Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury

OPG and BAFF as predictive biomarkers of the severity of SARS-CoV-2 infection

Molecules of the tumour necrosis factor superfamily (TNFSF) are key players in immune regulation; an increase in some TNFSF molecules has been reported during severe COVID-19. In this study, we profiled and evaluated TNFSF members in the serum of COVID-19 vaccine-naïve patients to identify potential biomarkers associated with disease severity. Our data show that TRAIL serum levels are lower in severely affected patients than those mildly affected by COVID-19 (AUC 0.8, p = 0.0003). On the contrary, OPG and BAFF serum levels are higher in severe COVID-19 compared to mild COVID-19 cases (AUC 0.8, p = 0.0001; AUC 0.7, p = 0.0012; respectively) and moderate COVID-19 cases (OPG p < 0.01), BAFF (p < 0.05). At the transcriptional level, TRAIL, OPG and BAFF are elevated in severe compared to mild COVID-19 cases, with OPG and BAFF also higher in moderate compared to mild COVID-19 patients. Additionally, we found that APRIL, LIGHT, CD30L and CD40L protein-levels are higher in COVID-19 patients compared to healthy donors but not significantly different between various COVID-19 clinical statuses. Finally, we found that TNF-α, TNF-β, RANKL and TWEAK protein levels were not affected during COVID-19. Our work identifies OPG and BAFF as potential biomarkers and therapeutic targets for preventing severe COVID-19. Due to the opposite contradictory levels of TRAIL (protein/transcriptional level), its role during COVID-19 should be elucidated and clarified with more in-depth studies.

Effects of PGK1 on immunoinfiltration by integrated single-cell and bulk RNA-sequencing analysis in sepsis

Background

Sepsis, a life-threatening organ dysfunction caused by a dysregulated immune response to infection, remains a significant global health challenge. Phosphoglycerate kinase 1 (PGK1) has been implicated in regulating inflammation and immune cell infiltration in inflammatory conditions. However, the role of PGK1 in sepsis remains largely unexplored.

Methods

Four microarray datasets and a high throughput sequencing dataset were acquired from GEO database to reveal the PGK1 expression in patients of sepsis. Quantitative real-time PCR and western blotting was then used to validate the PGK1 level. Additionally, microarray and single-cell RNA sequencing data integration, including gene set enrichment analysis (GSEA), KEGG and GO functional enrichment analysis, immune infiltration analysis, and single-cell sequencing analysis, were performed to elucidate the role of PGK1 in sepsis.

Results

Our results revealed a significant upregulation of PGK1 in sepsis patients, with the area under the ROC curve (AUC) exceeding 0.9 across multiple datasets, indicating PGK1's strong potential as a diagnostic biomarker. Notably, PGK1 was enriched in key immune-related pathways, including the TNF signaling pathways, and leukocyte transendothelial migration, suggesting its involvement in immune regulation. Furthermore, PGK1 expression showed a positive correlation with the levels of inflammatory mediators CXCL1, CXCL16, and the chemokine receptor CCR1. In terms of immune cell infiltration, PGK1 was positively correlated with naive B cells, resting memory CD4 T cell, gamma delta T cells, M0 macrophages, eosinophils and negatively correlated with plasma cells, CD8 T cells, activated memory CD4 T cell, Tregs, activated dendritic cells.

Conclusions

This study concluded that PGK1 served as a novel diagnostic biomarker for sepsis, with potential implications for prognosis and immune regulation. The significant upregulation of PGK1 in sepsis patients and its association with immune-related pathways and cell types highlight its potential role in the pathogenesis of sepsis.

