title: A Method for Measuring Metabolism in Sorted Subpopulations of Complex Cell Communities Using Stable Isotope Tracing.
abstract: 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.
authors.affiliation: Department of Medicine, Unit of Computational Medicine, Karolinska Institutet; Center for Molecular Medicine, Karolinska Institutet.
authors.forename: Irena
authors.initials: I
authors.lastname: Roci
authors.affiliation: Department of Medical Biochemistry and Biophysics, Division of Physiological Chemistry 2, Karolinska Institutet.
authors.forename: Hector
authors.initials: H
authors.lastname: Gallart-Ayala
authors.affiliation: Department of Medicine, University of California San Diego.
authors.forename: Jeramie
authors.initials: J
authors.lastname: Watrous
authors.affiliation: Department of Medicine, University of California San Diego.
authors.forename: Mohit
authors.initials: M
authors.lastname: Jain
authors.affiliation: Department of Medical Biochemistry and Biophysics, Division of Physiological Chemistry 2, Karolinska Institutet.
authors.forename: Craig E
authors.initials: CE
authors.lastname: Wheelock
authors.affiliation: Department of Medicine, Unit of Computational Medicine, Karolinska Institutet; Center for Molecular Medicine, Karolinska Institutet; roland.nilsson@ki.se.
authors.forename: Roland
authors.initials: R
authors.lastname: Nilsson
mesh_terms: D002453:Cell Cycle; D002478:Cells, Cultured; D002853:Chromatography, Liquid / Q000379:methods*; D005434:Flow Cytometry; D006801:Humans; D007553:Isotope Labeling / Q000379:methods*; D007554:Isotopes / Q000032:analysis; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics / Q000379:methods*
chemical_list: D007554:Isotopes