Biology subjects

Hether, T.

Publications and source records attributed to Hether, T..

4 recordsLinked to original sources

bioRxiv2022

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

genomics↗

bioRxiv2022

Background modeling, Quality Control and Normalization for GeoMx RNA data with GeoDiff

BackgroundNanoStrings GeoMx Digital Spatial Profiler (DSP) RNA assay can measure mRNA from hundreds of regions of customizable shape and size, yet it gives unique challenge in Quality Control(QC) and normalizating due to the omnipresent background noise incurred by the non-specific probe binding, which could not be addressed by conventional methods. Results and discussionUsing Poisson Background model, Background Score Test, Negative Binomial threshold model and Poisson threshold model for normalization from the R package GeoDiff, we perform tasks including size factor estimation, QC and normalization on GoeMx RNA assay data. They are shown to outperform conventional methods like Limit of Quantification for QC as to consistency/false positive rate and 75% quantile normalization as to eliminating technical variability and recovering true signal. ConclusionsWe present a statistical model based workflow for QC and normalizing GeoMx RNA data using GeoDiff, justified by statistical theory and validated by real/simulated data.

bioinformatics↗

bioRxiv2022

A model of persistent post SARS-CoV-2 induced lung disease for target identification and testing of therapeutic strategies

COVID-19 survivors develop post-acute sequelae of SARS-CoV-2 (PASC), but the mechanistic basis of PASC-associated lung abnormalities suffers from a lack of longitudinal samples. Mouse-adapted SARS-CoV-2 MA10 produces an acute respiratory distress syndrome (ARDS) in mice similar to humans. To investigate PASC pathogenesis, studies of MA10-infected mice were extended from acute disease through clinical recovery. At 15-120 days post-virus clearance, histologic evaluation identified subpleural lesions containing collagen, proliferative fibroblasts, and chronic inflammation with tertiary lymphoid structures. Longitudinal spatial transcriptional profiling identified global reparative and fibrotic pathways dysregulated in diseased regions, similar to human COVID-19. Populations of alveolar intermediate cells, coupled with focal upregulation of pro-fibrotic markers, were identified in persistently diseased regions. Early intervention with antiviral EIDD-2801 reduced chronic disease, and early anti-fibrotic agent (nintedanib) intervention modified early disease severity. This murine model provides opportunities to identify pathways associated with persistent SARS-CoV-2 pulmonary disease and test countermeasures to ameliorate PASC.

microbiology↗

bioRxiv2021

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

microbiology↗