Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection.

Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.

Transcription Factor Driven Gene Regulation in COVID-19 Patients.

SARS-CoV-2 and its many variants have caused a worldwide emergency. Host cells colonised by SARS-CoV-2 present a significantly different gene expression landscape. As expected, this is particularly true for genes that directly interact with virus proteins. Thus, understanding the role that transcription factors can play in driving differential regulation in patients affected by COVID-19 is a focal point to unveil virus infection. In this regard, we have identified 19 transcription factors which are predicted to target human proteins interacting with Spike glycoprotein of SARS-CoV-2. Transcriptomics RNA-Seq data derived from 13 human organs are used to analyse expression correlation between identified transcription factors and related target genes in both COVID-19 patients and healthy individuals. This resulted in the identification of transcription factors showing the most relevant impact in terms of most evident differential correlation between COVID-19 patients and healthy individuals. This analysis has also identified five organs such as the blood, heart, lung, nasopharynx and respiratory tract in which a major effect of differential regulation mediated by transcription factors is observed. These organs are also known to be affected by COVID-19, thereby providing consistency to our analysis. Furthermore, 31 key human genes differentially regulated by the transcription factors in the five organs are identified and the corresponding KEGG pathways and GO enrichment are also reported. Finally, the drugs targeting those 31 genes are also put forth. This in silico study explores the effects of transcription factors on human genes interacting with Spike glycoprotein of SARS-CoV-2 and intends to provide new insights to inhibit the virus infection.

Classification of tuberculosis-related programmed cell death-related patient subgroups and associated immune cell profiling.

Background: Tuberculosis (TB) is the deadliest communicable disease in the world with the exception of the ongoing COVID-19 pandemic. Programmed cell death (PCD) patterns play key roles in the development and progression of many disease states such that they may offer value as effective biomarkers or therapeutic targets that can aid in identifying and treating TB patients. Materials and methods: The Gene Expression Omnibus (GEO) was used to gather TB-related datasets after which immune cell profiles in these data were analyzed to examine the potential TB-related loss of immune homeostasis. Profiling of differentially expressed PCD-related genes was performed, after which candidate hub PCD-associated genes were selected via a machine learning approach. TB patients were then stratified into two subsets based on the expression of PCD-related genes via consensus clustering. The potential roles of these PCD-associated genes in other TB-related diseases were further examined. Results: In total, 14 PCD-related differentially expressed genes (DEGs) were identified and highly expressed in TB patient samples and significantly correlated with the abundance of many immune cell types. Machine learning algorithms enabled the selection of seven hub PCD-related genes that were used to establish PCD-associated patient subgroups, followed by the validation of these subgroups in independent datasets. These findings, together with GSVA results, indicated that immune-related pathways were significantly enriched in TB patients exhibiting high levels of PCD-related gene expression, whereas metabolic pathways were significantly enriched in the other patient group. Single cell RNA-seq (scRNA-seq) further highlighted significant differences in the immune status of these different TB patient samples. Furthermore, we used CMap to predict five potential drugs for TB-related diseases. Conclusion: These results highlight clear enrichment of PCD-related gene expression in TB patients and suggest that this PCD activity is closely associated with immune cell abundance. This thus indicates that PCD may play a role in TB progression through the induction or dysregulation of an immune response. These findings provide a foundation for further research aimed at clarifying the molecular drivers of TB, the selection of appropriate diagnostic biomarkers, and the design of novel therapeutic interventions aimed at treating this deadly infectious disease.

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19.

Background: The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information. Methods: Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD. Results: The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-ß) signalling. Conclusions: Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.

Antifungal Activity and Potential Action Mechanism of Allicin against Trichosporon asahii.

