Spatial mapping of SARS-CoV-2 and H1N1 lung injury identifies differential transcriptional signatures

Comparative single-cell analysis reveals IFN-γ as a driver of respiratory sequelae after acute COVID-19

Postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) represent an urgent public health challenge and are estimated to affect more than 60 million individuals globally. Although a growing body of evidence suggests that dysregulated immune reactions may be linked with PASC symptoms, most investigations have primarily centered around blood-based studies, with few focusing on samples derived from affected tissues. Furthermore, clinical studies alone often provide correlative insights rather than causal mechanisms. Thus, it is essential to compare clinical samples with relevant animal models and conduct functional experiments to understand the etiology of PASC. In this study, we comprehensively compared bronchoalveolar lavage fluid single-cell RNA sequencing data derived from clinical PASC samples and a mouse model of PASC. This revealed a pro-fibrotic monocyte-derived macrophage response in respiratory PASC, as well as abnormal interactions between pulmonary macrophages and respiratory resident T cells, in both humans and mice. Interferon-γ (IFN-γ) emerged as a key node mediating the immune anomalies in respiratory PASC. Neutralizing IFN-γ after the resolution of acute SARS-CoV-2 infection reduced lung inflammation and tissue fibrosis in mice. Together, our study underscores the importance of performing comparative analysis to understand the cause of PASC and suggests that the IFN-γ signaling axis might represent a therapeutic target.

Characteristics and determinants of pulmonary long COVID

BACKGROUNDPersistent cough and dyspnea are prominent features of postacute sequelae of SARS-CoV-2 (also termed "long COVID"); however, physiologic measures and clinical features associated with these pulmonary symptoms remain poorly defined. Using longitudinal pulmonary function testing (PFT) and CT imaging, this study aimed to identify the characteristics and determinants of pulmonary long COVID.METHODSThis single-center retrospective study included 1,097 patients with clinically defined long COVID characterized by persistent pulmonary symptoms (dyspnea, cough, and chest discomfort) lasting for 1 or more months after resolution of primary COVID infection.RESULTSAfter exclusion, a total of 929 patients with post-COVID pulmonary symptoms and PFTs were stratified as diffusion impairment and pulmonary restriction, as measured by percentage predicted diffusion capacity for carbon monoxide (DLCO) and total lung capacity (TLC). Longitudinal evaluation revealed diffusion impairment (DLCO ≤ 80%) and pulmonary restriction (TLC ≤ 80%) in 51% of the cohort overall (n = 479). In multivariable modeling regression analysis, invasive mechanical ventilation during primary infection conferred the greatest increased odds of developing pulmonary long COVID with diffusion impairment and restriction (adjusted odds ratio [aOR] = 9.89, 95% CI 3.62-26.9]). Finally, a subanalysis of CT imaging identified radiographic evidence of fibrosis in this patient population.CONCLUSIONLongitudinal PFTs revealed persistent diffusion-impaired restriction as a key feature of pulmonary long COVID. These results emphasize the importance of incorporating PFTs into routine clinical practice for evaluation of long COVID patients with prolonged pulmonary symptoms. Subsequent clinical trials should leverage combined symptomatic and quantitative PFT measurements for more targeted enrollment of pulmonary long COVID patients.FUNDINGNational Institute of Allergy and Infectious Diseases (AI156898, K08AI129705), National Heart, Lung, and Blood Institute (HL153113, OTA21-015E, HL149944), and the COVID-19 Urgent Research Response Fund at the University of Alabama at Birmingham.

Delay induced stability switch in a mathematical model of CD8 T-cell response to SARS-CoV-2 mediated by receptor ACE2

The pathogen SARS-CoV-2 binds to the receptor angiotensin-converting enzyme 2 (ACE2) of the target cells and then replicates itself through the host, eventually releasing free virus particles. After infection, the CD8 T-cell response is triggered and appears to play a critical role in the defense against virus infections. Infected cells and their activated CD8 T-cells can cause tissue damage. Here, we established a mathematical model of within-host SARS-CoV-2 infection that incorporates the receptor ACE2, the CD8 T-cell response, and the damaged tissues. According to this model, we can get the basic reproduction number R0 and the immune reproduction number R1. We provide the theoretical proof for the stability of the disease-free equilibrium, immune-inactivated equilibrium, and immune-activated equilibrium. Finally, our numerical simulations show that the time delay in CD8 T-cell production can induce complex dynamics such as stability switching. These results provide insights into the mechanisms of SARS-CoV-2 infection and may help in the development of effective drugs against COVID-19.

Differences of respiratory mechanics in mechanical ventilation of acute respiratory distress syndrome between patients with COVID-19 and Influenza A

BACKGROUND

Whether COVID-19-induced acute respiratory distress syndrome (ARDS) should be approached differently in terms of mechanical ventilation therapy compared to other virus-induced ARDS is debatable. Therefore, we aimed to ascertain whether the respiratory mechanical characteristics of COVID-19-induced ARDS differ from those of influenza A induced ARDS, in order to establish a rationale for mechanical ventilation therapy in COVID-19-induced ARDS.

