The spatial landscape of lung pathology during COVID-19 progression

Transcriptomics in the Study of Antiviral Innate Immunity

Transcriptomics is an extremely important area of molecular biology and is a powerful tool for studying all RNA molecules in an organism. Conventional transcriptomic technologies include microarrays and RNA sequencing, and the rapid development of single-cell sequencing and spatial transcriptomics in recent years has provided an enormous scope for research in this field. This chapter describes the application, significance, and experimental procedures of a variety of transcriptomic technologies in antiviral natural immunity.

A novel GFP-based strategy to quantitate cellular spatial associations in HSV-1 viral pathogenesis

Periodic reactivation of herpes simplex virus type 1 (HSV-1) triggers immune responses that result in corneal scarring (CS), known as herpes stromal keratitis (HSK). Despite considerable research, fully understanding HSK and eliminating it remains challenging due to a lack of comprehensive analysis of HSV-1-infected immune cells in both corneas and trigeminal ganglia (TG). We engineered a recombinant HSV-1 expressing green fluorescent protein (GFP) in the virulent McKrae virus strain that does not require corneal scarification for efficient virus replication (GFP-McKrae). Next-generation sequencing (NGS) analysis, along with in vitro and in vivo assays, showed that GFP-McKrae virus was similar to WT-McKrae virus. Furthermore, corneal cells infected with GFP-McKrae were quantitatively analyzed using image mass cytometry (IMC). The single-cell reconstruction data generated cellular maps of corneas based on the expression of 25 immune cell markers in GFP-McKrae-infected mice. Corneas from mock control mice showed the presence of T cells and macrophages, whereas corneas from GFP-McKrae-infected mice on days 3 and 5 post-infection (PI) exhibited increased immune cells. Notably, on day 3 PI, increased GFP expression was observed in closely situated clusters of DCs, macrophages, and epithelial cells. By day 5 PI, macrophages and T cells became prominent. Finally, immunostaining methods detected HSV-1 or GFP and gD proteins in latently infected TG. This study presents a valuable strategy for identifying cellular spatial associations in viral pathogenesis and holds promise for future therapeutic applications.IMPORTANCEThe goal of this study was to establish quantitative approaches to analyze immune cell markers in HSV-1-infected intact corneas and trigeminal ganglia from primary and latently infected mice. This allowed us to define spatial and temporal interactions between specific immune cells and their potential roles in virus replication and latency. To accomplish this important goal, we took advantage of the utility of GFP-McKrae virus as a valuable research tool while also highlighting its potential to uncover previously unrecognized cell types that play pivotal roles in HSV-1 replication and latency. Such insights will pave the way for developing targeted therapeutic approaches to tackle HSV-1 infections more effectively.

Single-cell spatiotemporal analysis of the lungs reveals Slamf9+ macrophages involved in viral clearance and inflammation resolution

How the lung achieves immune homeostasis after a pulmonary infection is not fully understood. Here, we analyzed the spatiotemporal changes in the lungs over a 2-week natural recovery from severe pneumonia in a Syrian hamster model of SARS-CoV-2 infection. We find that SARS-CoV-2 infects multiple cell types and causes massive cell death at the early stage, including alveolar macrophages. We identify a group of monocyte-derived Slamf9+ macrophages, which are induced after SARS-CoV-2 infection and resistant to impairment caused by SARS-CoV-2. Slamf9+ macrophages contain SARS-CoV-2, recruit and interact with Isg12+Cst7+ neutrophils to clear the viruses. After viral clearance, Slamf9+ macrophages differentiate into Trem2+ and Fbp1+ macrophages, contributing to inflammation resolution at the late stage, and finally replenish alveolar macrophages. These findings are validated in a SARS-CoV-2-infected hACE2 mouse model and confirmed with publicly available human autopsy single-cell RNA-seq data, demonstrating the potential role of Slamf9+ macrophages and their coordination with neutrophils in post-injury tissue repair and inflammation resolution.

Single-cell spatiotemporal analysis reveals alveolar dendritic cell-T cell immunity hubs defending against pulmonary infection

How immune cells are spatiotemporally coordinated in the lung to effectively monitor, respond to, and resolve infection and inflammation in primed form needs to be fully illustrated. Here we apply immunocartography, a high-resolution technique that integrates spatial and single-cell RNA sequencing (scRNA-seq) through deconvolution and co-localization analyses, to the SARS-CoV-2-infected Syrian hamster model. We generate a comprehensive transcriptome map of the whole process of pulmonary infection from physiological condition, infection initiation, severe pneumonia to natural recovery at organ scale and single-cell resolution, with 142,965 cells and 45 lung lobes from 25 hamsters at 5 time points. Integrative analysis identifies that alveolar dendritic cell-T cell immunity hubs, where Ccr7+Ido1+ dendritic cells, Cd160+Cd8+ T cells, and Tnfrsf4+Cd4+ T cells physiologically co-localize, rapidly expand during SARS-CoV-2 infection, eliminate SARS-CoV-2 with the aid of Slamf9+ macrophages, and then restore to physiological levels after viral clearance. We verify the presence of these cell subpopulations in the immunity hubs in normal and SARS-CoV-2-infected hACE2 mouse models, as well as in publicly available human scRNA-seq datasets, demonstrating the potential broad relevance of our findings in lung immunity.

FPR1 signaling aberrantly regulates S100A8/A9 production by CD14+FCN1hi macrophages and aggravates pulmonary pathology in severe COVID-19

Excessive alarmins S100A8/A9 escalate the inflammation and even exacerbate immune-driven thrombosis and multi-organ damage. However, the regulatory mechanisms of S100A8/A9 expression in infectious diseases remain unclear. In this study, high-dimensional transcriptomic data analyses revealed a high proportion of CD14+FCN1hi macrophages within the pulmonary niche post-severe SARS-CoV-2 infection. By constructing the S100-coexpression gene list and supervised module scoring, we found that CD14+FCN1hi macrophages presented the highest scores of alarmin S100, and possibly served as the trigger and amplifier of inflammation in severe COVID-19. These CD14+FCN1hi cells lacked the positive regulatory activity of transcription factor PPARγ, and lost their differentiation ability towards mature macrophages. Ex vivo experiments further validated that the epithelial cells with high ORF-3a expression promoted the expression and secretion of S100A8/A9 through ANXA1/SAA1-FPR1 signaling. S100A8/A9 heterodimers, as well as the co-localization of S100A8/A9 with microtubules, were both diminished by the FPR1 inhibitor. Phospho-kinase protein array indicated that STAT3 promoted transcription, and PLC-γ and ERK1/2 pathways were involved in the hetero-dimerization and unconventional secretion of S100A8/A9. Our study highlights the pivotal role of FPR1 signaling in the excessive production of S100A8/A9 and provides a promising target for the prevention and control of severe COVID-19 and post-acute COVID-19 sequelae.

