Biology subjects

Huseynov, A.

Publications and source records attributed to Huseynov, A..

4 recordsLinked to original sources

bioRxiv2025

Geospatially informed representation of spatial genomics data with SpatialFeatureExperiment

SpatialFeatureExperiment is a Bioconductor package that leverages the versatility of Simple Features for spatial data analysis and SpatialExperiment for single-cell -omics to provide an expansive and convenient S4 class for working with spatial -omics data. SpatialFeatureExperiment can be used to store and analyze a variety of spatial -omics data types, including data from the Visium, Xenium, MERFISH, SeqFish, and Slide-seq platforms, bringing spatial operations to the SingleCellExperiment ecosystem.

bioinformatics↗

bioRxiv2024

Comparison of spatial transcriptomics technologies used for tumor cryosections

BackgroundSpatial transcriptomics (ST) technologies are revolutionizing our understanding of intra-tumor heterogeneity and the tumor microenvironment by revealing single-cell molecular profiles within their spatial tissue context. The rapid evolution of ST methods, each with unique features, presents a challenge in selecting the most appropriate technology for specific research objectives. Here, we compare four imaging-based ST methods - RNAscope HiPlex, Molecular Cartography, MERFISH/Merscope, and Xenium - together with sequencing-based ST (Visium). These technologies were used to study cryosections of medulloblastoma with extensive nodularity (MBEN), a tumor chosen for its distinct microanatomical features. ResultsOur analysis reveals that automated imaging-based ST methods are well suited to delineating the intricate MBEN microanatomy, capturing cell-type-specific transcriptome profiles. We devise approaches to compare the sensitivity and specificity of the different methods together with their unique attributes to guide method selection based on the research aim. Furthermore, we demonstrate how reimaging of slides after the ST analysis can markedly improve cell segmentation accuracy and integrate additional transcript and protein readouts to expand the analytical possibilities and depth of insights. ConclusionsThis study highlights key distinctions between various ST technologies and provides a set of parameters for evaluating their performance. Our findings aid in the informed choice of ST methods and delineate approaches for enhancing the resolution and breadth of spatial transcriptomic analyses, thereby contributing to advancing ST applications in solid tumor research.

genomics↗

bioRxiv2023

Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 donor lungs with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage (DAD). We identify changes in cellular composition across progressive DAD, including waves of molecularly distinct macrophages and depleted epithelial and endothelial populations throughout different types of tissue damage. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early DAD, and fibrosis-related collagens in organised DAD. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early DAD. These results provide the first comprehensive, spatially resolved atlas of DAD stages, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways across alveolar damage progression.

pathology↗

bioRxiv2020

Lack of evidence of ACE2 expression and replicative infection by SARS-CoV-2 in human endothelial cells

A striking feature of severe COVID-19 is thrombosis in large as well as small vessels of multiple organs. This has led to the assumption that SARS-CoV-2 virus directly infects and damages the vascular endothelium. However, endothelial expression of ACE2, the cellular receptor for SARS-CoV-2, has not been convincingly demonstrated. Interrogating human bulk and single-cell transcriptomic data, we found ACE2 expression in endothelial cells to be extremely low or absent in vivo and not upregulated by exposure to inflammatory agents in vitro. Also, the endothelial chromatin landscape at the ACE2 locus showed presence of repressive and absence of activation marks, suggesting that the gene is inactive in endothelial cells. Finally, we failed to achieve infection and replication of SARS-CoV-2 in cultured human endothelial cells, which were permissive to productive infection by coronavirus 229E that uses CD13 as the receptor. Our data suggest that SARS-Cov-2 is unlikely to infect endothelial cells directly; these findings are consistent with a scenario where endothelial injury is indirectly caused by the infection of neighbouring epithelial cells and/or due to systemic effects mediated by immune cells, platelets, complement activation, and/or proinflammatory cytokines.

pathology↗