METHODS

This was a retrospective cohort study comparing patients with COVID-19-induced ARDS and influenza A induced ARDS. We included intensive care unit (ICU) patients with COVID-19 or Influenza A aged ≥ 19, who were diagnosed with ARDS according to the Berlin definition between January 2015 and July 2021. Ventilation parameters for respiratory mechanics were collected at specific times on days one, three, and seven after intubation.

RESULTS

The median age of the 87 participants was 71.0 (62.0-78.0) years old, and 63.2% were male. The ratio of partial pressure of oxygen in arterial blood to the fractional of inspiratory oxygen concentration in COVID-19-induced ARDS was lower than that in influenza A induced ARDS during the initial stages of mechanical ventilation (influenza A induced ARDS 216.1 vs. COVID-19-induced ARDS 167.9, p = 0.009, day 1). The positive end expiratory pressure remained consistently higher in the COVID-19 group throughout the follow-up period (7.0 vs. 10.0, p < 0.001, day 1). COVID-19 and influenza A initially showed different directions for peak inspiratory pressure and dynamic compliance; however, after day 3, both groups exhibited similar directions. Dynamic driving pressure exhibited opposite trends between the two groups during mechanical ventilation.

CONCLUSIONS

Respiratory mechanics show clear differences between COVID-19-induced ARDS and influenza A induced ARDS. Based on these findings, we can consider future treatment strategies for COVID-19-induced ARDS.

Single-cell analytical technologies: uncovering the mechanisms behind variations in immune responses

The immune landscape varies among individuals. It determines the immune response and results in surprisingly diverse symptoms, even in response to similar external stimuli. However, the detailed mechanisms underlying such diverse immune responses have remained mostly elusive. The utilization of recently developed single-cell multimodal analysis platforms has started to answer this question. Emerging studies have elucidated several molecular networks that may explain diversity with respect to age or other factors. An elaborate interplay between inherent physical conditions and environmental conditions has been demonstrated. Furthermore, the importance of modifications by the epigenome resulting in transcriptome variation among individuals is gradually being revealed. Accordingly, epigenomes and transcriptomes are direct indicators of the medical history and dynamic interactions with environmental factors. Coronavirus disease 2019 (COVID-19) has recently become one of the most remarkable examples of the necessity of in-depth analyses of diverse responses with respect to various factors to improve treatment in severe cases and to prevent viral transmission from asymptomatic carriers. In fact, determining why some patients develop serious symptoms is still a pressing issue. Here, we review the current "state of the art" in single-cell analytical technologies and their broad applications to healthy individuals and representative diseases, including COVID-19.

Characteristics and Determinants of Pulmonary Long COVID

RATIONALE

Persistent cough and dyspnea are prominent features of post-acute sequelae of SARS-CoV-2 (termed 'Long COVID'); however, physiologic measures and clinical features associated with these pulmonary symptoms remain poorly defined.

OBJECTIVES

Using longitudinal pulmonary function testing (PFTs) and CT imaging, this study aimed to identify the characteristics and determinants of pulmonary Long COVID.

METHODS

The University of Alabama at Birmingham Pulmonary Long COVID cohort was utilized to characterize lung defects in patients with persistent pulmonary symptoms after resolution primary COVID infection. Longitudinal PFTs including total lung capacity (TLC) and diffusion limitation of carbon monoxide (DLCO) were used to evaluate restriction and diffusion impairment over time in this cohort. Analysis of chest CT imaging was used to phenotype the pulmonary Long COVID pathology. Risk factors linked to development of pulmonary Long COVID were estimated using univariate and multivariate logistic regression models.

MEASUREMENTS AND MAIN RESULTS

Longitudinal evaluation 929 patients with post-COVID pulmonary symptoms revealed diffusion impairment (DLCO ≤80%) and restriction (TLC ≤80%) in 51% of the cohort (n=479). In multivariable logistic regression analysis (adjusted odds ratio; aOR, 95% confidence interval [CI]), invasive mechanical ventilation during primary infection conferred the greatest increased odds of developing pulmonary Long COVID with diffusion impaired restriction (aOR=10.9 [4.09-28.6]). Finally, a sub-analysis of CT imaging identified evidence of fibrosis in this population.

CONCLUSIONS

Persistent diffusion impaired restriction was identified as a key feature of pulmonary Long COVID. Subsequent clinical trials should leverage combined symptomatic and quantitative PFT measurements for more targeted enrollment of pulmonary Long COVID patients.