A spatially resolved single-cell lung atlas integrated with clinical and blood signatures distinguishes COVID-19 disease trajectories

COVID-19 is characterized by a broad range of symptoms and disease trajectories. Understanding the correlation between clinical biomarkers and lung pathology during acute COVID-19 is necessary to understand its diverse pathogenesis and inform more effective treatments. Here, we present an integrated analysis of longitudinal clinical parameters, peripheral blood markers, and lung pathology in 142 Brazilian patients hospitalized with COVID-19. We identified core clinical and peripheral blood signatures differentiating disease progression between patients who recovered from severe disease compared with those who succumbed to the disease. Signatures were heterogeneous among fatal cases yet clustered into two patient groups: "early death" (<15 days until death) and "late death" (>15 days). Progression to early death was characterized systemically and in lung histopathological samples by rapid endothelial and myeloid activation and the presence of thrombi associated with SARS-CoV-2+ macrophages. In contrast, progression to late death was associated with fibrosis, apoptosis, and SARS-CoV-2+ epithelial cells in postmortem lung tissue. In late death cases, cytotoxicity, interferon, and T helper 17 (TH17) signatures were only detectable in the peripheral blood after 2 weeks of hospitalization. Progression to recovery was associated with higher lymphocyte counts, TH2 responses, and anti-inflammatory-mediated responses. By integrating antemortem longitudinal blood signatures and spatial single-cell lung signatures from postmortem lung samples, we defined clinical parameters that could be used to help predict COVID-19 outcomes.

Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases

Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases-centered around the identification of biomarkers and the elucidation of disease mechanisms-are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.

Postinfectious Pulmonary Complications: Establishing Research Priorities to Advance the Field: An Official American Thoracic Society Workshop Report

Continued improvements in the treatment of pulmonary infections have paradoxically resulted in a growing challenge of individuals with postinfectious pulmonary complications (PIPCs). PIPCs have been long recognized after tuberculosis, but recent experiences such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic have underscored the importance of PIPCs following other lower respiratory tract infections. Independent of the causative pathogen, most available studies of pulmonary infections focus on short-term outcomes rather than long-term morbidity among survivors. In this document, we establish a conceptual scope for PIPCs with discussion of globally significant pulmonary pathogens and an examination of how these pathogens can damage different components of the lung, resulting in a spectrum of PIPCs. We also review potential mechanisms for the transition from acute infection to PIPC, including the interplay between pathogen-mediated injury and aberrant host responses, which together result in PIPCs. Finally, we identify cross-cutting research priorities for the field to facilitate future studies to establish the incidence of PIPCs, define common mechanisms, identify therapeutic strategies, and ultimately reduce the burden of morbidity in survivors of pulmonary infections.

Host-pathogen interactions from a metabolic perspective: methods of investigation

Metabolism shapes immune homeostasis in health and disease. This review presents the range of methods that are currently available to investigate the dialog between metabolism and immunity at the systemic, tissue and cellular levels, particularly during infection.

Fibrin drives thromboinflammation and neuropathology in COVID-19

Life-threatening thrombotic events and neurological symptoms are prevalent in COVID-19 and are persistent in patients with long COVID experiencing post-acute sequelae of SARS-CoV-2 infection1-4. Despite the clinical evidence1,5-7, the underlying mechanisms of coagulopathy in COVID-19 and its consequences in inflammation and neuropathology remain poorly understood and treatment options are insufficient. Fibrinogen, the central structural component of blood clots, is abundantly deposited in the lungs and brains of patients with COVID-19, correlates with disease severity and is a predictive biomarker for post-COVID-19 cognitive deficits1,5,8-10. Here we show that fibrin binds to the SARS-CoV-2 spike protein, forming proinflammatory blood clots that drive systemic thromboinflammation and neuropathology in COVID-19. Fibrin, acting through its inflammatory domain, is required for oxidative stress and macrophage activation in the lungs, whereas it suppresses natural killer cells, after SARS-CoV-2 infection. Fibrin promotes neuroinflammation and neuronal loss after infection, as well as innate immune activation in the brain and lungs independently of active infection. A monoclonal antibody targeting the inflammatory fibrin domain provides protection from microglial activation and neuronal injury, as well as from thromboinflammation in the lung after infection. Thus, fibrin drives inflammation and neuropathology in SARS-CoV-2 infection, and fibrin-targeting immunotherapy may represent a therapeutic intervention for patients with acute COVID-19 and long COVID.

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.

A Novel Human Extravascular Monocyte Subset with Antiviral Functions Is Crucial for Resolving Lung Tissue Infection

The recurring emergence of novel respiratory viruses has highlighted our poor understanding of the human immune mechanisms governing the resolution of lung infection in an immunologically naïve context. Using SARS-CoV-2 as a prototypical emerging respiratory virus, we leveraged mice co-engrafted with a genetically matched fetal lung xenograft (fLX) and a human immune system (BLT-L mice) to investigate such mechanisms. While BLT-L mice effectively resolve SARS-CoV-2 infection following acute viral replication in fLX, viral clearance is robustly abrogated through systemic depletion of CD4+, but not CD3+ or CD8+ cells, resulting in persistent infection. Leveraging single-cell transcriptomics to uncover the CD4-expressing subsets driving infection resolution, we identified a novel subset of lung extravascular inflammatory monocytes (ExiMO) with antiviral functions. ExiMO are the dominant CD163-expressing myeloid population emerging in fLX upon acute infection and derive from recruited circulating CD4+ monocytes. They are highly enriched in viral RNA and elicit a robust antiviral response before vanishing from tissues when infection resolves. Notably, systemic CD4+ cell depletion results in impaired recruitment of CD163+ cells into fLX and leads to a state of immune tolerance and chronic infection defined by the absence of ExiMO antiviral responses. Together, our study uncovers ExiMO as major sentinels driving SARS-CoV-2 infection resolution in human lung tissues without pre-existing immunity. This work expands our understanding of lung extravascular monocytes and unravels novel facets of the cellular determinants governing our vulnerability to viral respiratory pathogens.

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.

Communication between alveolar macrophages and fibroblasts via the TNFSF12-TNFRSF12A pathway promotes pulmonary fibrosis in severe COVID-19 patients

BACKGROUND

Severe COVID-19 infection has been associated with the development of pulmonary fibrosis, a condition that significantly affects patient prognosis. Understanding the underlying cellular communication mechanisms contributing to this fibrotic process is crucial.

OBJECTIVE

In this study, we aimed to investigate the role of the TNFSF12-TNFRSF12A pathway in mediating communication between alveolar macrophages and fibroblasts, and its implications for the development of pulmonary fibrosis in severe COVID-19 patients.

METHODS

We conducted single-cell RNA sequencing (scRNA-seq) analysis using lung tissue samples from severe COVID-19 patients and healthy controls. The data was processed, analyzed, and cell types were annotated. We focused on the communication between alveolar macrophages and fibroblasts and identified key signaling pathways. In vitro experiments were performed to validate our findings, including the impact of TNFRSF12A silencing on fibrosis reversal.

RESULTS

Our analysis revealed that in severe COVID-19 patients, alveolar macrophages communicate with fibroblasts primarily through the TNFSF12-TNFRSF12A pathway. This communication pathway promotes fibroblast proliferation and expression of fibrotic factors. Importantly, silencing TNFRSF12A effectively reversed the pro-proliferative and pro-fibrotic effects of alveolar macrophages.