Trichosporon asahii is an emerging opportunistic pathogen that causes potentially fatal disseminated trichosporonosis. The global prevalence of coronavirus disease 2019 (COVID-19) poses an increasing fungal infection burden caused by T. asahii. Allicin is the main biologically active component with broad-spectrum antimicrobial activity in garlic. In this study, we performed an in-depth analysis of the antifungal characteristics of allicin against T. asahii based on physiological, cytological, and transcriptomic assessments. In vitro, allicin inhibited the growth of T. asahii planktonic cells and biofilm cells significantly. In vivo, allicin improved the mean survival time of mice with systemic trichosporonosis and reduced tissue fungal burden. Electron microscopy observations clearly demonstrated damage to T. asahii cell morphology and ultrastructure caused by allicin. Furthermore, allicin increased intracellular reactive oxygen species (ROS) accumulation, leading to oxidative stress damage in T. asahii cells. Transcriptome analysis showed that allicin treatment disturbed the biosynthesis of cell membrane and cell wall, glucose catabolism, and oxidative stress. The overexpression of multiple antioxidant enzymes and transporters may also place an additional burden on cells, causing them to collapse. Our findings shed new light on the potential of allicin as an alternative treatment strategy for trichosporonosis. IMPORTANCE Systemic infection caused by T. asahii has recently been recognized as an important cause of mortality in hospitalized COVID-19 patients. Invasive trichosporonosis remains a significant challenge for clinicians, due to the limited therapeutic options. The present work suggests that allicin holds great potential as a therapeutic candidate for T. asahii infection. Allicin demonstrated potent in vitro antifungal activity and potential in vivo protective effects. In addition, transcriptome sequencing provided valuable insights into the antifungal effects of allicin.

Genomic Tools in Clinical Epidemiology

The advent of high-throughput technologies, including next-generation sequencing (NGSs), is currently revolutionizing our understanding of several aspects in biological and medical sciences. Particularly, genomic, transcriptomic, epigenomic, and interactomic studies are having a profound impact on the progress of clinical epidemiology. This science is improving public health practices by linking the knowledge from the etiology, distribution, and risk factors during the appearance and progress of infectious and chronic diseases. In this sense, genomic tools have been incorporated in epidemiological studies for the identification of rare genetic variants, genetic and environmental risk factors, and accurate biomarkers for the diagnosis and treatment of several diseases. In this chapter, we aim to highlight the influence that genomics is having on different epidemiological traits by illustrating some examples about the control of the COVID-19 pandemic and the diagnoses, screening, and treatment of chronic diseases such as the infection caused by Helicobacter pylori, cancer, and rheumatoid arthritis. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Single-cell sequencing of PBMC characterizes the altered transcriptomic landscape of classical monocytes in BNT162b2-induced myocarditis.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been the most dangerous threat to public health worldwide for the last few years, which led to the development of the novel mRNA vaccine (BNT162b2). However, BNT162b2 vaccination is known to be associated with myocarditis. Here, as an attempt to determine the pathogenesis of the disease and to develop biomarkers to determine whether subjects likely proceed to myocarditis after vaccination, we conducted a time series analysis of peripheral blood mononuclear cells of a patient with BNT162b2-induced myocarditis. Single-cell RNA sequence analysis identified monocytes as the cell clusters with the most dynamic changes. To identify distinct gene expression signatures, we compared monocytes of BNT162b2-induced myocarditis with monocytes under various conditions, including SARS-CoV-2 infection, BNT162b2 vaccination, and Kawasaki disease, a disease similar to myocarditis. Representative changes in the transcriptomic profile of classical monocytes include the upregulation of genes related to fatty acid metabolism and downregulation of transcription factor AP-1 activity. This study provides, for the first time, the importance of classical monocytes in the pathogenesis of myocarditis following BNT162b2 vaccination and presents the possibility that vaccination affects monocytes, further inducing their differentiation and infiltration into the heart.

Transcriptome in Human Mycoses

Mycoses are infectious diseases caused by fungi, which incidence has increased in recent decades due to the increasing number of immunocompromised patients and improved diagnostic tests. As eukaryotes, fungi share many similarities with human cells, making it difficult to design drugs without side effects. Commercially available drugs act on a limited number of targets and have been reported fungal resistance to commonly used antifungal drugs. Therefore, elucidating the pathogenesis of fungal infections, the fungal strategies to overcome the hostile environment of the host, and the action of antifungal drugs is essential for developing new therapeutic approaches and diagnostic tests. Large-scale transcriptional analyses using microarrays and RNA sequencing (RNA-seq), combined with improvements in molecular biology techniques, have improved the study of fungal pathogenicity. Such techniques have provided insights into the infective process by identifying molecular strategies used by the host and pathogen during the course of human mycoses. This chapter will explore the latest discoveries regarding the transcriptome of major human fungal pathogens. Further we will highlight genes essential for host–pathogen interactions, immune response, invasion, infection, antifungal drug response, and resistance. Finally, we will discuss their importance to the discovery of new molecular targets for antifungal drugs. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2014, 2022.

