<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Hagberg CE</submitter><funding>Karolinska Institutet/AstraZeneca Integrated Cardio Metabolic Centre (KI-AZ ICMC)</funding><funding>Novo Nordisk Foundation</funding><funding>The Erling-Persson Family Foundation</funding><funding>European Research Council</funding><funding>Vallee Foundation</funding><funding>Wilhelm och Else Stockmanns Stiftelse</funding><funding>Karolinska Institutet</funding><funding>Swedish Research Council</funding><funding>Diabetes Research Program at Karolinska Institutet</funding><funding>Novo Nordisk Fonden</funding><funding>Swedish Society for Medical Research</funding><pagination>2746-2756.e5</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6137819</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>24(10)</volume><pubmed_abstract>Adipocytes, once considered simple lipid-storing cells, are rapidly emerging as complex cells with many biologically diverse functions. A powerful high-throughput method for analyzing single cells is flow cytometry. Several groups have attempted to analyze and sort freshly isolated adipocytes; however, using an adipocyte-specific reporter mouse, we demonstrate that these studies fail to detect the majority of white adipocytes. We define critical settings required for adipocyte flow cytometry and provide a rigid strategy for analyzing and sorting white and brown adipocyte populations. The applicability of our protocol is shown by sorting mouse adipocytes based on size or UCP1 expression and demonstrating that a subset of human adipocytes lacks the β&lt;sub>2&lt;/sub>-adrenergic receptor, particularly in the insulin-resistant state. In conclusion, the present study confers key technological insights for analyzing and sorting mature adipocytes, opening up numerous downstream research applications.</pubmed_abstract><journal>Cell reports</journal><pubmed_title>Flow Cytometry of Mouse and Human Adipocytes for the Analysis of Browning and Cellular Heterogeneity.</pubmed_title><pmcid>PMC6137819</pmcid><funding_grant_id>261258</funding_grant_id><funding_grant_id>NNF12OC1016064</funding_grant_id><pubmed_authors>Shabalina IG</pubmed_authors><pubmed_authors>Thorell A</pubmed_authors><pubmed_authors>Li Q</pubmed_authors><pubmed_authors>Kozina V</pubmed_authors><pubmed_authors>Bhowmick D</pubmed_authors><pubmed_authors>Nedergaard J</pubmed_authors><pubmed_authors>Kutschke M</pubmed_authors><pubmed_authors>Harms MJ</pubmed_authors><pubmed_authors>Shilkova O</pubmed_authors><pubmed_authors>Spalding KL</pubmed_authors><pubmed_authors>Kiss E</pubmed_authors><pubmed_authors>Hagberg CE</pubmed_authors><pubmed_authors>Boucher J</pubmed_authors></additional><is_claimable>false</is_claimable><name>Flow Cytometry of Mouse and Human Adipocytes for the Analysis of Browning and Cellular Heterogeneity.</name><description>Adipocytes, once considered simple lipid-storing cells, are rapidly emerging as complex cells with many biologically diverse functions. A powerful high-throughput method for analyzing single cells is flow cytometry. Several groups have attempted to analyze and sort freshly isolated adipocytes; however, using an adipocyte-specific reporter mouse, we demonstrate that these studies fail to detect the majority of white adipocytes. We define critical settings required for adipocyte flow cytometry and provide a rigid strategy for analyzing and sorting white and brown adipocyte populations. The applicability of our protocol is shown by sorting mouse adipocytes based on size or UCP1 expression and demonstrating that a subset of human adipocytes lacks the β&lt;sub>2&lt;/sub>-adrenergic receptor, particularly in the insulin-resistant state. In conclusion, the present study confers key technological insights for analyzing and sorting mature adipocytes, opening up numerous downstream research applications.</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Sep</publication><modification>2026-06-08T04:04:50.495Z</modification><creation>2019-03-26T23:56:40Z</creation></dates><accession>S-EPMC6137819</accession><cross_references><pubmed>30184507</pubmed><doi>10.1016/j.celrep.2018.08.006</doi></cross_references></HashMap>