CONCLUSION

The TNFSF12-TNFRSF12A pathway plays a central role in alveolar macrophage-fibroblast communication and contributes to pulmonary fibrosis in severe COVID-19 patients. Silencing TNFRSF12A represents a potential therapeutic strategy for mitigating fibrosis in severe COVID-19 lung disease.

Integrative Transcriptomic and Single-Cell Protein Characterization of Colorectal Carcinoma Delineates Distinct Tumor Immune Microenvironments Associated with Overall Survival

Colorectal carcinoma (CRC) is a heterogeneous group of tumors with varying therapeutic response and prognosis, and evidence suggests the tumor immune microenvironment (TIME) plays a pivotal role. Using advanced molecular and spatial biology technologies, we aimed to evaluate the TIME in patients with CRC to determine whether specific alterations in the immune composition correlated with prognosis. We identified primary and metastatic tumor samples from 31 consented patients, which were profiled with whole-exome sequencing and bulk RNA-seq. Immune cell deconvolution followed by gene set enrichment analysis and unsupervised clustering was performed. A subset of tumors underwent in situ analysis of the TIME spatial composition at single-cell resolution through Imaging Mass Mass Cytometry. Gene set enrichment analysis revealed two distinct groups of advanced CRC, one with an immune activated phenotype and the other with a suppressed immune microenvironment. The activated TIME phenotype contained increased Th1 cells, activated dendritic cells, tertiary lymphoid structures, and higher counts of CD8+ T cells whereas the inactive or suppressed TIME contained increased macrophages and a higher M2/M1 ratio. Our findings were further supported by RNA-seq data analysis from the TCGA CRC database, in which unsupervised clustering also identified two separate groups. The immunosuppressed CRC TIME had a lower overall survival probability (HR 1.66, p=0.007). This study supports the pertinent role of the CRC immune microenvironment in tumor progression and patient prognosis. We characterized the immune cell composition to better understand the complexity and vital role that immune activity states of the TIME play in determining patient outcome.

Mass spectrometry imaging for spatially resolved multi-omics molecular mapping

The recent upswing in the integration of spatial multi-omics for conducting multidimensional information measurements is opening a new chapter in biological research. Mapping the landscape of various biomolecules including metabolites, proteins, nucleic acids, etc., and even deciphering their functional interactions and pathways is believed to provide a more holistic and nuanced exploration of the molecular intricacies within living systems. Mass spectrometry imaging (MSI) stands as a forefront technique for spatially mapping the metabolome, lipidome, and proteome within diverse tissue and cell samples. In this review, we offer a systematic survey delineating different MSI techniques for spatially resolved multi-omics analysis, elucidating their principles, capabilities, and limitations. Particularly, we focus on the advancements in methodologies aimed at augmenting the molecular sensitivity and specificity of MSI; and depict the burgeoning integration of MSI-based spatial metabolomics, lipidomics, and proteomics, encompassing the synergy with other imaging modalities. Furthermore, we offer speculative insights into the potential trajectory of MSI technology in the future.

Rujin Jiedu decoction protects against influenza virus infection by modulating gut microbiota

Background

Rujin Jiedu decoction (RJJDD) is a classical prescription of Traditional Chinese Medicine that has long been applied to treat pneumonia caused by external infection, but whether and how it benefits influenza virus therapy remains largely unclear. The aim of this study was to investigate the anti-inflammatory effect of RJJDD on the mouse model of influenza and to explore its potential mechanism.

Methods

The mice were mock-infected with PBS or infected with PR8 virus followed by treatment with RJJDD or antiviral oseltamivir. The weight loss and morbidity of mice were monitored daily. Network pharmacology is used to explore the potential pathways that RJJDD may modulate. qRT-PCR and ELISA were performed to assess the expression of inflammatory cytokines in the lung tissue and macrophages. The intestinal feces were collected for 16S rDNA sequencing to assess the changes in gut microbiota.

Results

We demonstrate that RJJDD protects against IAV-induced pneumonia. Comprehensive network pharmacology analyses of the Mass Spec-identified components of RJJDD suggest that RJJDD may act through down-regulating key signaling pathways producing inflammatory cytokines, which was experimentally confirmed by cytokine expression analysis in IAV-infected mouse lung tissues and IAV single-strand RNA mimic R837-induced macrophages. Furthermore, gut microbiota analysis indicates that RJJDD prevented IAV-induced dysbiosis of host intestinal flora, thereby offering a mechanistic explanation for RJJDD's efficacy in influenza pneumonia.

Conclusion

This study defines a previously uncharacterized role for RJJDD in protecting against influenza likely by maintaining homeostasis of gut microbiota, and provides a new therapeutic option for severe influenza.

Building a human lung from pluripotent stem cells to model respiratory viral infections

To protect against the constant threat of inhaled pathogens, the lung is equipped with cellular defenders. In coordination with resident and recruited immune cells, this defence is initiated by the airway and alveolar epithelium following their infection with respiratory viruses. Further support for viral clearance and infection resolution is provided by adjacent endothelial and stromal cells. However, even with these defence mechanisms, respiratory viral infections are a significant global health concern, causing substantial morbidity, socioeconomic losses, and mortality, underlining the need to develop effective vaccines and antiviral medications. In turn, the identification of new treatment options for respiratory infections is critically dependent on the availability of tractable in vitro experimental models that faithfully recapitulate key aspects of lung physiology. For such models to be informative, it is important these models incorporate human-derived, physiologically relevant versions of all cell types that normally form part of the lungs anti-viral response. This review proposes a guideline using human induced pluripotent stem cells (iPSCs) to create all the disease-relevant cell types. iPSCs can be differentiated into lung epithelium, innate immune cells, endothelial cells, and fibroblasts at a large scale, recapitulating in vivo functions and providing genetic tractability. We advocate for building comprehensive iPSC-derived in vitro models of both proximal and distal lung regions to better understand and model respiratory infections, including interactions with chronic lung diseases.

Altered spike IgG Fc N-linked glycans are associated with hyperinflammatory state in adult COVID and Multisystem Inflammatory Syndrome in Children

Background

Severe COVID and multisystem inflammatory syndrome (MIS-C) are characterized by excessive inflammatory cytokines/chemokines. In adults, disease severity is associated with SARS-CoV-2-specific IgG Fc afucosylation, which induces pro-inflammatory cytokine secretion from innate immune cells. This study aimed to define spike IgG Fc glycosylation following SARS-CoV-2 infection in adults and children and following SARS-CoV-2 vaccination in adults and the relationships between glycan modifications and cytokine/chemokine levels.

Methods

We analyzed longitudinal (n=146) and cross-sectional (n=49) serum/plasma samples from adult and pediatric COVID patients, MIS-C patients, adult vaccinees, and adult and pediatric healthy controls. We developed methods for characterizing bulk and spike IgG Fc glycosylation by capillary electrophoresis (CE) and measured levels of ten inflammatory cytokines/chemokines by multiplexed ELISA.

