{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T16:01:23Z","timestamp":1790438483003,"version":"4.1.0"},"reference-count":29,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:00:00Z","timestamp":1788480000000},"content-version":"vor","delay-in-days":3,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Current Protocols"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The role of the human microbiota in host health is an important area of research. Conventional characterization of the complex microbial communities colonizing the human body is primarily performed using culture\u2010based or high\u2010throughput sequencing approaches, which have improved general understanding yet lack cellular features relevant for interaction and function at the single\u2010cell level. Flow cytometry is an established tool for single\u2010cell analysis, and recent improvements, such as increased resolution of small cells and particles, offer possibilities for characterizing complex microbial communities. Here, we describe an updated protocol to characterize complex microbial communities derived from human stool samples at the single\u2010cell level by multiparametric microbiota flow cytometry. Our protocol covers the process from the isolation of bacteria from stool, preparation of cryo\u2010stocks, staining procedure for phenotypic features of the bacteria, and flow cytometric analysis. Our phenotypic characterization includes light scattering properties, quantitative DNA staining, isotype\u2010specific staining of host\u2013antibody coating, and profiling of bacterial cell surface sugar moieties. In addition, we highlight the importance of determining the bacterial load for improved biological interpretation. External staining controls ensure reproducibility and quality controls. Additionally, we suggest a downstream analysis pipeline involving segmentation of multivariate data by a self\u2010organized map (SOM) and machine learning to generate specific microbiota fingerprints. Optionally, bacteria with specific phenotypic characteristics can be isolated by fluorescence\u2010activated cell sorting (FACS) for further investigation. Our protocol can be applied to any microbial community or sample source and offers the flexibility to be expanded with additional phenotypic markers. \u00a9 2026 The Author(s).\n                    <jats:italic>Current Protocols<\/jats:italic>\n                    published by Wiley Periodicals LLC.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Basic Protocol 1<\/jats:bold>\n                    : Preparation of cryo\u2010preserved bacterial stocks from a single\u2010cell microbiota suspension derived from native human stool sample\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Basic Protocol 2<\/jats:bold>\n                    : Staining protocol for cryo\u2010preserved microbiota stocks and acquisition using a flow cytometer\n                  <\/jats:p>","DOI":"10.1002\/cpz1.70460","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T15:37:35Z","timestamp":1788536255000},"source":"Crossref","is-referenced-by-count":0,"title":["A Step\u2010by\u2010Step Guide to Successful Multiparametric Microbiota Flow Cytometry"],"prefix":"10.1002","volume":"6","author":[{"given":"Toni","family":"Sempert","sequence":"first","affiliation":[{"name":"German Rheumatology Research Center Berlin \u2013 A Leibniz Institute  Berlin Germany"},{"name":"Department for Cytometry, Institute of Biotechnology Technische Universit\u00e4t Berlin  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisa","family":"Budzinski","sequence":"additional","affiliation":[{"name":"German Rheumatology Research Center Berlin \u2013 A Leibniz Institute  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robin","family":"Kempkens","sequence":"additional","affiliation":[{"name":"German Rheumatology Research Center Berlin \u2013 A Leibniz Institute  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gi\u2010Ung","family":"Kang","sequence":"additional","affiliation":[{"name":"German Rheumatology Research Center Berlin \u2013 A Leibniz Institute  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ren\u00e9","family":"Maier","sequence":"additional","affiliation":[{"name":"German Rheumatology Research Center Berlin \u2013 A Leibniz Institute  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyun\u2010Dong","family":"Chang","sequence":"additional","affiliation":[{"name":"German Rheumatology Research Center Berlin \u2013 A Leibniz Institute  Berlin Germany"},{"name":"Department for Cytometry, Institute of Biotechnology Technische Universit\u00e4t Berlin  Berlin Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,4]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40168\u2010021\u201001206\u20107"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2026.106326"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1080\/19490976.2025.2452250"},{"key":"e_1_2_9_5_1","first-page":"91","volume-title":"Methods in cell biology","author":"Budzinski L.","year":"2024"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40348\u2010024\u201000186\u20106"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/eji.202250337"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41596\u2010020\u20100362\u20100"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/eji.201646632"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1003806"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.2166\/wrd.2025.011"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1021\/es2010682"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471\u20102105\u201010\u2010106"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/1462\u20102920.15310"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41392\u2010022\u201000974\u20104"},{"key":"e_1_2_9_16_1","unstructured":"Kang G.\u2010U.(2025).MicroBiotR: A Comprehensive R Toolkit for SOM\u2010Based Microbiota Flow Cytometry and Downstream Machine Learning[Computer software].https:\/\/github.com\/changlabs\/MicroBiotR"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/elsc.202200025"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1038\/nprot.2012.149"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.3390\/microorganisms12101998"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v028.i05"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.24704"},{"key":"e_1_2_9_22_1","unstructured":"Oksanen J. Simpson G. L. Blanchet F. G. Kindt R. Legendre P. Minchin P. R. O'Hara R. B. Solymos P. Stevens M. H. H. Szoecs E. Wagner H. Barbour M. Bedward M. Bolker B. Borcard D. Borman T. Carvalho G. Chirico M. deCaceres M. \u2026Weedon J.(2024).Vegan: Community ecology package(Version 2.6\u20108) [R package].https:\/\/vegandevs.github.io\/vegan\/"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1111\/2041\u2010210X.12607"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.24910"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41396\u2010020\u201000762\u20104"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1128\/mSphere.00530\u201020"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1080\/19490976.2022.2081475"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature24460"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v021.i05"},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.1002\/eji.201646297"}],"container-title":["Current Protocols"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/currentprotocols.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpz1.70460","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/currentprotocols.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/cpz1.70460","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/currentprotocols.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpz1.70460","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T15:55:07Z","timestamp":1790438107000},"score":1,"resource":{"primary":{"URL":"https:\/\/currentprotocols.onlinelibrary.wiley.com\/doi\/10.1002\/cpz1.70460"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":29,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["10.1002\/cpz1.70460"],"URL":"https:\/\/doi.org\/10.1002\/cpz1.70460","archive":["Portico"],"relation":{},"ISSN":["2691-1299","2691-1299"],"issn-type":[{"value":"2691-1299","type":"print"},{"value":"2691-1299","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9]]},"article-number":"e70460"}}