Upper Respiratory Infection Drives Clinical Signs and Inflammatory Responses Following Heterologous Challenge of SARS-CoV-2 Variants of Concern in K18 Mice.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the emergence of several variants of concern (VOC) with increased immune evasion and transmissibility. This has motivated studies to assess protection conferred by earlier strains following infection or vaccination to each new VOC. We hypothesized that while NAbs play a major role in protection against infection and disease, a heterologous reinfection or challenge may gain a foothold in the upper respiratory tract (URT) and result in a self-limited viral infection accompanied by an inflammatory response. To test this hypothesis, we infected K18-hACE2 mice with SARS-CoV-2 USA-WA1/2020 (WA1) and, after 24 days, challenged with WA1, Alpha, or Delta. While NAb titers against each virus were similar across all cohorts prior to challenge, the mice challenged with Alpha and Delta showed weight loss and upregulation of proinflammatory cytokines in the URT and lower RT (LRT). Mice challenged with WA1 showed complete protection. We noted increased levels of viral RNA transcripts only in the URT of mice challenged with Alpha and Delta. In conclusion, our results suggested self-limiting breakthrough infections of Alpha or Delta in the URT, which correlated with clinical signs and a significant inflammatory response in mice.

Discovery and Genome Characterization of a Closterovirus from Wheat Plants with Yellowing Leaf Symptoms in Japan.

Many aphid-borne viruses are important pathogens that affect wheat crops worldwide. An aphid-transmitted closterovirus named wheat yellow leaf virus (WYLV) was found to have infected wheat plants in Japan in the 1970s; however, since then, its viral genome sequence and occurrence in the field have not been investigated. We observed yellowing leaves in the 2018/2019 winter wheat-growing season in an experimental field in Japan where WYLV was detected five decades ago. A virome analysis of those yellow leaf samples lead to the discovery of a closterovirus together with a luteovirus (barley yellow dwarf virus PAV variant IIIa). The complete genomic sequence of this closterovirus, named wheat closterovirus 1 isolate WL19a (WhCV1-WL19a), consisted of 15,452 nucleotides harboring nine open reading frames. Additionally, we identified another WhCV1 isolate, WL20, in a wheat sample from the winter wheat-growing season of 2019/2020. A transmission test indicated that WhCV1-WL20 was able to form typical filamentous particles and transmissible by oat bird-cherry aphid (Rhopalosiphum pad). Sequence and phylogenetic analyses showed that WhCV1 was distantly related to members of the genus Closterovirus (family Closteroviridae), suggesting that the virus represents a novel species in the genus. Furthermore, the characterization of WhCV1-WL19a-derived small RNAs using high-throughput sequencing revealed highly abundant 22-nt-class small RNAs potentially derived from the 3'-terminal end of the WhCV1 negative-strand genomic RNA, indicating that this terminal end of the WhCV1 genome is likely particularly targeted for the synthesis of viral small RNAs in wheat plants. Our results provide further knowledge on closterovirus diversity and pathogenicity and suggest that the impact of WhCV1 on wheat production warrants further investigations.

Analysing transcriptomic signatures and identifying potential genes for the protective effect of inactivated COVID-19 vaccines.

Inactivated vaccines are one of the most effective strategies for controlling the coronavirus disease 2019 (COVID-19) pandemic. However, the response genes for the protective effect of inactivated vaccines are still unclear. Herein, we analysed the neutralization antibody responses elicited by vaccine serum and carried out transcriptome sequencing of RNAs isolated from the PBMCs of 29 medical staff receiving two doses of the CoronaVac vaccine. The results showed that SARS-CoV-2 neutralization antibody titers varied considerably among individuals, and revealed that many innate immune pathways were activated after vaccination. Furthermore, the blue module revealed that NRAS, YWHAB, SMARCA5, PPP1CC and CDC5L may be correlated with the protective effect of the inactivated vaccine. Additionally, MAPK1, CDC42, PPP2CA, EP300, YWHAZ and NRAS were demonstrated as the hub genes having a significant association with vaccines. These findings provide a basis for understanding the molecular mechanism of the host immune response induced by inactivated vaccines.