Differential effects of microRNAs miR-21, miR-99 and miR-145 on lung regeneration and inflammation during recovery from influenza pneumonia

In a mouse model of influenza pneumonia, we previously documented that proliferating alveolar type II (AT2) cells are the major stem cells involved in early lung recovery. Profiling of microRNAs revealed significant dysregulation of specific ones, including miR-21 and miR-99a. Moreover, miR-145 is known to exhibit antagonism to miR-21. This follow-up study investigated the roles of microRNAs miR-21, miR-99a, and miR-145 in the murine pulmonary regenerative process and inflammation during influenza pneumonia. Inhibition of miR-21 resulted in severe morbidity, and in significantly decreased proliferating AT2 cells due to impaired transition from innate to adaptive immune responses. Knockdown of miR-99a culminated in moderate morbidity, with a significant increase in proliferating AT2 cells that may be linked to PTEN downregulation. In contrast, miR-145 antagonism did not impact morbidity nor the proliferating AT2 cell population, and was associated with downregulation of TNF-alpha, IL1-beta, YM1, and LY6G. Hence, a complex interplay exists between expression of specific miRNAs, lung regeneration, and inflammation during recovery from influenza pneumonia. Inhibition of miR-21 and miR-99a (but not miR-145) can lead to deleterious cellular and molecular effects on pulmonary repair and inflammatory processes during influenza pneumonia.

Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections

Technologies to study localized host-pathogen interactions are urgently needed. Here, we present a spatial transcriptomics approach to simultaneously capture host and pathogen transcriptome-wide spatial gene expression information from human formalin-fixed paraffin-embedded (FFPE) tissue sections at a near single-cell resolution. We demonstrate this methodology in lung samples from COVID-19 patients and validate our spatial detection of SARS-CoV-2 against RNAScope and in situ sequencing. Host-pathogen colocalization analysis identified putative modulators of SARS-CoV-2 infection in human lung cells. Our approach provides new insights into host response to pathogen infection through the simultaneous, unbiased detection of two transcriptomes in FFPE samples.

Pulmonary Sequelae of COVID-19: Focus on Interstitial Lung Disease

As the world transitions from the acute phase of the COVID-19 pandemic, a novel concern has arisen-interstitial lung disease (ILD) as a consequence of SARS-CoV-2 infection. This review discusses what we have learned about its epidemiology, radiological, and pulmonary function findings, risk factors, and possible management strategies. Notably, the prevailing radiological pattern observed is organising pneumonia, with ground-glass opacities and reticulation frequently reported. Longitudinal studies reveal a complex trajectory, with some demonstrating improvement in lung function and radiographic abnormalities over time, whereas others show more static fibrotic changes. Age, disease severity, and male sex are emerging as risk factors for residual lung abnormalities. The intricate relationship between post-COVID ILD and idiopathic pulmonary fibrosis (IPF) genetics underscores the need for further research and elucidation of shared pathways. As this new disease entity unfolds, continued research is vital to guide clinical decision making and improve outcomes for patients with post-COVID ILD.

Spatial transcriptomics: recent developments and insights in respiratory research

The respiratory system's complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial localization and cellular interactions have not been clearly elucidated. Spatial transcriptomics (ST) has filled this gap and has been widely used in respiratory studies. This review focuses on the latest iterative technology of ST in recent years, summarizing how ST can be applied to the physiological and pathological processes of the respiratory system, with emphasis on the lungs. Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, integration of multi-omics, temporal and spatial omics, bioinformatics analysis, etc. These viewpoints are expected to advance the study of systematic mechanisms, including respiratory studies.

Spatial Transcriptomic Analysis of Focal and Normal Areas of Myocyte Disarray in Human Hypertrophic Cardiomyopathy

Hypertrophic Cardiomyopathy (HCM) is a common inherited disorder that can lead to heart failure and sudden cardiac death, characterized at the histological level by focal areas of myocyte disarray, hypertrophy and fibrosis, and only a few disease-targeted therapies exist. To identify the focal and spatially restricted alterations in the transcriptional pathways and reveal novel therapeutic targets, we performed a spatial transcriptomic analysis of the areas of focal myocyte disarray compared to areas of normal tissue using a commercially available platform (GeoMx, nanoString). We analyzed surgical myectomy tissue from four patients with HCM and the control interventricular septum tissue from two unused organ donor hearts that were free of cardiovascular disease. Histological sections were reviewed by an expert pathologist, and 72 focal areas with varying degrees of myocyte disarray (normal, mild, moderate, severe) were chosen for analysis. Areas of interest were interrogated with the Human Cancer Transcriptome Atlas designed to profile 1800 transcripts. Differential expression analysis revealed significant changes in gene expression between HCM and the control tissue, and functional enrichment analysis indicated that these genes were primarily involved in interferon production and mitochondrial energetics. Within the HCM tissue, differentially expressed genes between areas of normal and severe disarray were enriched for genes related to mitochondrial energetics and the extracellular matrix in severe disarray. An analysis of the gene expression of the ligand-receptor pair revealed that the HCM tissue exhibited downregulation of platelet-derived growth factor (PDGF), NOTCH, junctional adhesion molecule, and CD46 signaling while showing upregulation of fibronectin, CD99, cadherin, and amyloid precursor protein signaling. A deconvolution analysis utilizing the matched single nuclei RNA-sequencing (snRNA-seq) data to determine cell type composition in areas of interest revealed significant differences in fibroblast and vascular cell composition in areas of severe disarray when compared to normal areas in HCM samples. Cell composition in the normal areas of the control tissue was also divergent from the normal areas in HCM samples, which was consistent with the differential expression results. Overall, our data identify novel and potential disease-modifying targets for therapy in HCM.