Results

Spike IgG were more afucosylated than bulk IgG during acute adult COVID and MIS-C. We observed an opposite trend following vaccination, but it was not significant. Spike IgG were more galactosylated and sialylated and less bisected than bulk IgG during adult COVID, with similar trends observed during pediatric COVID/MIS-C and following SARS-CoV-2 vaccination. Spike IgG glycosylation changed with time following adult COVID or vaccination. Afucosylated spike IgG exhibited inverse and positive correlations with inflammatory markers in MIS-C and following vaccination, respectively; galactosylated and sialylated spike IgG inversely correlated with pro-inflammatory cytokines in adult COVID and MIS-C; and bisected spike IgG positively correlated with inflammatory cytokines/chemokines in multiple groups.

Conclusions

We identified previously undescribed relationships between spike IgG glycan modifications and inflammatory cytokines/chemokines that expand our understanding of IgG glycosylation changes that may impact COVID and MIS-C immunopathology.

Neuropathogenesis of SARS-CoV-2 in human neuronal, microglial and glial cells

Neurological complications, both acute and chronic, are reported commonly in COVID-19 affected individuals. In this context, the understanding of pathogenesis of SARS-CoV-2 in specific cells of central nervous system (CNS) origin is relevant. The present study explores infection biology of a clinical isolate of SARS-CoV-2 in human cell lines of neural origin such as the glioblastoma (U87-MG), neuroblastoma (SHSY5Y) and microglia (C20). Despite showing clear evidence of infection by immunofluorescence with an anti-spike protein antibody, all the three neural cell lines were observed to be highly restrictive to the replication of the infecting virus. While the U87-MG glioblastoma cells demonstrated no cytopathic effects and a low viral titre with no signs of replication, the SHSY5Y neuroblastoma cells exhibited cytopathic effects with bleb formation but no evidence of viable virus. The C20 microglial cells showed neither signs of cytopathic effects nor viable virus. Ultrastructural studies demonstrated intracellular virions in infected neural cells. The presence of lipid droplets in infected SHSY5Y cells suggested an impact on host cell metabolism. The decrease in viral RNA levels over time in all the neural cell lines suggested restricted viral replication. In conclusion, this study highlights the limited susceptibility of neural cells to SARS-CoV-2 infection. This reduced permissibility of neural cell lines to SARS-CoV-2 may point to their inherent lower expression of receptors that support viral entry in addition to the intracellular factors that potently inhibit viral replication. The study findings prompt further investigation into the mechanisms of SARS-CoV-2 infection of neural cells.

PI3Kγ inhibition circumvents inflammation and vascular leak in SARS-CoV-2 and other infections

Virulent infectious agents such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and methicillin-resistant Staphylococcus aureus (MRSA) induce tissue damage that recruits neutrophils, monocyte, and macrophages, leading to T cell exhaustion, fibrosis, vascular leak, epithelial cell depletion, and fatal organ damage. Neutrophils, monocytes, and macrophages recruited to pathogen-infected lungs, including SARS-CoV-2-infected lungs, express phosphatidylinositol 3-kinase gamma (PI3Kγ), a signaling protein that coordinates both granulocyte and monocyte trafficking to diseased tissues and immune-suppressive, profibrotic transcription in myeloid cells. PI3Kγ deletion and inhibition with the clinical PI3Kγ inhibitor eganelisib promoted survival in models of infectious diseases, including SARS-CoV-2 and MRSA, by suppressing inflammation, vascular leak, organ damage, and cytokine storm. These results demonstrate essential roles for PI3Kγ in inflammatory lung disease and support the potential use of PI3Kγ inhibitors to suppress inflammation in severe infectious diseases.

Extracellular histones promote TWIK2-dependent potassium efflux and associated NLRP3 activation in alveolar macrophages during sepsis-induced lung injury

BACKGROUND AND AIM

Sepsis-induced acute lung injury (ALI) is a complex and life-threatening condition lacking specific and efficient clinical treatments. Extracellular histones, identified as a novel type of damage-associated molecular patterns, have been implicated in the inflammatory process of ALI. However, further elucidation is needed regarding the precise mechanism through which extracellular histones induce inflammation. The aim of this study was to investigate whether extracellular histones can activate NLRP3 inflammasome-mediated inflammation in alveolar macrophages (AMs) by affecting TWIK2-dependent potassium efflux.

METHODS AND RESULTS

We conducted experiments using cecal ligation and puncture (CLP) C57BL/6 mice and extracellular histone-stimulated LPS-primed MH-S cells. The results demonstrated a significant increase in the levels of extracellular histones in the plasma and bronchoalveolar lavage fluid (BALF) of CLP mice. Furthermore, neutralizing extracellular histone mitigated lung injury and inflammation in CLP-induced ALI mice. In vitro studies confirmed that extracellular histones upregulated the expression of NLRP3 inflammasome activation-related proteins in MH-S cells, and this effect was dependent on increased potassium efflux mediated by the TWIK2 channel on the plasma membrane. Moreover, extracellular histones directly triggered a substantial influx of calcium, leading to increased Rab11 activity and facilitating the trafficking and location of TWIK2 to the plasma membrane.

CONCLUSION

These findings underscore the critical role of extracellular histone-induced upregulation of TWIK2 expression on the plasma membrane of alveolar macrophages (AMs). This upregulation leads to potassium efflux and subsequent activation of the NLRP3 inflammasome, ultimately exacerbating lung inflammation and injury during sepsis.

Cellular pathways and molecular events that shape autoantibody production in COVID-19

A hallmark of COVID-19 is the variety of complications that follow SARS-CoV-2 infection in some patients, and that target multiple organs and tissues. Also remarkable are the associations with several auto-inflammatory disorders and the presence of autoantibodies directed to a vast array of antigens. The processes underlying autoantibody production in COVID-19 have not been completed deciphered. Here, we review mechanisms involved in autoantibody production in COVID-19, multisystem inflammatory syndrome in children, and post-acute sequelae of COVID19. We critically discuss how genomic integrity, loss of B cell tolerance to self, superantigen effects of the virus, and extrafollicular B cell activation could underly autoantibody proaction in COVID-19. We also offer models that may account for the pathogenic roles of autoantibodies in the promotion of inflammatory cascades, thromboembolic phenomena, and endothelial and vascular deregulations.