IR-ER- A Hybrid Pipeline for Classifying COVID-19 RNA Seq Data

Bioinformatics has numerous approaches for evaluating the similarities between RNA-seq data for disease classification. Processing RNA-sequencing (RNA-seq) data using clustering or classification approach is extremely challenging, although analysis of ribonucleic acid (RNA-Seq) helps understand differentially expressed genes and classify the patient in a risk-free method. In this study, we present a hybrid end-to-end pipeline for analyzing, processing, and classifying the RNA-Seq data with a major focus on the covid-19 data set. The pipeline has been developed in three phases initially the raw data is normalized. Then the normalized data is pushed to a colonization algorithm to remove the noise data. The optimized data set is passed to a Deep Learning (DL) classifier. Further, a comparative analysis is performed with state of art methods discussed in the literature. The results prove that our proposed hybrid pipeline achieved the best accuracy over other methods. Gene set enrichment analysis was also performed to analyze the genes that are informative towards COVID-19 identification. © 2023 ACM.

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens.

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

Single-cell RNA-seq analysis identifies distinct myeloid cells in a case with encephalitis temporally associated with COVID-19 vaccination.

Recently accumulating evidence has highlighted the rare occurrence of COVID-19 vaccination-induced inflammation in the central nervous system. However, the precise information on immune dysregulation related to the COVID-19 vaccination-associated autoimmunity remains elusive. Here we report a case of encephalitis temporally associated with COVID-19 vaccination, where single-cell RNA sequencing (scRNA-seq) analysis was applied to elucidate the distinct immune signature in the peripheral immune system. Peripheral blood mononuclear cells (PBMCs) were analyzed using scRNA-seq to clarify the cellular components of the patients in the acute and remission phases of the disease. The data obtained were compared to those acquired from a healthy cohort. The scRNA-seq analysis identified a distinct myeloid cell population in PBMCs during the acute phase of encephalitis. This specific myeloid population was detected neither in the remission phase of the disease nor in the healthy cohort. Our findings illustrate induction of a unique myeloid subset in encephalitis temporally associated with COVID-19 vaccination. Further research into the dysregulated immune signature of COVID-19 vaccination-associated autoimmunity including the cerebrospinal fluid (CSF) cells of central nervous system (CNS) is warranted to clarify the pathogenic role of the myeloid subset observed in our study.

SARS-CoV-2 infection of airway organoids reveals conserved use of Tetraspanin-8 by Ancestral, Delta, and Omicron variants.

Ancestral SARS coronavirus-2 (SARS-CoV-2) and variants of concern (VOC) caused a global pandemic with a spectrum of disease severity. The mechanistic explaining variations related to airway epithelium are relatively understudied. Here, we biobanked airway organoids (AO) by preserving stem cell function. We optimized viral infection with H1N1/PR8 and comprehensively characterized epithelial responses to SARS-CoV-2 infection in phenotypically stable AO from 20 different subjects. We discovered Tetraspanin-8 (TSPAN8) as a facilitator of SARS-CoV-2 infection. TSPAN8 facilitates SARS-CoV-2 infection rates independently of ACE2-Spike interaction. In head-to-head comparisons with Ancestral SARS-CoV-2, Delta and Omicron VOC displayed lower overall infection rates of AO but triggered changes in epithelial response. All variants shared highest tropism for ciliated and goblet cells. TSPAN8-blocking antibodies diminish SARS-CoV-2 infection and may spur novel avenues for COVID-19 therapy.

Differential haplotype expression in class I MHC genes during SARS-CoV-2 infection of human lung cell lines.