Spatial transcriptomic profiling of coronary endothelial cells in SARS-CoV-2 myocarditis

Objectives

Our objective was to examine coronary endothelial and myocardial programming in patients with severe COVID-19 utilizing digital spatial transcriptomics.

Background

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has well-established links to thrombotic and cardiovascular events. Endothelial cell infection was initially proposed to initiate vascular events; however, this paradigm has sparked growing controversy. The significance of myocardial infection also remains unclear.

Methods

Autopsy-derived cardiac tissue from control (n = 4) and COVID-19 (n = 8) patients underwent spatial transcriptomic profiling to assess differential expression patterns in myocardial and coronary vascular tissue. Our approach enabled transcriptional profiling in situ with preserved anatomy and unaltered local SARS-CoV-2 expression. In so doing, we examined the paracrine effect of SARS-CoV-2 infection in cardiac tissue.

Results

We observed heterogeneous myocardial infection that tended to colocalize with CD31 positive cells within coronary capillaries. Despite these differences, COVID-19 patients displayed a uniform and unique myocardial transcriptional profile independent of local viral burden. Segmentation of tissues directly infected with SARS-CoV-2 showed unique, pro-inflammatory expression profiles including upregulated mediators of viral antigen presentation and immune regulation. Infected cell types appeared to primarily be capillary endothelial cells as differentially expressed genes included endothelial cell markers. However, there was limited differential expression within the endothelium of larger coronary vessels.

Conclusion

Our results highlight altered myocardial programming during severe COVID-19 that may in part be associated with capillary endothelial cells. However, similar patterns were not observed in larger vessels, diminishing endotheliitis, and endothelial activation as key drivers of cardiovascular events during COVID-19.

Warmer ambient air temperatures reduce nasal turbinate and brain infection, but increase lung inflammation in the K18-hACE2 mouse model of COVID-19

Warmer climatic conditions have been associated with fewer COVID-19 cases. Herein we infected K18-hACE2 mice housed at the standard animal house temperature of ∼22 °C, or at ∼31 °C, which is considered to be thermoneutral for mice. On day 2 post infection, RNA-Seq analyses showed no significant differential gene expression lung in lungs of mice housed at the two temperatures, with almost identical viral loads and type I interferon responses. There was also no significant difference in viral loads in lungs on day 5, but RNA-Seq and histology analyses showed clearly elevated inflammatory signatures and infiltrates. Thermoneutrality thus promoted lung inflammation. On day 2 post infection mice housed at 31 °C showed reduced viral loads in nasal turbinates, consistent with increased mucociliary clearance at the warmer ambient temperature. These mice also had reduced virus levels in the brain, and an ensuing amelioration of weight loss and a delay in mortality. Warmer air temperatures may thus reduce infection of the upper respiratory track and the olfactory epithelium, resulting in reduced brain infection. Potential relevance for anosmia and neurological sequelae in COVID-19 patients is discussed.

Alternative normalization and analysis pipeline to address systematic bias in NanoString GeoMx Digital Spatial Profiling data

Spatial transcriptomics is a novel technique that provides RNA-expression data with tissue-contextual annotations. Quality assessments of such techniques using end-user generated data are often lacking. Here, we evaluated data from the NanoString GeoMx Digital Spatial Profiling (DSP) platform and standard processing pipelines. We queried 72 ROIs from 12 glioma samples, performed replicate experiments of eight samples for validation, and evaluated five external datasets. The data consistently showed vastly different signal intensities between samples and experimental conditions that resulted in biased analysis. We evaluated the performance of alternative normalization strategies and show that quantile normalization can adequately address the technical issues related to the differences in data distributions. Compared to bulk RNA sequencing, NanoString DSP data show a limited dynamic range which underestimates differences between conditions. Weighted gene co-expression network analysis allowed extraction of gene signatures associated with tissue phenotypes from ROI annotations. Nanostring GeoMx DSP data therefore require alternative normalization methods and analysis pipelines.

IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study

Purpose

Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.

Methods

We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.

Results

We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.