Human vascularized macrophage-islet organoids to model immune-mediated pancreatic β cell pyroptosis upon viral infection

There is a paucity of human models to study immune-mediated host damage. Here, we utilized the GeoMx spatial multi-omics platform to analyze immune cell changes in COVID-19 pancreatic autopsy samples, revealing an accumulation of proinflammatory macrophages. Single-cell RNA sequencing (scRNA-seq) analysis of human islets exposed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or coxsackievirus B4 (CVB4) viruses identified activation of proinflammatory macrophages and β cell pyroptosis. To distinguish viral versus proinflammatory-macrophage-mediated β cell pyroptosis, we developed human pluripotent stem cell (hPSC)-derived vascularized macrophage-islet (VMI) organoids. VMI organoids exhibited enhanced marker expression and function in both β cells and endothelial cells compared with separately cultured cells. Notably, proinflammatory macrophages within VMI organoids induced β cell pyroptosis. Mechanistic investigations highlighted TNFSF12-TNFRSF12A involvement in proinflammatory-macrophage-mediated β cell pyroptosis. This study established hPSC-derived VMI organoids as a valuable tool for studying immune-cell-mediated host damage and uncovered the mechanism of β cell damage during viral exposure.

Human Vascularized Macrophage-Islet Organoids to Model Immune-Mediated Pancreatic β cell Pyroptosis upon Viral Infection

There is a paucity of human models to study immune-mediated host damage. Here, we utilized the GeoMx spatial multi-omics platform to analyze immune cell changes in COVID-19 pancreatic autopsy samples, revealing an accumulation of proinflammatory macrophages. Single cell RNA-seq analysis of human islets exposed to SARS-CoV-2 or Coxsackievirus B4 (CVB4) viruses identified activation of proinflammatory macrophages and β cell pyroptosis. To distinguish viral versus proinflammatory macrophage-mediated β cell pyroptosis, we developed human pluripotent stem cell (hPSC)-derived vascularized macrophage-islet (VMI) organoids. VMI organoids exhibited enhanced marker expression and function in both β cells and endothelial cells compared to separately cultured cells. Notably, proinflammatory macrophages within VMI organoids induced β cell pyroptosis. Mechanistic investigations highlighted TNFSF12-TNFRSF12A involvement in proinflammatory macrophage-mediated β cell pyroptosis. This study established hPSC-derived VMI organoids as a valuable tool for studying immune cell-mediated host damage and uncovered mechanism of β cell damage during viral exposure.

Compartmentalization of the inflammatory response during bacterial sepsis and severe COVID-19

Acute infections cause local and systemic disorders which can lead in the most severe forms to multi-organ failure and eventually to death. The host response to infection encompasses a large spectrum of reactions with a concomitant activation of the so-called inflammatory response aimed at fighting the infectious agent and removing damaged tissues or cells, and the anti-inflammatory response aimed at controlling inflammation and initiating the healing process. Fine-tuning at the local and systemic levels is key to preventing local and remote injury due to immune system activation. Thus, during bacterial sepsis and Coronavirus disease 2019 (COVID-19), concomitant systemic and compartmentalized pro-inflammatory and compensatory anti-inflammatory responses are occurring. Immune cells (e.g., macrophages, neutrophils, natural killer cells, and T-lymphocytes), as well as endothelial cells, differ from one compartment to another and contribute to specific organ responses to sterile and microbial insult. Furthermore, tissue-specific microbiota influences the local and systemic response. A better understanding of the tissue-specific immune status, the organ immunity crosstalk, and the role of specific mediators during sepsis and COVID-19 can foster the development of more accurate biomarkers for better diagnosis and prognosis and help to define appropriate host-targeted treatments and vaccines in the context of precision medicine.

Spatial Transcriptomics: A Powerful Tool in Disease Understanding and Drug Discovery

Recent advancements in modern science have provided robust tools for drug discovery. The rapid development of transcriptome sequencing technologies has given rise to single-cell transcriptomics and single-nucleus transcriptomics, increasing the accuracy of sequencing and accelerating the drug discovery process. With the evolution of single-cell transcriptomics, spatial transcriptomics (ST) technology has emerged as a derivative approach. Spatial transcriptomics has emerged as a hot topic in the field of omics research in recent years; it not only provides information on gene expression levels but also offers spatial information on gene expression. This technology has shown tremendous potential in research on disease understanding and drug discovery. In this article, we introduce the analytical strategies of spatial transcriptomics and review its applications in novel target discovery and drug mechanism unravelling. Moreover, we discuss the current challenges and issues in this research field that need to be addressed. In conclusion, spatial transcriptomics offers a new perspective for drug discovery.

