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通过循环多重标记对单细胞蛋白质组学研究中单免疫细胞中的>400 个分化簇生物标志物和途径蛋白进行检测。

Detection of >400 Cluster of Differentiation Biomarkers and Pathway Proteins in Single Immune Cells by Cyclic Multiplex Tagging for Single-Cell Proteomic Studies.

机构信息

Multiplex Biotechnology Laboratory, Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York 11794, United States.

Institute for Systems Biology, Seattle, Washington 98109, United States.

出版信息

Anal Chem. 2024 Oct 29;96(43):17387-17395. doi: 10.1021/acs.analchem.4c04239. Epub 2024 Oct 18.

DOI:10.1021/acs.analchem.4c04239
PMID:39422499
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11648578/
Abstract

The identification and characterization of immune cell subpopulations are critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced single-cell genomics and transcriptomics for immune cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in protein format. Current single-cell proteomic technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein, we present a single-cell cyclic multiplex tagging (CycMIST) technology to simultaneously measure >400 proteins, a scale of >10 times than similar technologies. Such an ultrahigh multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both peripheral blood mononuclear cells (PBMCs) and T cells are analyzed by the CycMIST technology, and almost the entire spectrum of cluster of differentiation (CD) surface markers has been measured. The landscape of fluctuation of CD protein expression in single cells has been uncovered by our technology. Further study found T cell activation signatures and protein-protein networks. This study represents the highest multiplexity of single immune cell marker measurement targeting functional proteins. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses under various disease conditions.

摘要

鉴定和描述免疫细胞亚群对于揭示细胞在整个生命周期中的发育以及对环境因素的免疫反应至关重要。下一代测序技术极大地推动了免疫细胞分类的单细胞基因组学和转录组学研究。然而,基因表达通常与蛋白质表达不相关,免疫分型大多以蛋白质形式被接受。目前的单细胞蛋白质组学技术要么在多重容量上受到限制,要么不够灵敏,无法检测到关键的功能蛋白。在这里,我们提出了一种单细胞循环多重标记(CycMIST)技术,可以同时测量超过 400 种蛋白质,这一规模比类似技术高出 10 倍以上。这种超高的多重性是通过反复染色单个细胞并结合 MIST 阵列进行检测来实现的。该技术已通过与流式细胞术和荧光免疫染色技术的比较得到了充分验证。通过 CycMIST 技术分析外周血单核细胞(PBMC)和 T 细胞,几乎可以测量到整个分化簇(CD)表面标志物谱。我们的技术揭示了单个细胞中 CD 蛋白表达波动的全貌。进一步的研究发现了 T 细胞激活特征和蛋白质-蛋白质网络。这项研究代表了针对功能蛋白的单个免疫细胞标志物测量的最高多重性。通过同一单细胞的细胞内蛋白质的附加信息,我们的技术可以潜在地促进在各种疾病状态下对免疫反应的机制研究。

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本文引用的文献

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Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell.单细胞蛋白质组分析可定量检测哺乳动物细胞中多达 3000 种蛋白质。
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Single-cell analysis targeting the proteome.针对蛋白质组的单细胞分析。
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Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics.优先质谱分析提高了单细胞蛋白质组学的深度、灵敏度和数据完整性。
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Cyclic microchip assay for measurement of hundreds of functional proteins in single neurons.循环微芯片分析测定单个神经元中的数百种功能蛋白。
Nat Commun. 2022 Jun 21;13(1):3548. doi: 10.1038/s41467-022-31336-x.
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Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell.超灵敏单细胞蛋白质组学工作流程可识别每个哺乳动物细胞中超过1000个蛋白质组。
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Quantitative single-cell proteomics as a tool to characterize cellular hierarchies.定量单细胞蛋白质组学作为一种表征细胞层次结构的工具。
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Single-cell RNA sequencing reveals the sustained immune cell dysfunction in the pathogenesis of sepsis secondary to bacterial pneumonia.单细胞RNA测序揭示了细菌性肺炎继发脓毒症发病机制中持续存在的免疫细胞功能障碍。
Genomics. 2021 May;113(3):1219-1233. doi: 10.1016/j.ygeno.2021.01.026. Epub 2021 Mar 7.
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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2.单细胞蛋白质组学和转录组学分析使用 SCoPE2 分析巨噬细胞异质性。
Genome Biol. 2021 Jan 27;22(1):50. doi: 10.1186/s13059-021-02267-5.
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CD57 Memory T Cells Proliferate In Vivo.CD57 记忆 T 细胞在体内增殖。
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Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19.多组学解析轻度和中度 COVID-19 之间明显的疾病状态转变。
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