Imaging the Architecture of Granulomas Induced by Mycobacterium tuberculosis Infection with Single-molecule Fluorescence In Situ Hybridization

原位杂交 生物 结核分枝杆菌 荧光原位杂交 免疫荧光 免疫系统 背景(考古学) 肺结核 转录组 信使核糖核酸 病理 细胞生物学 分子生物学 基因表达 免疫学 抗体 基因 遗传学 医学 古生物学 染色体
作者
Ranjeet Kumar,Afsal Kolloli,Selvakumar Subbian,Deepak Kaushal,Lanbo Shi,Sanjay Tyagi
出处
期刊:Journal of Immunology [American Association of Immunologists]
标识
DOI:10.4049/jimmunol.2300068
摘要

Abstract Granulomas are an important hallmark of Mycobacterium tuberculosis infection. They are organized and dynamic structures created when immune cells assemble around the sites of infection in the lungs that locally restrict M. tuberculosis growth and the host’s inflammatory responses. The cellular architecture of granulomas is traditionally studied by immunofluorescence labeling of surface markers on the host cells. However, very few Abs are available for model animals used in tuberculosis research, such as nonhuman primates and rabbits, and secreted immunological markers such as cytokines cannot be imaged in situ using Abs. Furthermore, traditional phenotypic surface markers do not provide sufficient resolution for the detection of the many subtypes and differentiation states of immune cells. Using single-molecule fluorescence in situ hybridization (smFISH) and its derivatives, amplified smFISH and iterative smFISH, we developed a platform for imaging mRNAs encoding immune markers in rabbit and macaque tuberculosis granulomas. Multiplexed imaging for several mRNA and protein markers was followed by quantitative measurement of the expression of these markers in single cells. An analysis of the combinatorial expressions of these markers allowed us to classify the cells into several subtypes, and to chart their densities within granulomas. For one mRNA target, hypoxia-inducible factor-1α, we imaged its mRNA and protein in the same cells, demonstrating the specificity of the probes. This method paves the way for defining granular differentiation states and cell subtypes from transcriptomic data, identifying key mRNA markers for these cell subtypes, and then locating the cells in the spatial context of granulomas.
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