Distinct lung cell signatures define the temporal evolution of diffuse alveolar damage in fatal COVID-19

BACKGROUND

Lung damage in severe COVID-19 is highly heterogeneous however studies with dedicated spatial distinction of discrete temporal phases of diffuse alveolar damage (DAD) and alternate lung injury patterns are lacking. Existing studies have also not accounted for progressive airspace obliteration in cellularity estimates. We used an imaging mass cytometry (IMC) analysis with an airspace correction step to more accurately identify the cellular immune response that underpins the heterogeneity of severe COVID-19 lung disease.

METHODS

Lung tissue was obtained at post-mortem from severe COVID-19 deaths. Pathologist-selected regions of interest (ROIs) were chosen by light microscopy representing the patho-evolutionary spectrum of DAD and alternate disease phenotypes were selected for comparison. Architecturally normal SARS-CoV-2-positive lung tissue and tissue from SARS-CoV-2-negative donors served as controls. ROIs were stained for 40 cellular protein markers and ablated using IMC before segmented cells were classified. Cell populations corrected by ROI airspace and their spatial relationships were compared across lung injury patterns.

FINDINGS

Forty patients (32M:8F, age: 22-98), 345 ROIs and >900k single cells were analysed. DAD progression was marked by airspace obliteration and significant increases in mononuclear phagocytes (MnPs), T and B lymphocytes and significant decreases in alveolar epithelial and endothelial cells. Neutrophil populations proved stable overall although several interferon-responding subsets demonstrated expansion. Spatial analysis revealed immune cell interactions occur prior to microscopically appreciable tissue injury.

INTERPRETATION

The immunopathogenesis of severe DAD in COVID-19 lung disease is characterised by sustained increases in MnPs and lymphocytes with key interactions occurring even prior to lung injury is established.

FUNDING

UK Research and Innovation/Medical Research Council through the UK Coronavirus Immunology Consortium, Barbour Foundation, General Sir John Monash Foundation, Newcastle University, JGW Patterson Foundation, Wellcome Trust.

Sarcoidosis-related autoimmune inflammation in COVID-19 convalescent patients

Currently, there are a large number of reports about the development of autoimmune conditions after COVID-19. Also, there have been cases of sarcoid-like granulomas in convalescents as a part of the post-COVID-19 syndrome. Since one of the etiological theories of sarcoidosis considers it to be an autoimmune disease, we decided to study changes in the adaptive humoral immune response in sarcoidosis and SARS-CoV-2 infection and to find out whether COVID-19 can provoke the development of sarcoidosis. This review discusses histological changes in lymphoid organs in sarcoidosis and COVID-19, changes in B cell subpopulations, T-follicular helper cells (Tfh), and T-follicular regulatory cells (Tfr), and analyzes various autoantibodies detected in these pathologies. Based on the data studied, we concluded that SARS-CoV-2 infection may cause the development of autoimmune pathologies, in particular contributing to the onset of sarcoidosis in convalescents.

Single cell spatial analysis reveals inflammatory foci of immature neutrophil and CD8 T cells in COVID-19 lungs

Single cell spatial interrogation of the immune-structural interactions in COVID -19 lungs is challenging, mainly because of the marked cellular infiltrate and architecturally distorted microstructure. To address this, we develop a suite of mathematical tools to search for statistically significant co-locations amongst immune and structural cells identified using 37-plex imaging mass cytometry. This unbiased method reveals a cellular map interleaved with an inflammatory network of immature neutrophils, cytotoxic CD8 T cells, megakaryocytes and monocytes co-located with regenerating alveolar progenitors and endothelium. Of note, a highly active cluster of immature neutrophils and CD8 T cells, is found spatially linked with alveolar progenitor cells, and temporally with the diffuse alveolar damage stage. These findings offer further insights into how immune cells interact in the lungs of severe COVID-19 disease. We provide our pipeline [Spatial Omics Oxford Pipeline (SpOOx)] and visual-analytical tool, Multi-Dimensional Viewer (MDV) software, as a resource for spatial analysis.