SARS-CoV-2 infection modifies the transcriptome of the megakaryocytes in the bone marrow

ABSTRACT

Megakaryocytes (MKs), integral to platelet production, predominantly reside in the bone marrow (BM) and undergo regulated fragmentation within sinusoid vessels to release platelets into the bloodstream. Inflammatory states and infections influence MK transcription, potentially affecting platelet functionality. Notably, COVID-19 has been associated with altered platelet transcriptomes. In this study, we investigated the hypothesis that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection could affect the transcriptome of BM MKs. Using spatial transcriptomics to discriminate subpopulations of MKs based on proximity to BM sinusoids, we identified ∼19 000 genes in MKs. Machine learning techniques revealed that the transcriptome of healthy murine BM MKs exhibited minimal differences based on proximity to sinusoid vessels. Furthermore, at peak SARS-CoV-2 viremia, when the disease primarily affected the lungs, MKs were not significantly different from those from healthy mice. Conversely, a significant divergence in the MK transcriptome was observed during systemic inflammation, although SARS-CoV-2 RNA was never detected in the BM, and it was no longer detectable in the lungs. Under these conditions, the MK transcriptional landscape was enriched in pathways associated with histone modifications, MK differentiation, NETosis, and autoimmunity, which could not be explained by cell proximity to sinusoid vessels. Notably, the type I interferon signature and calprotectin (S100A8/A9) were not induced in MKs under any condition. However, inflammatory cytokines induced in the blood and lungs of COVID-19 mice were different from those found in the BM, suggesting a discriminating impact of inflammation on this specific subset of cells. Collectively, our data indicate that a new population of BM MKs may emerge through COVID-19-related pathogenesis.

Interstitial macrophages are a focus of viral takeover and inflammation in COVID-19 initiation in human lung

Early stages of deadly respiratory diseases including COVID-19 are challenging to elucidate in humans. Here, we define cellular tropism and transcriptomic effects of SARS-CoV-2 virus by productively infecting healthy human lung tissue and using scRNA-seq to reconstruct the transcriptional program in "infection pseudotime" for individual lung cell types. SARS-CoV-2 predominantly infected activated interstitial macrophages (IMs), which can accumulate thousands of viral RNA molecules, taking over 60% of the cell transcriptome and forming dense viral RNA bodies while inducing host profibrotic (TGFB1, SPP1) and inflammatory (early interferon response, CCL2/7/8/13, CXCL10, and IL6/10) programs and destroying host cell architecture. Infected alveolar macrophages (AMs) showed none of these extreme responses. Spike-dependent viral entry into AMs used ACE2 and Sialoadhesin/CD169, whereas IM entry used DC-SIGN/CD209. These results identify activated IMs as a prominent site of viral takeover, the focus of inflammation and fibrosis, and suggest targeting CD209 to prevent early pathology in COVID-19 pneumonia. This approach can be generalized to any human lung infection and to evaluate therapeutics.

Pathology of COVID-19 Lung Disease

The pathology of severe COVID-19 lung injury is predominantly diffuse alveolar damage, with other reported patterns including acute fibrinous organizing pneumonia, organizing pneumonia, and bronchiolitis. Lung injury was caused by primary viral injury, exaggerated immune responses, and superinfection with bacteria and fungi. Although fatality rates have decreased from the early phases of the pandemic, persistent pulmonary dysfunction occurs and its pathogenesis remains to be fully elucidated.

Spatial Patterning Analysis of Cellular Ensembles (SPACE) discovers complex spatial organization at the cell and tissue levels

Spatial patterns of cells and other biological elements drive both physiologic and pathologic processes within tissues. While many imaging and transcriptomic methods document tissue organization, discerning these patterns is challenging, especially when they involve multiple elements in complex arrangements. To address this challenge, we present Spatial Patterning Analysis of Cellular Ensembles (SPACE), an R package for analysis of high-plex spatial data. SPACE is compatible with any data collection modality that records values (i.e., categorical cell/structure types or quantitative expression levels) at fixed spatial coordinates (i.e., 2d pixels or 3d voxels). SPACE detects not only broad patterns of co-occurrence but also context-dependent associations, quantitative gradients and orientations, and other organizational complexities. Via a robust information theoretic framework, SPACE explores all possible ensembles of tissue elements - single elements, pairs, triplets, and so on - and ranks the most strongly patterned ensembles. For single images, rankings reflect patterns that differ from random assortment. For sets of images, rankings reflect patterns that differ across sample groups (e.g., genotypes, treatments, timepoints, etc.). Further tools then thoroughly characterize the nature of each pattern for intuitive interpretation. We validate SPACE and demonstrate its advantages using murine lymph node images for which ground truth has been defined. We then use SPACE to detect new patterns across varied datasets, including tumors and tuberculosis granulomas.

CTHRC1: An Emerging Hallmark of Pathogenic Fibroblasts in Lung Fibrosis

Pulmonary fibrosis is a chronic, progressive, irreversible lung disease characterized by fibrotic scarring in the lung parenchyma. This condition involves the excessive accumulation of extracellular matrix (ECM) due to the aberrant activation of myofibroblasts in the alveolar environment. Transforming growth factor beta (TGF-β) signaling is a crucial driver of fibrogenesis because it promotes excessive ECM deposition, thereby leading to scar formation and lung damage. A primary target of TGF-β signaling in fibrosis is Collagen Triple Helix Repeat Containing 1 (CTHRC1), a secreted glycoprotein that plays a pivotal role in ECM deposition and wound repair. TGF-β transcriptionally regulates CTHRC1 in response to tissue injury and controls the wound healing response through functional activity. CTHRC1 may also play an essential role in re-establishing and maintaining tissue homeostasis after wound closure by modulating both the TGF-β and canonical Wnt signaling pathways. This dual function suggests that CTHRC1 regulates tissue remodeling and homeostasis. However, deregulated CTHRC1 expression in pathogenic fibroblasts has recently emerged as a hallmark of fibrosis in multiple organs and tissues. This review highlights recent studies suggesting that CTHRC1 can serve as a diagnostic and prognostic biomarker for fibrosis in idiopathic pulmonary fibrosis, systemic sclerosis, and post-COVID-19 lung fibrosis. Notably, CTHRC1 expression is responsive to antifibrotic drugs that target the TGF-β pathway, such as pirfenidone and bexotegrast, indicating its potential as a biomarker of treatment success. These findings suggest that CTHRC1 may present new opportunities for diagnosing and treating patients with lung fibrosis.

Targeting IL-6 trans-signalling by sgp130Fc attenuates severity in SARS-CoV-2 -infected mice and reduces endotheliopathy

BACKGROUND

SARS-CoV-2 infection is considered as a relapsing inflammatory process with a dysregulation of IL-6 signalling. Classic IL-6 signalling is thought to represent a defence mechanism against pathogens. In contrast, IL-6 trans-signalling has pro-inflammatory effects. In severe COVID-19, therapeutic strategies have focused on global inhibition of IL-6, with controversial results. We hypothesized that specific blockade of IL-6 trans-signalling could inhibit inflammatory response preserving the host defence activity inherent to IL-6 classic signalling.

METHODS

To test the role of the specific IL-6 trans-signalling inhibition by sgp130Fc in short- and long-term consequences of COVID-19, we used the established K18-hACE2 transgenic mouse model. Histological as well as immunohistochemical analysis, and pro-inflammatory marker profiling were performed. To investigate IL-6 trans-signalling in human cells we used primary lung microvascular endothelial cells and fibroblasts in the presence/absence of sgp130Fc.

