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整合多重免疫荧光和质谱成像技术,以在代谢和细胞环境中绘制髓系异质性图谱。

Integrating multiplex immunofluorescent and mass spectrometry imaging to map myeloid heterogeneity in its metabolic and cellular context.

机构信息

Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands.

Cardiovascular Research Institute Maastricht, Experimental Vascular Pathology Group, Department of Pathology, Maastricht University Medical Center+, Maastricht, the Netherlands.

出版信息

Cell Metab. 2022 Aug 2;34(8):1214-1225.e6. doi: 10.1016/j.cmet.2022.06.012. Epub 2022 Jul 19.

Abstract

Cells often adopt different phenotypes, dictated by tissue-specific or local signals such as cell-cell and cell-matrix contacts or molecular micro-environment. This holds in extremis for macrophages with their high phenotypic plasticity. Their broad range of functions, some even opposing, reflects their heterogeneity, and a multitude of subsets has been described in different tissues and diseases. Such micro-environmental imprint cannot be adequately studied by single-cell applications, as cells are detached from their context, while histology-based assessment lacks the phenotypic depth due to limitations in marker combination. Here, we present a novel, integrative approach in which 15-color multispectral imaging allows comprehensive cell classification based on multi-marker expression patterns, followed by downstream analysis pipelines to link their phenotypes to contextual, micro-environmental cues, such as their cellular ("community") and metabolic ("local lipidome") niches in complex tissue. The power of this approach is illustrated for myeloid subsets and associated lipid signatures in murine atherosclerotic plaque.

摘要

细胞通常会表现出不同的表型,这些表型由组织特异性或局部信号决定,如细胞-细胞和细胞-基质接触或分子微环境。这种情况在巨噬细胞中表现得尤为极端,它们具有很高的表型可塑性。巨噬细胞具有广泛的功能,其中一些甚至是相互矛盾的,这反映了它们的异质性,并且在不同的组织和疾病中已经描述了多种亚群。这种微环境的印记不能通过单细胞应用充分研究,因为细胞与它们的环境分离,而基于组织学的评估由于标记组合的限制而缺乏表型深度。在这里,我们提出了一种新的综合方法,其中 15 色多光谱成像允许基于多标记表达模式进行全面的细胞分类,然后是下游分析管道,将它们的表型与上下文、微环境线索联系起来,例如它们在复杂组织中的细胞(“群落”)和代谢(“局部脂质组”)生态位。这种方法的强大功能在小鼠动脉粥样硬化斑块中的髓样细胞亚群和相关脂质特征中得到了说明。

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