Evidence map›Paper›PMID 42696306›Full record

ArticleCurrent protocols2026

A Step-by-Step Guide to Successful Multiparametric Microbiota Flow Cytometry.

Toni Sempert, Lisa Budzinski, Robin Kempkens, Gi-Ung Kang, René Maier, Hyun-Dong Chang

Abstract read
In one paragraph

Article in Current protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Toni SempertGerman Rheumatology Research Center Berlin - A Leibniz Institute, Berlin, Germany.
Lisa BudzinskiGerman Rheumatology Research Center Berlin - A Leibniz Institute, Berlin, Germany.
Robin KempkensGerman Rheumatology Research Center Berlin - A Leibniz Institute, Berlin, Germany.
Gi-Ung KangGerman Rheumatology Research Center Berlin - A Leibniz Institute, Berlin, Germany.
René MaierGerman Rheumatology Research Center Berlin - A Leibniz Institute, Berlin, Germany.
Hyun-Dong ChangGerman Rheumatology Research Center Berlin - A Leibniz Institute, Berlin, Germany.

Funding

Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) 375876048Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) 491069896Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) 565743763EFRE-Project grant 1.6./01"BacFlow-AnalysebakteriellerGemeinschaftendurchMikrobiota-Zytometrie"Innovative Medicines Initiative 2 Joint Undertaking 831434Rolf M. Schwiete Foundation
6 · The paper itself

Abstract

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-based or high-throughput sequencing approaches, which have improved general understanding yet lack cellular features relevant for interaction and function at the single-cell level. Flow cytometry is an established tool for single-cell 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-cell level by multiparametric microbiota flow cytometry. Our protocol covers the process from the isolation of bacteria from stool, preparation of cryo-stocks, staining procedure for phenotypic features of the bacteria, and flow cytometric analysis. Our phenotypic characterization includes light scattering properties, quantitative DNA staining, isotype-specific staining of host-antibody 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-organized map (SOM) and machine learning to generate specific microbiota fingerprints. Optionally, bacteria with specific phenotypic characteristics can be isolated by fluorescence-activated 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. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of cryo-preserved bacterial stocks from a single-cell microbiota suspension derived from native human stool sample Basic Protocol 2: Staining protocol for cryo-preserved microbiota stocks and acquisition using a flow cytometer.

Indexed as

BacteriaFlow CytometryMicrobiotaFecesHumansSingle-Cell Analysishost–microbiota interactionsmicrobiomemicrobiota phenotypingmultiparametric flow cytometry

Identifiers

PMID42696306
PMCPMC13544355

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