Introduction: Cell entry of SARS-CoV-2 causes genome-wide disruption of the transcriptional profiles of genes and biological pathways involved in the pathogenesis of COVID-19. Expression allelic imbalance is characterized by a deviation from the Mendelian expected 1:1 expression ratio and is an important source of allele-specific heterogeneity. Expression allelic imbalance can be measured by allele-specific expression analysis (ASE) across heterozygous informative expressed single nucleotide variants (eSNVs). ASE reflects many regulatory biological phenomena that can be assessed by combining genome and transcriptome information. ASE contributes to the interindividual variability associated with the disease. We aim to estimate the transcriptome-wide impact of SARS-CoV-2 infection by analyzing eSNVs. Methods: We compared ASE profiles in the human lung cell lines Calu-3, A459, and H522 before and after infection with SARS-CoV-2 using RNA-Seq experiments. Results: We identified 34 differential ASE (DASE) sites in 13 genes (HLA-A, HLA-B, HLA-C, BRD2, EHD2, GFM2, GSPT1, HAVCR1, MAT2A, NQO2, SUPT6H, TNFRSF11A, UMPS), all of which are enriched in protein binding functions and play a role in COVID-19. Most DASE sites were assigned to the MHC class I locus and were predominantly upregulated upon infection. DASE sites in the MHC class I locus also occur in iPSC-derived airway epithelium basal cells infected with SARS-CoV-2. Using an RNA-Seq haplotype reconstruction approach, we found DASE sites and adjacent eSNVs in phase (i.e., predicted on the same DNA strand), demonstrating differential haplotype expression upon infection. We found a bias towards the expression of the HLA alleles with a higher binding affinity to SARS-CoV-2 epitopes. Discussion: Independent of gene expression compensation, SARS-CoV-2 infection of human lung cell lines induces transcriptional allelic switching at the MHC loci. This suggests a response mechanism to SARS-CoV-2 infection that swaps HLA alleles with poor epitope binding affinity, an expectation supported by publicly available proteome data.

Early Transcriptional Responses of Human Nasal Epithelial Cells to Infection with Influenza A and SARS-CoV-2 Virus Differ and Are Influenced by Physiological Temperature.

Influenza A (IAV) and SARS-CoV-2 (SCV2) viruses represent an ongoing threat to public health. Both viruses target the respiratory tract, which consists of a gradient of cell types, receptor expression, and temperature. Environmental temperature has been an understudied contributor to infection susceptibility and understanding its impact on host responses to infection could help uncover new insight into severe disease risk factors. As the nasal passageways are the initial site of respiratory virus infection, in this study we investigated the effect of temperature on host responses in human nasal epithelial cells (hNECs) utilizing IAV and SCV2 in vitro infection models. We demonstrate that temperature affected SCV2, but not IAV, viral replicative fitness and that SCV2-infected cultures were slower to mount an infection-induced response, likely due to suppression by the virus. Additionally, we show that that temperature not only changed the basal transcriptomic landscape of epithelial cells, but that it also impacted the response to infection. The induction of interferon and other innate immune responses was not drastically affected by temperature, suggesting that while the baseline antiviral response at different temperatures remained consistent, there may be metabolic or signaling changes that affect how well the cultures were able to adapt to new pressures, such as infection. Finally, we show that hNECs responded differently to IAV and SCV2 infection in ways that give insight into how the virus is able to manipulate the cell to allow for replication and release. Taken together, these data give new insight into the innate immune response to respiratory infections and can assist in identifying new treatment strategies for respiratory infections.

Time-course RNA-Seq profiling reveals isoform-level gene expression dynamics of the cGAS-STING pathway.

The cGAS-STING pathway, orchestrating complicated transcriptome-wide immune responses, is essential for host antiviral defense but can also drive immunopathology in severe COVID-19. Here, we performed time-course RNA-Seq experiments to dissect the transcriptome expression dynamics at the gene-isoform level after cGAS-STING pathway activation. The in-depth time-course transcriptome after cGAS-STING pathway activation within 12 h enabled quantification of 48,685 gene isoforms. By employing regression models, we obtained 13,232 gene isoforms with expression patterns significantly associated with the process of cGAS-STING pathway activation, which were named activation-associated isoforms. The combination of hierarchical and k-means clustering algorithms revealed four major expression patterns of activation-associated isoforms, including two clusters with increased expression patterns enriched in cell cycle, autophagy, antiviral innate-immune functions, and COVID-19 coronavirus disease pathway, and two clusters showing decreased expression pattern that mainly involved in ncRNA metabolism, translation process, and mRNA processing. Importantly, by merging four clusters of activation-associated isoforms, we identified three types of genes that underwent isoform usage alteration during the cGAS-STING pathway activation. We further found that genes exhibiting protein-coding and non-protein-coding gene isoform usage alteration were strongly enriched for the factors involved in innate immunity and RNA splicing. Notably, overexpression of an enriched splicing factor, EFTUD2, shifted transcriptome towards the cGAS-STING pathway activated status and promoted protein-coding isoform abundance of several key regulators of the cGAS-STING pathway. Taken together, our results revealed the isoform-level gene expression dynamics of the cGAS-STING pathway and uncovered novel roles of splicing factors in regulating cGAS-STING pathway mediated immune responses.

