| 1. |
- Carow, Berit, et al.
(author)
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Spatial and temporal localization of immune transcripts defines hallmarks and diversity in the tuberculosis granuloma
- 2019
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
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Journal article (peer-reviewed)abstract
- Granulomas are the pathological hallmark of tuberculosis (TB) and the niche where bacilli can grow and disseminate or the immunological microenvironment in which host cells interact to prevent bacterial dissemination. Here we show 34 immune transcripts align to the morphology of lung sections from Mycobacterium tuberculosis-infected mice at cellular resolution. Colocalizing transcript networks at <10 mu m in C57BL/6 mouse granulomas increase complexity with time after infection. B-cell clusters develop late after infection. Transcripts from activated macrophages are enriched at subcellular distances from M. tuberculosis. Encapsulated C3HeB/FeJ granulomas show necrotic centers with transcripts associated with immunosuppression (Foxp3, Il10), whereas those in the granuloma rims associate with activated T cells and macrophages. We see highly diverse networks with common interactors in similar lesions. Different immune landscapes of M. tuberculosis granulomas depending on the time after infection, the histopathological features of the lesion, and the proximity to bacteria are here defined.
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| 2. |
- Qian, Xiaoyan, et al.
(author)
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Probabilistic cell typing enables fine mapping of closely related cell types in situ
- 2020
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In: Nature Methods. - : Springer Science and Business Media LLC. - 1548-7091 .- 1548-7105. ; 17:1, s. 101-106
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Journal article (peer-reviewed)abstract
- Understanding the function of a tissue requires knowing the spatial organization of its constituent cell types. In the cerebral cortex, single-cell RNA sequencing (scRNA-seq) has revealed the genome-wide expression patterns that define its many, closely related neuronal types, but cannot reveal their spatial arrangement. Here we introduce probabilistic cell typing by in situ sequencing (pciSeq), an approach that leverages prior scRNA-seq classification to identify cell types using multiplexed in situ RNA detection. We applied this method by mapping the inhibitory neurons of mouse hippocampal area CA1, for which ground truth is available from extensive prior work identifying their laminar organization. Our method identified these neuronal classes in a spatial arrangement matching ground truth, and further identified multiple classes of isocortical pyramidal cell in a pattern matching their known organization. This method will allow identifying the spatial organization of closely related cell types across the brain and other tissues.
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