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通过流式细胞术对微生物群落进行单细胞多参数特征分析。

Single-cell multi-parametric characterization of microbiota by flow cytometry.

机构信息

Deutsches Rheuma-Forschungszentrum Berlin, a Leibniz Institute, Berlin, Germany; Institute for Biotechnology, Technische Universität Berlin, Berlin, Germany.

Deutsches Rheuma-Forschungszentrum Berlin, a Leibniz Institute, Berlin, Germany.

出版信息

Methods Cell Biol. 2024;186:91-106. doi: 10.1016/bs.mcb.2024.02.023. Epub 2024 Apr 9.

DOI:10.1016/bs.mcb.2024.02.023
PMID:38705607
Abstract

It has become evident, that the microbes colonizing the human body have a great impact on health and disease. Investigations of microbiota currently primarily rely on culturomics, high-throughput sequencing and metaproteomics which have considerably advanced our knowledge regarding the role of the microbiota in our environment and for our health. While single-cell phenotyping of immune cells and other somatic cells by flow cytometry has become widely used, the detailed analysis of bacterial cells such as the human microbiota on the single-cell level, is lagging behind. Here, we outline a protocol for the single-cell characterization of bacterial cells from complex microbiota samples, such as stool, by multi-parametric flow cytometry. Our protocol describes the isotype-specific detection of host-antibody coating of intestinal bacteria ex vivo, which together with quantitative DNA staining and light scatter detection comprise an individual's microbiota fingerprint. Cryoconservation and appropriate staining controls ensure reliable, reproducible data generation and analysis. We have automated the analysis of the multi-dimensional data using a segmentation approach by self-organizing map (SOM) algorithm for downstream comparative analyses. Our protocol can be adapted to integrate further phenotypic markers and uses the power of analytical cytometry for the characterization of bacteria on the single-cell level.

摘要

很明显,定植于人体的微生物对健康和疾病有着重大影响。目前对微生物组的研究主要依赖于培养组学、高通量测序和代谢蛋白质组学,这些方法极大地提高了我们对微生物组在环境和健康中作用的认识。虽然流式细胞术已广泛用于对免疫细胞和其他体细胞的单细胞表型进行分析,但对人类微生物组等细菌细胞的详细分析仍相对滞后。在这里,我们概述了一种通过多参数流式细胞术对来自复杂微生物组样本(如粪便)中的细菌细胞进行单细胞特征分析的方案。我们的方案描述了对肠道细菌的宿主抗体包被进行同型特异性检测,该检测与定量 DNA 染色和光散射检测相结合,构成了个体的微生物组指纹。冷冻保存和适当的染色对照可确保可靠、可重复的数据生成和分析。我们已经使用自组织映射(SOM)算法的分割方法对多维数据进行了自动化分析,以便进行下游比较分析。我们的方案可以进行修改以整合更多的表型标记,并利用分析型流式细胞术对细菌进行单细胞水平的特征分析。

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Single-cell multi-parametric characterization of microbiota by flow cytometry.通过流式细胞术对微生物群落进行单细胞多参数特征分析。
Methods Cell Biol. 2024;186:91-106. doi: 10.1016/bs.mcb.2024.02.023. Epub 2024 Apr 9.
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High-resolution microbiota flow cytometry reveals dynamic colitis-associated changes in fecal bacterial composition.高分辨率微生物群流式细胞术揭示了粪便细菌组成中与结肠炎相关的动态变化。
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Single-cell genomics for resolution of conserved bacterial genes and mobile genetic elements of the human intestinal microbiota using flow cytometry.利用流式细胞术解析人类肠道微生物群的保守细菌基因和移动遗传元件的单细胞基因组学。
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Are all faecal bacteria detected with equal efficiency? A study using next-generation sequencing and quantitative culture of infants' faecal samples.所有粪便细菌的检测效率都一样吗?一项使用下一代测序和婴儿粪便样本定量培养的研究。
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Translational activity is uncoupled from nucleic acid content in bacterial cells of the human gut microbiota.在人类肠道微生物群的细菌细胞中,翻译活性与核酸含量解耦。
Gut Microbes. 2021 Jan-Dec;13(1):1-15. doi: 10.1080/19490976.2021.1903289.

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Gut Microbes. 2025 Dec;17(1):2452250. doi: 10.1080/19490976.2025.2452250. Epub 2025 Jan 15.
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Age-stratification reveals age-specific intestinal microbiota signatures in juvenile idiopathic arthritis.年龄分层揭示了幼年特发性关节炎中特定年龄的肠道微生物群特征。
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