Conclusion

These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

HCV Infection Increases the Expression of ACE2 Receptor, Leading to Enhanced Entry of Both HCV and SARS-CoV-2 into Hepatocytes and a Coinfection State

Recent studies suggest the enhancement of liver injury in COVID-19 patients infected with Hepatitis C virus (HCV). Hepatocytes express low levels of angiotensin-converting enzyme 2 (ACE2), the SARS-CoV-2 entry receptor, raising the possibility of HCV-SARS-CoV-2 coinfection in the liver. This work aimed to explore whether HCV and SARS-CoV-2 coinfect hepatocytes and the interplay between these viruses. We demonstrate that SARS-CoV-2 coinfects HCV-infected Huh7.5 (Huh7.5HCV) cells. Both viruses replicated efficiently in the coinfected cells, with HCV replication enhanced in coinfected compared to HCV-mono-infected cells. Strikingly, Huh7.5HCV cells were eight fold more susceptible to SARS-CoV-2 pseudoviruses than naive Huh7.5 cells, suggesting enhanced SARS-CoV-2 entry into HCV-preinfected hepatocytes. In addition, we observed increased binding of spike receptor-binding domain (RBD) protein to Huh7.5HCV cells, as well as enhanced cell-to-cell fusion of Huh7.5HCV cells with spike-expressing Huh7.5 cells. We explored the mechanism of enhanced SARS-CoV-2 entry and identified an increased ACE2 mRNA and protein levels in Huh7.5HCV cells, primary hepatocytes, and in data from infected liver biopsies obtained from database. Importantly, higher expression of ACE2 increased HCV infection by enhancing its binding to the host cell, underscoring its role in the HCV life cycle as well. Transcriptome analysis revealed that shared host signaling pathways were induced in HCV-SARS-CoV-2 coinfection. This study revealed complex interactions between HCV and SARS-CoV-2 infections in hepatocytes, which may lead to the increased liver damage recently reported in HCV-positive COVID-19 patients. IMPORTANCE Here, we provide the first experimental evidence for the coexistence of SARS-CoV-2 infection with HCV, and the interplay between them. The study revealed a complex relationship of enhancement between the two viruses, where HCV infection increased the expression of the SARS-CoV-2 entry receptor ACE2, thus facilitating SARS-CoV-2 entry, and potentially, also HCV entry. Thereafter, SARS-CoV-2 infection enhanced HCV replication in hepatocytes. This study may explain the aggravation of liver damage that was recently reported in COVID-19 patients with HCV coinfection and suggests preinfection with HCV as a risk factor for severe COVID-19. Moreover, it highlights the possible importance of HCV treatment for coinfected patients. In a broader view, these findings emphasize the importance of identifying coinfecting pathogens that increase the risk of SARS-CoV-2 infection and that may accelerate COVID-19-related co-morbidities.

α2,6-Sialylation Is Upregulated in Severe COVID-19, Implicating the Complement Cascade

Better understanding of the molecular mechanisms underlying COVID-19 severity is desperately needed in current times. Although hyper-inflammation drives severe COVID-19, precise mechanisms triggering this cascade and what role glycosylation might play therein are unknown. Here we report the first high-throughput glycomic analysis of COVID-19 plasma samples and autopsy tissues. We find that α2,6-sialylation is upregulated in the plasma of patients with severe COVID-19 and in autopsied lung tissue. This glycan motif is enriched on members of the complement cascade (e.g., C5, C9), which show higher levels of sialylation in severe COVID-19. In the lung tissue, we observe increased complement deposition, associated with elevated α2,6-sialylation levels, corresponding to elevated markers of poor prognosis (IL-6) and fibrotic response. We also observe upregulation of the α2,6-sialylation enzyme ST6GAL1 in patients who succumbed to COVID-19. Our work identifies a heretofore undescribed relationship between sialylation and complement in severe COVID-19, potentially informing future therapeutic development.

Spatial transcriptomic profiling of coronary endothelial cells in SARS-CoV-2 myocarditis

OBJECTIVES

Our objective was to examine coronary endothelial and myocardial programming in patients with severe COVID-19 utilizing digital spatial transcriptomics.

BACKGROUND

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has well-established links to thrombotic and cardiovascular events. Endothelial cell infection was initially proposed to initiate vascular events; however, this paradigm has sparked growing controversy. The significance of myocardial infection also remains unclear.

METHODS

Autopsy-derived cardiac tissue from control (n = 4) and COVID-19 (n = 8) patients underwent spatial transcriptomic profiling to assess differential expression patterns in myocardial and coronary vascular tissue. Our approach enabled transcriptional profiling in situ with preserved anatomy and unaltered local SARS-CoV-2 expression. In so doing, we examined the paracrine effect of SARS-CoV-2 infection in cardiac tissue.

RESULTS

We observed heterogeneous myocardial infection that tended to colocalize with CD31 positive cells within coronary capillaries. Despite these differences, COVID-19 patients displayed a uniform and unique myocardial transcriptional profile independent of local viral burden. Segmentation of tissues directly infected with SARS-CoV-2 showed unique, pro-inflammatory expression profiles including upregulated mediators of viral antigen presentation and immune regulation. Infected cell types appeared to primarily be capillary endothelial cells as differentially expressed genes included endothelial cell markers. However, there was limited differential expression within the endothelium of larger coronary vessels.