SARS-CoV-2 niches in human placenta revealed by spatial transcriptomics

BACKGROUND

Functional placental niches are presumed to spatially separate maternal-fetal antigens and restrict the vertical transmission of pathogens. We hypothesized a high-resolution map of placental transcription could provide direct evidence for niche microenvironments with unique functions and transcription profiles.

METHODS

We utilized Visium Spatial Transcriptomics paired with H&E staining to generate 17,927 spatial transcriptomes. By integrating these spatial transcriptomes with 273,944 placental single-cell and single-nuclei transcriptomes, we generated an atlas composed of at least 22 subpopulations in the maternal decidua, fetal chorionic villi, and chorioamniotic membranes.

FINDINGS

Comparisons of placentae from uninfected healthy controls (n = 4) with COVID-19 asymptomatic (n = 4) and symptomatic (n = 5) infected participants demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection in syncytiotrophoblasts occurred in both the presence and the absence of maternal clinical disease. With spatial transcriptomics, we found that the limit of detection for SARS-CoV-2 was 1/7,000 cells, and placental niches without detectable viral transcripts were unperturbed. In contrast, niches with high SARS-CoV-2 transcript levels were associated with significant upregulation in pro-inflammatory cytokines and interferon-stimulated genes, altered metallopeptidase signaling (TIMP1), with coordinated shifts in macrophage polarization, histiocytic intervillositis, and perivillous fibrin deposition. Fetal sex differences in gene expression responses to SARS-CoV-2 were limited, with confirmed mapping limited to the maternal decidua in males.

CONCLUSIONS

High-resolution placental transcriptomics with spatial resolution revealed dynamic responses to SARS-CoV-2 in coordinate microenvironments in the absence and presence of clinically evident disease.

FUNDING

This work was supported by the NIH (R01HD091731 and T32-HD098069), NSF (2208903), the Burroughs Welcome Fund and the March of Dimes Preterm Birth Research Initiatives, and a Career Development Award from the American Society of Gene and Cell Therapy.

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.

Vaccination increased host antiviral gene expression and reduced COVID-19 severity during the Omicron variant outbreak in Fuyang City, China

BACKGROUND

The differences in host antiviral gene expression and disease severity between vaccinated and non-vaccinated coronavirus disease 2019 (COVID-19) patients are not well characterized. We sought to compare the clinical characteristics and host antiviral gene expression patterns of vaccinated and non-vaccinated cohorts at the Second People's Hospital of Fuyang City.

METHODS

In this case-control study, we retrospectively analyzed 113 vaccinated patients with a COVID-19 Omicron variant infection, 46 non-vaccinated COVID-19 patients, and 24 healthy subjects (no history of COVID-19) recruited from the Second People's Hospital of Fuyang City. Blood samples were collected from each study participant for RNA extraction and PCR. We compared host antiviral gene expression profiles between healthy controls and COVID-19 patients who were either vaccinated or non-vaccinated at the time of infection.

RESULTS

In the vaccinated group, most patients were asymptomatic, with only 42.9 % of patients developing fever. Notably, no patients had extrapulmonary organ damage. In contrast, 21.4 % of patients in the non-vaccinated group developed severe/critical (SC) disease and 78.6 % had mild/moderate (MM) disease, with fever occurring in 74.2 % patients. We found that Omicron infection in COVID-19 vaccinated patients was associated with significantly increased expression of several important host antiviral genes including IL12B, IL13, CXCL11, CXCL9, IFNA2, IFNA1, IFNγ, and TNFα.

CONCLUSION

Vaccinated patients infected with the Omicron variant were mostly asymptomatic. In contrast, non-vaccinated patients frequently developed SC or MM disease. Older patients with SC COVID-19 also had a higher occurrence of mild liver dysfunction. Omicron infection in COVID-19 vaccinated patients was associated with the activation of key host antiviral genes and thus may play a role in reducing disease severity.