FINDINGS

We report that targeting IL-6 trans-signalling by sgp130Fc attenuated SARS-CoV-2-related clinical symptoms and mortality. In surviving mice, the treatment caused a significant decrease in lung damage. In vitro, IL-6 trans-signalling induced strong and persisting JAK1/STAT3 activation in endothelial cells and lung fibroblasts with proinflammatory effects, which were attenuated by sgp130Fc. Our data also suggest that in those cells with scant amounts of IL-6R, the induction of gp130 and IL-6 by IL-6:sIL-6R complex sustains IL-6 trans-signalling.

INTERPRETATION

IL-6 trans-signalling fosters progression of COVID-19, and suggests that specific blockade of this signalling mode could offer a promising alternative to mitigate both short- and long-term consequences without affecting the beneficial effects of IL-6 classic signalling. These results have implications for the development of new therapies of lung injury and endotheliopathy in COVID-19.

FUNDING

The project was supported by ISCIII, Spain (COV-20/00792 to MB, PI23/01351 to MARH) and the European Commission-Next generation EU (European Union) (Regulation EU 2020/2094), through CSIC's Global Health Platform (PTI Salud Global, SGL2103029 to MB). PID2019-110587RB-I00 (MB) supported by MICIN/AEI/10.13039/501100011033/and PID2022-143034OB-I00 (MB) by MICIN/AEI/10.13039/501100011033/FEDER. MAR-H acknowledges support from ISCIII, Spain and the European Commission-Next generation EU (European Union), through CSIC's Global Health PTI.

AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic continues to pose significant challenges to the public health sector, including that of the United Arab Emirates (UAE). The objective of this study was to assess the efficiency and accuracy of various deep-learning models in forecasting COVID-19 cases within the UAE, thereby aiding the nation's public health authorities in informed decision-making.

METHODS

This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators. Several advanced deep learning models, including long short-term memory (LSTM), bidirectional LSTM, convolutional neural network (CNN), CNN-LSTM, multilayer perceptron, and recurrent neural network (RNN) models, were trained and evaluated. Bayesian optimization was also implemented to fine-tune these models.

RESULTS

The evaluation framework revealed that each model exhibited different levels of predictive accuracy and precision. Specifically, the RNN model outperformed the other architectures even without optimization. Comprehensive predictive and perspective analytics were conducted to scrutinize the COVID-19 dataset.

CONCLUSION

This study transcends academic boundaries by offering critical insights that enable public health authorities in the UAE to deploy targeted data-driven interventions. The RNN model, which was identified as the most reliable and accurate for this specific context, can significantly influence public health decisions. Moreover, the broader implications of this research validate the capability of deep learning techniques in handling complex datasets, thus offering the transformative potential for predictive accuracy in the public health and healthcare sectors.

The evolution of metastatic upper tract urothelial carcinoma through genomic-transcriptomic and single-cell protein markers analysis

The molecular characteristics of metastatic upper tract urothelial carcinoma (UTUC) are not well understood, and there is a lack of knowledge regarding the genomic and transcriptomic differences between primary and metastatic UTUC. To address these gaps, we integrate whole-exome sequencing, RNA sequencing, and Imaging Mass Cytometry using lanthanide metal-conjugated antibodies of 44 tumor samples from 28 patients with high-grade primary and metastatic UTUC. We perform a spatially-resolved single-cell analysis of cancer, immune, and stromal cells to understand the evolution of primary to metastatic UTUC. We discover that actionable genomic alterations are frequently discordant between primary and metastatic UTUC tumors in the same patient. In contrast, molecular subtype membership and immune depletion signature are stable across primary and matched metastatic UTUC. Molecular and immune subtypes are consistent between bulk RNA-sequencing and mass cytometry of protein markers from 340,798 single cells. Molecular subtypes at the single-cell level are highly conserved between primary and metastatic UTUC tumors within the same patient.

Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19

Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait-relevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID-19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular-specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications.

Extensive acute and sustained changes to neutrophil proteomes post-SARS-CoV-2 infection

BACKGROUND

Neutrophils are important in the pathophysiology of coronavirus disease 2019 (COVID-19), but the molecular changes contributing to altered neutrophil phenotypes following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are not fully understood. We used quantitative mass spectrometry-based proteomics to explore neutrophil phenotypes immediately following acute SARS-CoV-2 infection and during recovery.

METHODS

Prospective observational study of hospitalised patients with PCR-confirmed SARS-CoV-2 infection (May to December 2020). Patients were enrolled within 96 h of admission, with longitudinal sampling up to 29 days. Control groups comprised non-COVID-19 acute lower respiratory tract infection (LRTI) and age-matched noninfected controls. Neutrophils were isolated from peripheral blood and analysed using mass spectrometry. COVID-19 severity and recovery were defined using the World Health Organization ordinal scale.

RESULTS

Neutrophil proteomes from 84 COVID-19 patients were compared to those from 91 LRTI and 42 control participants. 5800 neutrophil proteins were identified, with >1700 proteins significantly changed in neutrophils from COVID-19 patients compared to noninfected controls. Neutrophils from COVID-19 patients initially all demonstrated a strong interferon signature, but this signature rapidly declined in patients with severe disease. Severe disease was associated with increased abundance of proteins involved in metabolism, immunosuppression and pattern recognition, while delayed recovery from COVID-19 was associated with decreased granule components and reduced abundance of metabolic proteins, chemokine and leukotriene receptors, integrins and inhibitory receptors.

CONCLUSIONS

SARS-CoV-2 infection results in the sustained presence of circulating neutrophils with distinct proteomes suggesting altered metabolic and immunosuppressive profiles and altered capacities to respond to migratory signals and cues from other immune cells, pathogens or cytokines.

Deep spatial proteomics reveals region-specific features of severe COVID-19-related pulmonary injury

As a primary target of severe acute respiratory syndrome coronavirus 2, lung exhibits heterogeneous histopathological changes following infection. However, comprehensive insight into their protein basis with spatial resolution remains deficient, which hinders further understanding of coronavirus disease 2019 (COVID-19)-related pulmonary injury. Here, we generate a region-resolved proteomic atlas of hallmark pathological pulmonary structures by integrating histological examination, laser microdissection, and ultrasensitive proteomics. Over 10,000 proteins are quantified across 71 post-mortem specimens. We identify a spectrum of pathway dysregulations in alveolar epithelium, bronchial epithelium, and blood vessels compared with non-COVID-19 controls, providing evidence for transitional-state pneumocyte hyperplasia. Additionally, our data reveal the region-specific enrichment of functional markers in bronchiole mucus plugs, pulmonary fibrosis, airspace inflammation, and alveolar type 2 cells, uncovering their distinctive features. Furthermore, we detect increased protein expression associated with viral entry and inflammatory response across multiple regions, suggesting potential therapeutic targets. Collectively, this study provides a distinct perspective for deciphering COVID-19-caused pulmonary dysfunction by spatial proteomics.