CONCLUSIONS

Our results highlight altered myocardial programming during severe COVID-19 that may in part be associated with capillary endothelial cells. However, similar patterns were not observed in larger vessels, diminishing endotheliitis and endothelial activation as key drivers of cardiovascular events during COVID-19.

CONDENSED ABSTRACT

SARS-CoV-2 is linked to thrombotic and cardiovascular events; however, the mechanism remains uncertain. Our objective was to examine coronary endothelial and myocardial programming in patients with severe COVID-19 utilizing digital spatial transcriptomics. Autopsy-derived coronary arterial and cardiac tissues from control and COVID-19 patients underwent spatial transcriptomic profiling. Our approach enabled transcriptional profiling in situ with preserved anatomy and unaltered local SARS-CoV-2 expression. We observed unique, pro-inflammatory expression profiles among all COVID-19 patients. While heterogeneous viral expression was noted within the tissue, SARS-CoV-2 tended to colocalize with CD31 positive cells within coronary capillaries and was associated with unique expression profiles. Similar patterns were not observed in larger coronary vessels. Our results highlight altered myocardial programming during severe COVID-19 that may in part be associated with capillary endothelial cells. Such results diminish coronary arterial endotheliitis and endothelial activation as key drivers of cardiovascular events during COVID-19 infection.

LIST OF HIGHLIGHTS

SARS-CoV-2 has variable expression patterns within the myocardium of COVID-19 patientsSARS-CoV-2 infection induces a unique myocardial transcriptional programming independent of local viral burdenSARS-CoV-2 myocarditis is predominantly associated with capillaritis, and tissues directly infected with SARS-CoV-2 have unique, pro-inflammatory expression profilesDiffuse endothelial activation of larger coronary vessels was absent, diminishing large artery endotheliitis as a significant contributor to cardiovascular events during COVID-19 infection.

Transcriptomics and RNA-Based Therapeutics as Potential Approaches to Manage SARS-CoV-2 Infection

SARS-CoV-2 is a coronavirus family member that appeared in China in December 2019 and caused the disease called COVID-19, which was declared a pandemic in 2020 by the World Health Organization. In recent months, great efforts have been made in the field of basic and clinical research to understand the biology and infection processes of SARS-CoV-2. In particular, transcriptome analysis has contributed to generating new knowledge of the viral sequences and intracellular signaling pathways that regulate the infection and pathogenesis of SARS-CoV-2, generating new information about its biology. Furthermore, transcriptomics approaches including spatial transcriptomics, single-cell transcriptomics and direct RNA sequencing have been used for clinical applications in monitoring, detection, diagnosis, and treatment to generate new clinical predictive models for SARS-CoV-2. Consequently, RNA-based therapeutics and their relationship with SARS-CoV-2 have emerged as promising strategies to battle the SARS-CoV-2 pandemic with the assistance of novel approaches such as CRISPR-CAS, ASOs, and siRNA systems. Lastly, we discuss the importance of precision public health in the management of patients infected with SARS-CoV-2 and establish that the fusion of transcriptomics, RNA-based therapeutics, and precision public health will allow a linkage for developing health systems that facilitate the acquisition of relevant clinical strategies for rapid decision making to assist in the management and treatment of the SARS-CoV-2-infected population to combat this global public health problem.

Host and microbiome features of secondary infections in lethal covid-19

Secondary infections contribute significantly to covid-19 mortality but driving factors remain poorly understood. Autopsies of 20 covid-19 cases and 14 controls from the first pandemic wave complemented with microbial cultivation and RNA-seq from lung tissues enabled description of major organ pathologies and specification of secondary infections. Lethal covid-19 segregated into two main death causes with either dominant diffuse alveolar damage (DAD) or secondary pneumonias. The lung microbiome in covid-19 showed a reduced biodiversity and increased prototypical bacterial and fungal pathogens in cases of secondary pneumonias. RNA-seq distinctly mirrored death causes and stratified DAD cases into subgroups with differing cellular compositions identifying myeloid cells, macrophages and complement C1q as strong separating factors suggesting a pathophysiological link. Together with a prominent induction of inhibitory immune-checkpoints our study highlights profound alterations of the lung immunity in covid-19 wherein a reduced antimicrobial defense likely drives development of secondary infections on top of SARS-CoV-2 infection.