Mendelian randomization analysis identified tumor necrosis factor as being associated with severe COVID-19

Background: Observational studies have shown that anti-tumor necrosis factor (TNF) therapy may be beneficial for patients with coronavirus disease 2019 (COVID-19). Nevertheless, because of the methodological restrictions of traditional observational studies, it is a challenge to make causal inferences. This study involved a two-sample Mendelian randomization analysis to investigate the causal link between nine TNFs and COVID-19 severity using publicly released genome-wide association study summary statistics. Methods: Summary statistics for nine TNFs (21,758 cases) were obtained from a large-scale genome-wide association study. Correlation data between single-nucleotide polymorphisms and severe COVID-19 (18,152 cases vs. 1,145,546 controls) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by inverse variance-weighted (IVW), MR-Egger, and weighted median methods. Sensitivity tests were conducted to assess the validity of the causal relationship. Results: Genetically predicted TNF receptor superfamily member 6 (FAS) positively correlated with the severity of COVID-19 (IVW, odds ratio = 1.10, 95% confidence interval = 1.01-1.19, p = 0.026), whereas TNF receptor superfamily member 5 (CD40) was protective against severe COVID-19 (IVW, odds ratio = 0.92, 95% confidence interval = 0.87-0.97, p = 0.002). Conclusion: Genetic evidence from this study supports that the increased expression of FAS is associated with the risk of severe COVID-19 and that CD40 may have a potential protective effect against COVID-19.

Host Expression Profiling From Diagnostic Coronavirus Disease 2019 Swabs Associates Upper Respiratory Tract Immune Responses With Radiologic Lung Pathology and Clinical Severity

Background

COVID-19 presents with a breadth of symptomatology including a spectrum of clinical severity requiring intensive care unit (ICU) admission. We investigated the mucosal host gene response at the time of gold standard COVID-19 diagnosis using clinical surplus RNA from upper respiratory tract swabs.

Methods

Host response was evaluated by RNA-sequencing, and transcriptomic profiles of 44 unvaccinated patients including outpatients and in-patients with varying levels of oxygen supplementation were included. Additionally, chest X-rays were reviewed and scored for patients in each group.

Results

Host transcriptomics revealed significant changes in the immune and inflammatory response. Patients destined for the ICU were distinguished by the significant upregulation of immune response pathways and inflammatory chemokines, including cxcl2 which has been linked to monocyte subsets associated with COVID-19 related lung damage. In order to temporally associate gene expression profiles in the upper respiratory tract at diagnosis of COVID-19 with lower respiratory tract sequalae, we correlated our findings with chest radiography scoring, showing nasopharygeal or mid-turbinate sampling can be a relevant surrogate for downstream COVID-19 pneumonia/ICU severity.

Conclusions

This study demonstrates the potential and relevance for ongoing study of the mucosal site of infection of SARS-CoV-2 using a single sampling that remains standard of care in hospital settings. We highlight also the archival value of high quality clinical surplus specimens, especially with rapidly evolving COVID-19 variants and changing public health/vaccination measures.

Classification of COVID-19 Patients into Clinically Relevant Subsets by a Novel Machine Learning Pipeline Using Transcriptomic Features

The persistent impact of the COVID-19 pandemic and heterogeneity in disease manifestations point to a need for innovative approaches to identify drivers of immune pathology and predict whether infected patients will present with mild/moderate or severe disease. We have developed a novel iterative machine learning pipeline that utilizes gene enrichment profiles from blood transcriptome data to stratify COVID-19 patients based on disease severity and differentiate severe COVID cases from other patients with acute hypoxic respiratory failure. The pattern of gene module enrichment in COVID-19 patients overall reflected broad cellular expansion and metabolic dysfunction, whereas increased neutrophils, activated B cells, T-cell lymphopenia, and proinflammatory cytokine production were specific to severe COVID patients. Using this pipeline, we also identified small blood gene signatures indicative of COVID-19 diagnosis and severity that could be used as biomarker panels in the clinical setting.