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to identify commensal or mutualistic bacteria species. The latter ones, have been observed to serve multiple functions to the insect, i.e. helping in insect reproduction1, boosting the immune response2, pheromone production3, as well as nutrition, including the synthesis of essential amino acids4, among others. &#160; &#160;
Due to the importance of these associations, many efforts have been made to characterize the communities down to the individual members. However, most of these efforts were either based on cultivation methods or relied on the generation of 16S rRNA gene fragments which were sequenced for final identification. Unfortunately, these approaches only identified the bacterial species present in the gut and provided no information on the metabolic activity of the microorganisms.
To characterize the metabolically active bacterial species in the gut of an insect, we used stable isotope probing (SIP) in vivo employing 13C-glucose as a universal substrate. This is a promising culture-free technique that allows the linkage of microbial phylogenies to their particular metabolic activity. This is possible by tracking stable, isotope labeled atoms from substrates into microbial biomarkers, such as DNA and RNA5. The incorporation of 13C isotopes into DNA increases the density of the labeled DNA compared to the unlabeled (12C) one. In the end, the 13C-labeled DNA or RNA is separated by density-gradient ultracentrifugation from the 12C-unlabeled similar one6. Subsequent molecular analysis of the separated nucleic acid isotopomers provides the connection between metabolic activity and identity of the species.
Here, we present the protocol used to characterize the metabolically active bacteria in the gut of a generalist insect (our model system), Spodoptera littoralis (Lepidoptera, Noctuidae). The phylogenetic analysis of the DNA was done using pyrosequencing, which allowed high resolution and precision in the identification of insect gut bacterial community. As main substrate, 13C-labeled glucose was used in the experiments. The substrate was fed to the insects using an artificial diet.

Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose

The active bacterial community associated with the gut of Spodoptera littoralis, was determined by stable-isotope-probing (SIP) coupled to pyrosequencing. Using this methodology, identification of the metabolically active bacteria species within the community was done with high resolution and precision.

Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to ...

Low-Input Metabolic Studies in Mice Cell Types

Targeted Metabolomics on Rare Primary Cells

Cellular function critically depends on metabolism, and the function of the underlying metabolic networks can be studied by measuring small molecule intermediates. However, obtaining accurate and reliable measurements of cellular metabolism, particularly in rare cell types like hematopoietic stem cells, has traditionally required pooling cells from multiple animals. A protocol now enables researchers to measure metabolites in rare cell types using only one mouse per sample while generating multiple replicates for more abundant cell types. This reduces the number of animals that are required for a given project. The protocol presented here involves several key differences over traditional metabolomics protocols, such as using 5 g/L NaCl as a sheath fluid, sorting directly into acetonitrile, and utilizing targeted quantification with rigorous use of internal standards, allowing for more accurate and comprehensive measurements of cellular metabolism. Despite the time required for the isolation of single cells, fluorescent staining, and sorting, the protocol can preserve differences among cell types and drug treatments to a large extent.

Author Spotlight: Advancing Metabolomics Analysis of Rare Hematopoietic Stem Cells 

Here, we present a protocol to accurately and reliably measure metabolites in rare cell types. Technical improvements, including a modified sheath fluid for cell sorting and the generation of relevant blank samples, enable a comprehensive quantification of metabolites with an input of only 5000 cells per sample.

Cellular function critically depends on metabolism, and the function of the underlying metabolic networks can be studied by measuring small molecule ...

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

Summary

Explore More Videos

Chapters in this video

Fatty Acid ¹³C Isotopologue Profiling Provides Insight into Trophic Carbon Transfer and Lipid Metabolism of Invertebrate Consumers

Absolute Quantification of Cell-Free Protein Synthesis Metabolism by Reversed-Phase Liquid Chromatography-Mass Spectrometry

Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry

Oxygen-Independent Assays to Measure Mitochondrial Function in Mammals

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

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

Metabolic Pathway Confirmation and Discovery Through ¹³C-labeling of Proteinogenic Amino Acids

Metabolic Analysis of Drosophila melanogaster Larval and Adult Brains

Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using ¹³C-Glucose

Targeted Metabolomics on Rare Primary Cells