Pre-Infection Innate Immunity Attenuates SARS-CoV-2 Infection and Viral Load in iPSC-Derived Alveolar Epithelial Type 2 Cells

A large portion of the heterogeneity in coronavirus disease 2019 (COVID-19) susceptibility and severity of illness (SOI) remains poorly understood. Recent evidence suggests that SARS-CoV-2 infection-associated damage to alveolar epithelial type 2 cells (AT2s) in the distal lung may directly contribute to disease severity and poor prognosis in COVID-19 patients. Our in vitro modeling of SARS-CoV-2 infection in induced pluripotent stem cell (iPSC)-derived AT2s from 10 different individuals showed interindividual variability in infection susceptibility and the postinfection cellular viral load. To understand the underlying mechanism of the AT2's capacity to regulate SARS-CoV-2 infection and cellular viral load, a genome-wide differential gene expression analysis between the mock and SARS-CoV-2 infection-challenged AT2s was performed. The 1393 genes, which were significantly (one-way ANOVA FDR-corrected p ≤ 0.05; FC abs ≥ 2.0) differentially expressed (DE), suggest significant upregulation of viral infection-related cellular innate immune response pathways (p-value ≤ 0.05; activation z-score ≥ 3.5), and significant downregulation of the cholesterol- and xenobiotic-related metabolic pathways (p-value ≤ 0.05; activation z-score ≤ -3.5). Whilst the effect of post-SARS-CoV-2 infection response on the infection susceptibility and postinfection viral load in AT2s is not clear, interestingly, pre-infection (mock-challenged) expression of 238 DE genes showed a high correlation with the postinfection SARS-CoV-2 viral load (FDR-corrected p-value ≤ 0.05 and r2-absolute ≥ 0.57). The 85 genes whose expression was negatively correlated with the viral load showed significant enrichment in viral recognition and cytokine-mediated innate immune GO biological processes (p-value range: 4.65 × 10-10 to 2.24 × 10-6). The 153 genes whose expression was positively correlated with the viral load showed significant enrichment in cholesterol homeostasis, extracellular matrix, and MAPK/ERK pathway-related GO biological processes (p-value range: 5.06 × 10-5 to 6.53 × 10-4). Overall, our results strongly suggest that AT2s' pre-infection innate immunity and metabolic state affect their susceptibility to SARS-CoV-2 infection and viral load.

Pathogenesis of Pulmonary Long COVID-19

COVID-19 is characterized by an acute respiratory illness that, in some patients, progresses to respiratory failure, largely demonstrating a pattern of acute respiratory distress syndrome. Excluding fatal cases, the outcome of this severe illness ranges from complete resolution to persistent respiratory dysfunction. This subacute-to-chronic respiratory illness has different manifestations and is collectively termed as "long COVID." The pathogenesis of organ dysfunction in acute injury stems from exaggerated innate immune response, complement activation, and monocyte influx, with a shift toward an organ injury state with abnormalities in cellular maturation. Although the increased rate of thrombosis observed in acute COVID-19 does not appear to persist, interestingly, ongoing symptomatic COVID-19 and post-COVID pathogeneses appear to reflect the persistence of immune and cellular disturbances triggered by the acute and subacute periods.

Extracorporeal membrane oxygenation circuits in parallel for refractory hypoxemia in patients with COVID-19

OBJECTIVES

Refractory hypoxemia can occur in patients with acute respiratory distress syndrome from COVID-19 despite support with venovenous (VV) extracorporeal membrane oxygenation (ECMO). Parallel ECMO circuits can be used to increase physiologic support. We report our clinical experience using ECMO circuits in parallel for select patients with persistent severe hypoxemia despite the use of a single ECMO circuit.

METHODS

We performed a retrospective cohort study of all patients with COVID-19-related acute respiratory distress syndrome who received VV-ECMO with an additional circuit in parallel at Vanderbilt University Medical Center between March 1, 2020, and March 1, 2022. We report demographic characteristics and clinical characteristics including ECMO settings, mechanical ventilator settings, use of adjunctive therapies, and arterial blood gas results after initial cannulation, before and after receipt of a second ECMO circuit in parallel, and before removal of the circuit in parallel, and outcomes.

RESULTS

Of 84 patients with COVID-19 who received VV-ECMO during the study period, 22 patients (26.2%) received a circuit in parallel. The median duration of ECMO was 40.0 days (interquartile range, 31.6-53.1 days), of which 19.0 days (interquartile range, 13.0-33.0 days) were spent with a circuit in parallel. Of the 22 patients who received a circuit in parallel, 16 (72.7%) survived to hospital discharge and 6 (27.3%) died before discharge.

CONCLUSIONS

In select patients, the additional use of an ECMO circuit in parallel can increase ECMO blood flow and improve oxygenation while allowing for lung-protective mechanical ventilation and excellent outcomes.

Tissue niches and immunopathology through the lens of spatial tissue profiling techniques

Spatial organization plays a fundamental role in biology, influencing the function of biological structures at various levels. The immune system, in particular, relies on the orchestrated interactions of immune cells with their microenvironment to mount protective or pathogenic immune responses. The COVID-19 pandemic has underscored the significance of studying immunity within target organs to understand disease progression and severity. To achieve this, multiplex histology and spatial transcriptomics have proven indispensable in providing a spatial context to protein and gene expression patterns. By combining these techniques, researchers gain a more comprehensive understanding of the complex interactions at the cellular and molecular level in distinct tissue niches, key functional units modulating health and disease. In this review, we discuss recent advances in spatial tissue profiling techniques, highlighting their advantages over traditional histopathology studies. The insights gained from these approaches have the potential to revolutionize the diagnosis and treatment of various diseases including cancer, autoimmune disorders, and infectious diseases. However, we also acknowledge their challenges and limitations. Despite these, spatial tissue profiling offers promising opportunities to improve our understanding of how tissue niches direct regional immunity, and their relevance in tissue immunopathology, as a basis for novel therapeutic strategies and personalized medicine.

Lung regeneration: diverse cell types and the therapeutic potential

Lung tissue has a certain regenerative ability and triggers repair procedures after injury. Under controllable conditions, lung tissue can restore normal structure and function. Disruptions in this process can lead to respiratory system failure and even death, causing substantial medical burden. The main types of respiratory diseases are chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), and acute respiratory distress syndrome (ARDS). Multiple cells, such as lung epithelial cells, endothelial cells, fibroblasts, and immune cells, are involved in regulating the repair process after lung injury. Although the mechanism that regulates the process of lung repair has not been fully elucidated, clinical trials targeting different cells and signaling pathways have achieved some therapeutic effects in different respiratory diseases. In this review, we provide an overview of the cell type involved in the process of lung regeneration and repair, research models, and summarize molecular mechanisms involved in the regulation of lung regeneration and fibrosis. Moreover, we discuss the current clinical trials of stem cell therapy and pharmacological strategies for COPD, IPF, and ARDS treatment. This review provides a reference for further research on the molecular and cellular mechanisms of lung regeneration, drug development, and clinical trials.

