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Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics [visium]

ABSTRACT: Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics [visium]

PROVIDER: PRJNA846745 | ENA |

REPOSITORIES: ENA

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Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics [visium]

Project description:We and others have demonstrated Zika virus (ZIKV) congenital infection evades double-stranded RNA detection, and may persist in the placenta for the duration of pregnancy without accompanying overt histopathologic inflammation. We used orthogonal approaches to test the hypothesis that ZIKV disrupts placental miRNAs to enable viral persistence and fetal pathogenesis. In primary human trophoblasts, high-throughput sequencing crosslinking and immunoprecipitation (AGO-HITS-CLIP) demonstrated an unexpected disruption of placental miRNA-regulated TGF-β networks. In gnotobiotic mice, absence of microbes rendered normally resistant mice susceptible to congenital ZIKV infection, and placental spatial transcriptomics revealed distinct microenvironments defined by significant upregulation of complement cascade components. Finally, treatment of ZIKV-infected mice with the RNAi-enhancer enoxacin led to loss of ZIKV placental persistence and rescue of fetal growth restriction. These results collectively suggest that ZIKV co-opts miRNA inflammatory regulatory networks to persist in the placenta reservoir, a conduit of vertical transmission and fetal pathogenesis.

2023-06-03 | GSE205631 | GEO

Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics [AGO-HITS-CLIP]

2023-06-03 | GSE205609 | GEO

Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics

Project description:Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics

| PRJNA846741 | ENA

Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics [AGO-HITS-CLIP]

Project description:Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics [AGO-HITS-CLIP]

| PRJNA846714 | ENA

Zika virus co-opts miRNA networks to persist in placental microenvironments detected by spatial transcriptomics

Project description:This SuperSeries is composed of the SubSeries listed below.

2023-06-03 | GSE205632 | GEO

A spatial multi-omics atlas of the human lung reveals a novel immune cell survival niche - Visium

Project description:Multiple distinct cell types of the human lung and airways have been defined by single cell RNA sequencing (scRNAseq). Here we present a multi-omics spatial lung atlas to define novel cell types which we map back into the macro- and micro-anatomical tissue context to define functional tissue microenvironments. Firstly, we have generated single cell and nuclei RNA sequencing, VDJ-sequencing and Visium Spatial Transcriptomics data sets from 5 different locations of the human lung and airways. Secondly, we define additional cell types/states, as well as spatially map novel and known human airway cell types, such as adult lung chondrocytes, submucosal gland (SMG) duct cells, distinct pericyte and smooth muscle subtypes, immune-recruiting fibroblasts, peribronchial and perichondrial fibroblasts, peripheral nerve associated fibroblasts and Schwann cells. Finally, we define a survival niche for IgA-secreting plasma cells at the SMG, comprising the newly defined epithelial SMG-Duct cells, and B and T lineage immune cells. Using our transcriptomic data for cell-cell interaction analysis, we propose a signalling circuit that establishes and supports this niche. Overall, we provide a transcriptional and spatial lung atlas with multiple novel cell types that allows for the study of specific tissue microenvironments such as the newly defined gland-associated lymphoid niche (GALN).

2022-01-06 | E-MTAB-11640 | biostudies-arrayexpress

Spatially resolved transcriptomic profiling: an experimental comparison of GeoMx Digital Spatial Profiling and Visium CytAssist spatial transcriptomics in three cancer types (Chromium and Visium)

Project description:We performed Visium CytAssist (10X), GeoMx DSP (Nanostring) and Chromium Flex (10X Genomics) full transcriptome profiling on Breast Cancer (BC), Lung Cancer (LC) and diffuse large B cell lymphoma (DLBCL) samples from archival FFPE blocks. We explore the data quality across blocks with different storage times and DV200 values for all the three methods. We compared the cell type signature purity between ST methods Visium and GeoMx by utilising pathology annotations and scRNAseq. For the Visium and Chromium methods with a large number of data points we explored the heterogeneity between tissues. Finally, we demonstrate the discovery of patient-specific tumor-TME interactions across all three methods.

2024-11-01 | E-MTAB-14560 | biostudies-arrayexpress

Spatial Visium FFPE Samples

Project description:Spatial Visium FFPE Samples

| PRJNA971973 | ENA

Single-cell transcriptional landscape of human embryonic limb development - Visium

Project description:We performed spatial transcriptomic experiments using the 10x Visium assay, generating high-quality transcriptomic profiles for samples from PCW5 to PCW8

2022-04-15 | E-MTAB-10367 | biostudies-arrayexpress

Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples

Project description:We designed a Nextflow DSL2-based pipeline, Spatial Transcriptomics Quantification (STQ), for simultaneous processing of 10x Genomics Visium spatial transcriptomics data and a matched hematoxylin and eosin (H&E)-stained whole slide image (WSI), optimized for Patient-Derived Xenograft (PDX) cancer specimens. Our pipeline enables the classification of sequenced transcripts for deconvolving the mouse and human species and mapping the transcripts to reference transcriptomes. We align the H&E WSI with the spatial layout of the Visium slide and generate imaging and quantitative morphology features for each Visium spot. The pipeline design enables multiple analysis workflows, including single or dual reference genomes input and stand-alone image analysis. We show the utility of our pipeline on a dataset from Visium profiling of four melanoma PDX samples. The clustering of Visium spots and clustering of H&E imaging features reveal similar patterns arising from the two data modalities.

2024-05-21 | GSE238004 | GEO

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