The pulmonary vasculature in lethal COVID-19 and idiopathic pulmonary fibrosis at single cell resolution.

AIMS: SARS-CoV-2 infection causes COVID-19, which in severe cases evokes life-threatening acute respiratory distress syndrome (ARDS). Transcriptome signatures and the functional relevance of non-vascular cell types (e.g. immune and epithelial cells) in COVID-19 are becoming increasingly evident. However, despite its known contribution to vascular inflammation, recruitment/invasion of immune cells, vascular leakage and perturbed hemostasis in the lungs of severe COVID-19 patients, an in-depth interrogation of the endothelial cell (EC) compartment in lethal COVID-19 is lacking. Moreover, progressive fibrotic lung disease represents one of the complications of COVID-19 pneumonia and ARDS. Analogous features between idiopathic pulmonary fibrosis (IPF) and COVID-19 suggest partial similarities in their pathophysiology, yet, a head-to-head comparison of pulmonary cell transcriptomes between both conditions has not been implemented to date. METHODS AND RESULTS: We performed single nucleus RNA-seq (snRNA-seq) on frozen lungs from 7 deceased COVID-19 patients, 6 IPF explant lungs and 12 controls. The vascular fraction, comprising 38,794 nuclei, could be subclustered into 14 distinct EC subtypes. Non-vascular cell types, comprising 137,746 nuclei, were subclustered and used for EC-interactome analyses. Pulmonary ECs of deceased COVID-19 patients showed an enrichment of genes involved in cellular stress, as well as signatures suggestive of dampened immunomodulation and impaired vessel wall integrity. In addition, increased abundance of a population of systemic capillary and venous ECs was identified in COVID-19 and IPF. COVID-19 systemic ECs closely resembled their IPF counterparts, and a set of 30 genes was found congruently enriched in systemic ECs across studies. Receptor-ligand interaction analysis of ECs with non-vascular cell types in the pulmonary micro-environment revealed numerous previously unknown interactions specifically enriched/depleted in COVID-19 and/or IPF. CONCLUSIONS: This study uncovered novel insights into the abundance, expression patterns and interactomes of EC subtypes in COVID-19 and IPF, relevant for future investigations into the progression and treatment of both lethal conditions. TRANSLATIONAL PERSPECTIVE: While assessing clinical and molecular characteristics of severe and lethal COVID-19 cases, the vasculature's undeniable role in disease progression has been widely acknowledged. COVID-19 lung pathology moreover shares certain clinical features with late-stage IPF - yet an in-depth interrogation and direct comparison of the endothelium at single-cell level in both conditions is still lacking. By comparing the transcriptomes of ECs from lungs of deceased COVID-19 patients to those from IPF explant and control lungs, we gathered key insights the heterogeneous composition and potential roles of ECs in both lethal diseases, which may serve as a foundation for development of novel therapeutics.

A systems immunology study comparing innate and adaptive immune responses in adults to COVID-19 mRNA and adenovirus vectored vaccines.

Identifying the molecular mechanisms that promote optimal immune responses to coronavirus disease 2019 (COVID-19) vaccination is critical for future rational vaccine design. Here, we longitudinally profile innate and adaptive immune responses in 102 adults after the first, second, and third doses of mRNA or adenovirus-vectored COVID-19 vaccines. Using a multi-omics approach, we identify key differences in the immune responses induced by ChAdOx1-S and BNT162b2 that correlate with antigen-specific antibody and T cell responses or vaccine reactogenicity. Unexpectedly, we observe that vaccination with ChAdOx1-S, but not BNT162b2, induces an adenoviral vector-specific memory response after the first dose, which correlates with the expression of proteins with roles in thrombosis with potential implications for thrombosis with thrombocytopenia syndrome (TTS), a rare but serious adverse event linked to adenovirus-vectored vaccines. The COVID-19 Vaccine Immune Responses Study thus represents a major resource that can be used to understand the immunogenicity and reactogenicity of these COVID-19 vaccines.