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Covid-19 autopsy cohort complemented with microbial cultivation and deep sequencing

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Major death causes stratify into DAD and secondary pneumonias

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Prototypical bacterial and fungal agents are found in secondary pneumonias

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Macrophages and C1q stratify DAD subgroups and indicate immune impairment in lungs

α2,6-Sialylation is Upregulated in Severe COVID-19 Implicating the Complement Cascade

Better understanding of the mechanisms of COVID-19 severity is desperately needed in current times. Although hyper-inflammation drives severe COVID-19, precise mechanisms triggering this cascade and what role glycosylation might play therein is unknown. Here we report the first high-throughput glycomic analysis of COVID-19 plasma samples and autopsy tissues. We find α2,6-sialylation is upregulated in plasma of patients with severe COVID-19 and in the lung. This glycan motif is enriched on members of the complement cascade, which show higher levels of sialylation in severe COVID-19. In the lung tissue, we observe increased complement deposition, associated with elevated α2,6-sialylation levels, corresponding to elevated markers of poor prognosis (IL-6) and fibrotic response. We also observe upregulation of the α2,6-sialylation enzyme ST6GAL1 in patients who succumbed to COVID-19. Our work identifies a heretofore undescribed relationship between sialylation and complement in severe COVID-19, potentially informing future therapeutic development.

Mechanisms of Lung Injury Induced by SARS-CoV-2 Infection

The lung is the major target organ of SARS-CoV-2 infection, which causes COVID-19. Here, we outline the multistep mechanisms of lung epithelial and endothelial injury induced by SARS-CoV-2: direct viral infection, chemokine/cytokine-mediated damage, and immune cell-mediated lung injury. Finally, we discuss the recent progress in terms of antiviral therapeutics as well as the development of anti-inflammatory or immunomodulatory therapeutic approaches. This review also provides a systematic overview of the models for studying SARS-CoV-2 infection and discusses how an understanding of mechanisms of lung injury will help identify potential targets for future drug development to mitigate lung injury.

System-wide transcriptome damage and tissue identity loss in COVID-19 patients

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.

Post-mortem lung tissue: the fossil record of the pathophysiology and immunopathology of severe COVID-19

The lungs are the main site that is affected in severe COVID-19, and post-mortem lung tissue provides crucial insights into the pathophysiology of severe disease. From basic histology to state-of-the-art multiparameter digital pathology technologies, post-mortem lung tissue provides snapshots of tissue architecture, and resident and inflammatory cell phenotypes and composition at the time of death. Contrary to early assumptions that COVID-19 in the lungs is a uniform disease, post-mortem findings have established a high degree of disease heterogeneity. Classic diffuse alveolar damage represents just one phenotype, with disease divisible by early and late progression as well as by pathophysiological process. A distinct lung tissue state occurs with secondary infection; extrapulmonary causes of death might also originate from a pathological process in the lungs linked to microthrombosis. This heterogeneity of COVID-19 lung disease must be recognised in the management of patients and in the development of novel treatment strategies.

Use of Telepathology to Facilitate COVID-19 Research and Education through an Online COVID-19 Autopsy Biorepository

Introduction:

The coronavirus disease 2019 (COVID-19) pandemic has increased the use of technology for communication including departmental conferences, working remotely, and distance teaching. Methods to enable these activities should be developed and promulgated.

Objective:

To repurpose a preexisting educational website to enable the development of a COVID-19 autopsy biorepository to support distance teaching and COVID-19 research.

Methods:

After consent was obtained, autopsies were performed on patients with a confirmed positive severe acute respiratory syndrome coronavirus-2 reverse-transcriptase-polymerase-chain reaction test. Autopsies were performed according to a COVID-19 protocol, and all patients underwent both gross and microscopic examination. The H and E histology slides were scanned using a Leica Biosystems Aperio CS ScanScope whole slide scanner and the digital slide files were converted to deep zoom images that could be uploaded to the University of Alabama at Birmingham (UAB) Pathology Educational Instructional Resource website where virtual microscopy of the slides is available.

Results:

A total of 551 autopsy slides from 24 UAB COVID-19 cases, 1 influenza H1N1 case and 1 tuberculosis case were scanned and uploaded. Five separate COVID-19 research teams used the digital slides remotely with or without a pathologist on a Zoom call. The scanned slides were used to produce one published case report and one published research project. The digital COVID-19 autopsy biorepository was routinely used for educational conferences and research meetings locally, nationally and internationally.

Conclusion:

The repurposing of a pre-existing website enabled telepathology consultation for research and education purposes. Combined with other communication technology (Zoom) this achievement highlights what is possible using pre-existing technologies during a global pandemic.

