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利用细胞金属组和免疫质谱成像进行多参数组织表征

Multiparametric Tissue Characterization Utilizing the Cellular Metallome and Immuno-Mass Spectrometry Imaging.

作者信息

Schaier Martin, Theiner Sarah, Baier Dina, Braun Gabriel, Berger Walter, Koellensperger Gunda

机构信息

Institute of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Strasse 38, Vienna 1090, Austria.

Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Waehringer Strasse 42, Vienna 1090, Austria.

出版信息

JACS Au. 2023 Feb 8;3(2):419-428. doi: 10.1021/jacsau.2c00571. eCollection 2023 Feb 27.

DOI:10.1021/jacsau.2c00571
PMID:36873697
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9975846/
Abstract

In this study, we present a workflow that enables spatial single-cell metallomics in tissue decoding the cellular heterogeneity. Low-dispersion laser ablation in combination with inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOFMS) provides mapping of endogenous elements with cellular resolution at unprecedented speed. Capturing the heterogeneity of the cellular population by metals only is of limited use as the cell type, functionality, and cell state remain elusive. Therefore, we expanded the toolbox of single-cell metallomics by integrating the concepts of imaging mass cytometry (IMC). This multiparametric assay successfully utilizes metal-labeled antibodies for cellular tissue profiling. One important challenge is the need to preserve the original metallome in the sample upon immunostaining. Therefore, we studied the impact of extensive labeling on the obtained endogenous cellular ionome data by quantifying elemental levels in consecutive tissue sections (with and without immunostaining) and correlating elements with structural markers and histological features. Our experiments showed that the elemental tissue distribution remained intact for selected elements such as sodium, phosphorus, and iron, while absolute quantification was precluded. We hypothesize that this integrated assay not only advances single-cell metallomics (enabling to link metal accumulation to multi-dimensional characterization of cells/cell populations), but in turn also enhances selectivity in IMC, as in selected cases, labeling strategies can be validated by elemental data. We showcase the power of this integrated single-cell toolbox using an in vivo tumor model in mice and provide mapping of the sodium and iron homeostasis as linked to different cell types and function in mouse organs (such as spleen, kidney, and liver). Phosphorus distribution maps added structural information, paralleled by the DNA intercalator visualizing the cellular nuclei. Overall, iron imaging was the most relevant addition to IMC. In tumor samples, for example, iron-rich regions correlated with high proliferation and/or located blood vessels, which are key for potential drug delivery.

摘要

在本研究中,我们提出了一种工作流程,可在组织中实现空间单细胞金属组学分析,从而解码细胞异质性。低分散激光烧蚀与电感耦合等离子体飞行时间质谱(LA-ICP-TOFMS)相结合,以前所未有的速度提供了具有细胞分辨率的内源性元素图谱。仅通过金属来捕捉细胞群体的异质性用途有限,因为细胞类型、功能和细胞状态仍难以确定。因此,我们通过整合成像质谱流式细胞术(IMC)的概念,扩展了单细胞金属组学的工具集。这种多参数分析成功地利用金属标记抗体进行细胞组织分析。一个重要的挑战是在免疫染色后需要保留样品中的原始金属组。因此,我们通过量化连续组织切片(有和没有免疫染色)中的元素水平,并将元素与结构标记和组织学特征相关联,研究了广泛标记对获得的内源性细胞离子组数据的影响。我们的实验表明,钠、磷和铁等选定元素的元素组织分布保持完整,而绝对定量则无法进行。我们假设这种综合分析不仅推动了单细胞金属组学的发展(能够将金属积累与细胞/细胞群体的多维特征联系起来),而且反过来还提高了IMC的选择性,因为在某些情况下,标记策略可以通过元素数据进行验证。我们使用小鼠体内肿瘤模型展示了这种集成单细胞工具集的强大功能,并提供了与小鼠器官(如脾脏、肾脏和肝脏)中不同细胞类型和功能相关的钠和铁稳态图谱。磷分布图增加了结构信息,同时DNA嵌入剂可视化了细胞核。总体而言,铁成像对IMC来说是最相关的补充。例如,在肿瘤样本中,富含铁的区域与高增殖和/或定位的血管相关,而血管是潜在药物递送的关键。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/04e362cea4e1/au2c00571_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/31ecd29a9542/au2c00571_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/4608a20ddb55/au2c00571_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/e51ff509e9fd/au2c00571_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/513d775f2598/au2c00571_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/0799df97f08e/au2c00571_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/b224da3787e1/au2c00571_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/04e362cea4e1/au2c00571_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/31ecd29a9542/au2c00571_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/4608a20ddb55/au2c00571_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/e51ff509e9fd/au2c00571_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/513d775f2598/au2c00571_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/0799df97f08e/au2c00571_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/b224da3787e1/au2c00571_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eef/9975846/04e362cea4e1/au2c00571_0008.jpg

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