Core genes involved in the regulation of acute lung injury and their association with COVID-19 and tumor progression: A bioinformatics and experimental study

Acute lung injury (ALI) is a specific form of lung damage caused by different infectious and non-infectious agents, including SARS-CoV-2, leading to severe respiratory and systemic inflammation. To gain deeper insight into the molecular mechanisms behind ALI and to identify core elements of the regulatory network associated with this pathology, key genes involved in the regulation of the acute lung inflammatory response (Il6, Ccl2, Cat, Serpine1, Eln, Timp1, Ptx3, Socs3) were revealed using comprehensive bioinformatics analysis of whole-genome microarray datasets, functional annotation of differentially expressed genes (DEGs), reconstruction of protein-protein interaction networks and text mining. The bioinformatics data were validated using a murine model of LPS-induced ALI; changes in the gene expression patterns were assessed during ALI progression and prevention by anti-inflammatory therapy with dexamethasone and the semisynthetic triterpenoid soloxolone methyl (SM), two agents with different mechanisms of action. Analysis showed that 7 of 8 revealed ALI-related genes were susceptible to LPS challenge (up-regulation: Il6, Ccl2, Cat, Serpine1, Eln, Timp1, Socs3; down-regulation: Cat) and their expression was reversed by the pre-treatment of mice with both anti-inflammatory agents. Furthermore, ALI-associated nodal genes were analysed with respect to SARS-CoV-2 infection and lung cancers. The overlap with DEGs identified in postmortem lung tissues from COVID-19 patients revealed genes (Saa1, Rsad2, Ifi44, Rtp4, Mmp8) that (a) showed a high degree centrality in the COVID-19-related regulatory network, (b) were up-regulated in murine lungs after LPS administration, and (c) were susceptible to anti-inflammatory therapy. Analysis of ALI-associated key genes using The Cancer Genome Atlas showed their correlation with poor survival in patients with lung neoplasias (Ptx3, Timp1, Serpine1, Plaur). Taken together, a number of key genes playing a core function in the regulation of lung inflammation were found, which can serve both as promising therapeutic targets and molecular markers to control lung ailments, including COVID-19-associated ALI.

Profiling of lung SARS-CoV-2 and influenza virus infection dissects virus-specific host responses and gene signatures

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies. Here, we use targeted transcriptomics of FFPE tissue using the Nanostring GeoMX™ platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients. Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the sample, within patient correlations and patient-patient variation had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27, previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza. Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.

Persistent Right Ventricle Dilatation in SARS-CoV-2-Related Acute Respiratory Distress Syndrome on Extracorporeal Membrane Oxygenation Support

Objectives

Venovenous extracorporeal membrane oxygenation (ECMO) support may be considered in experienced centers for patients with acute respiratory distress syndrome (ARDS) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection refractory to conventional treatment. In ECMO patients, echocardiography has emerged as a clinical tool for implantation and clinical management; but to date, little data are available on COVID-related ARDS patients requiring ECMO. The authors assessed the incidence of right ventricular dilatation and dysfunction (RvDys) in patients with COVID-related ARDS requiring ECMO.

Design

Single-center investigation.

Setting

Intensive care unit (ICU).

Participants

A total of 35 patients with COVID-related ARDS requiring ECMO, consecutively admitted to the ICU (March 1, 2020, to February 28, 2021).

Interventions

Serial echocardiographic examinations. RvDys was defined as RV end-diastolic area/LV end-diastolic area >0.6 and tricuspid annular plane excursion <15 mm.

Measurements and Main Results

The incidence of RvDys was 15/35 (42%). RvDys patients underwent ECMO support after a longer period of mechanical ventilation (p = 0.006) and exhibited a higher mortality rate (p = 0.024) than those without RvDys. In nonsurvivors, RvDys was observed in all patients (n = nine) who died with unfavorable progression of COVID-related ARDS. In survivors, weaned from ECMO, a significant reduction in systolic pulmonary arterial pressures was detectable.

Conclusions

According to the authors’ data, in COVID-related ARDS requiring ECMO support, RvDys is common, associated with increased ICU mortality. Overall, the data underscored the clinical role of echocardiography in COVID-related ARDS supported by venovenous ECMO, because serial echocardiographic assessments (especially focused on RV changes) are able to reflect pulmonary COVID disease severity.

Spatially Resolved Immunometabolism to Understand Infectious Disease Progression

Infectious diseases, including those of viral, bacterial, fungal, and parasitic origin are often characterized by focal inflammation occurring in one or more distinct tissues. Tissue-specific outcomes of infection are also evident in many infectious diseases, suggesting that the local microenvironment may instruct complex and diverse innate and adaptive cellular responses resulting in locally distinct molecular signatures. In turn, these molecular signatures may both drive and be responsive to local metabolic changes in immune as well as non-immune cells, ultimately shaping the outcome of infection. Given the spatial complexity of immune and inflammatory responses during infection, it is evident that understanding the spatial organization of transcripts, proteins, lipids, and metabolites is pivotal to delineating the underlying regulation of local immunity. Molecular imaging techniques like mass spectrometry imaging and spatially resolved, highly multiplexed immunohistochemistry and transcriptomics can define detailed metabolic signatures at the microenvironmental level. Moreover, a successful complementation of these two imaging techniques would allow multi-omics analyses of inflammatory microenvironments to facilitate understanding of disease pathogenesis and identify novel targets for therapeutic intervention. Here, we describe strategies for downstream data analysis of spatially resolved multi-omics data and, using leishmaniasis as an exemplar, describe how such analysis can be applied in a disease-specific context.