A comprehensive SARS-CoV-2 and COVID-19 review, Part 2: host extracellular to systemic effects of SARS-CoV-2 infection

COVID-19, the disease caused by SARS-CoV-2, has caused significant morbidity and mortality worldwide. The betacoronavirus continues to evolve with global health implications as we race to learn more to curb its transmission, evolution, and sequelae. The focus of this review, the second of a three-part series, is on the biological effects of the SARS-CoV-2 virus on post-acute disease in the context of tissue and organ adaptations and damage. We highlight the current knowledge and describe how virological, animal, and clinical studies have shed light on the mechanisms driving the varied clinical diagnoses and observations of COVID-19 patients. Moreover, we describe how investigations into SARS-CoV-2 effects have informed the understanding of viral pathogenesis and provide innovative pathways for future research on the mechanisms of viral diseases.

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.

Infectious Diseases

Microglia, brain-resident innate immune cells, have been extensively studied in neurodegenerative contexts like Alzheimer's disease. The Coronavirus disease 2019 (COVID-19) pandemic highlighted how peripheral infection and inflammation can be detrimental to the neuroimmune milieu and initiate microgliosis driven by peripheral inflammation. Microglia can remain deleterious to brain health by sustaining inflammation in the central nervous system even after the clearance of the original immunogenic agents. In this chapter, we discuss how pulmonary infection with Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) can lead to neurovascular and neuroimmune inflammation causing the neurological syndrome of post-acute sequelae of COVID-19 (PASC). Further, we incorporate lessons from the Human Immunodeficiency Virus' (HIV's) effects on microglial functioning in the era of combined antiretroviral therapies (cART) that contribute to HIV-1 associated neurocognitive disorders (HAND). Finally, we describe roles for mixed lineage kinase 3 (MLK3) and leucine-rich repeat kinase (LRRK2) as key regulators of multiple inflammatory and apoptotic pathways important to the pathogenesis of PASC and HAND. Inhibition of these pathways provides a therapeutically synergistic method of treating both PASC and HAND.

'Immune-inflammatory markers & clinical characteristics for outcomes in hospitalized SARS-CoV-2 infected patients of Pakistan: a retrospective analysis'

OBJECTIVE

Accumulating evidence suggests the role of immune-inflammatory markers in early risk stratification and prognostication of COVID-19 patients. We aimed to evaluate their association with severity and the development of diagnostic scores with optimal thresholds in critical patients.

SETTING AND PARTICIPANTS

This retrospective case study includes hospitalized COVID-19 patients from March 2019 to March, 2022, in the developing area teaching hospital in Pakistan. Polymerase chain reaction (PCR) positive patients, n = 467 were investigated for clinical outcomes, comorbidities and disease prognosis. The plasma levels of Interleukin-6 (IL-6), Lactate dehydrogenase (LDH), C-reactive protein (CRP), Procalcitonin (PCT), ferritin and Complete blood count markers were measured.

RESULTS

Majority were males (58.8%) and patients with comorbidities had more severe disease. Hypertension and diabetes mellitus were the commonest comorbidities. Shortness of breath, myalgia and cough were the main symptoms. The hematological markers NLR, as well as the plasma levels of immune-inflammatory variables, IL-6, LDH, Procalcitonin, Erythrocyte sedimentation rate, Ferritin were markedly raised in severe and critical patients (p < 0.0001 for these markers). ROC analysis supports IL-6 as the most accurate marker with high prognostic relevance with proposed cut-off threshold (43 pg/ml), determining >90% of patients in terms of COVID-19 severity (AUC = 0.93, 91.7%, se; 90.3%sp). Furthermore, positive correlation with all other markers including NLR with cut-off = 2.99 (AUC = 0.87, se = 89.8%, sp = 88.4%), CRP with cut-offs at 42.9 mg/l, (AUC = 0.883, se = 89.3% and sp = 78.6%), LDH cut-off at 267μg/L, evidenced in >80% patients (AUC = 0.834 se = 84% and sp = 80%). Additionally, ESR and ferritin have the corresponding AUC 0.81 and 0.813 with cut-off at 55 mm/hr and 370, respectively.

CONCLUSION

Investigating the immune-inflammatory markers can assist physicians in providing prompt treatment and ICU admission in terms of COVID-19 severity. As a result, which may reduce the overall mortality of COVID-19 patients.

Opportunities for High-plex Spatial Transcriptomics in Solid Organ Transplantation

The last 5 y have seen the development and widespread adoption of high-plex spatial transcriptomic technology. This technique detects and quantifies mRNA transcripts in situ, meaning that transcriptomic signatures can be sampled from specific cells, structures, lesions, or anatomical regions while conserving the physical relationships that exist within complex tissues. These methods now frequently implement next-generation sequencing, enabling the simultaneous measurement of many targets, up to and including the whole mRNA transcriptome. To date, spatial transcriptomics has been foremost used in the fields of neuroscience and oncology, but there is potential for its use in transplantation sciences. Transplantation has a clear dependence on biopsies for diagnosis, monitoring, and research. Transplant patients represent a unique cohort with multiple organs of interest, clinical courses, demographics, and immunosuppressive regimens. Obtaining high complexity data on the disease processes underlying rejection, tolerance, infection, malignancy, and injury could identify new opportunities for therapeutic intervention and biomarker identification. In this review, we discuss currently available spatial transcriptomic technologies and how they can be applied to transplantation.

Macrophage phenotypes and functions: resolving inflammation and restoring homeostasis

Inflammation must be tightly regulated to both defend against pathogens and restore tissue homeostasis. The resolution of inflammatory responses is a dynamic process orchestrated by cells of the immune system. Macrophages, tissue-resident innate immune cells, are key players in modulating inflammation. Here, we review recent work highlighting the importance of macrophages in tissue resolution and the return to homeostasis. We propose that enhancing macrophage pro-resolution functions represents a novel and widely applicable therapeutic strategy to dampen inflammation, promote repair, and restore tissue integrity and function.

Enablers and challenges of spatial omics, a melting pot of technologies

Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly interdisciplinary field that integrates imaging and omics, spatial and molecular analyses, sequencing and mass spectrometry, and image analysis and bioinformatics. The emergence of this field has not only opened a window into spatial biology, but also created multiple novel opportunities, questions, and challenges for method developers. Here, we provide the perspective of technology developers on what makes the spatial omics field unique. After providing a brief overview of the state of the art, we discuss technological enablers and challenges and present our vision about the future applications and impact of this melting pot.

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.

Chemical tagging mass spectrometry: an approach for single-cell omics

Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.

An end-to-end workflow for multiplexed image processing and analysis

Multiplexed imaging enables the simultaneous spatial profiling of dozens of biological molecules in tissues at single-cell resolution. Extracting biologically relevant information, such as the spatial distribution of cell phenotypes from multiplexed tissue imaging data, involves a number of computational tasks, including image segmentation, feature extraction and spatially resolved single-cell analysis. Here, we present an end-to-end workflow for multiplexed tissue image processing and analysis that integrates previously developed computational tools to enable these tasks in a user-friendly and customizable fashion. For data quality assessment, we highlight the utility of napari-imc for interactively inspecting raw imaging data and the cytomapper R/Bioconductor package for image visualization in R. Raw data preprocessing, image segmentation and feature extraction are performed using the steinbock toolkit. We showcase two alternative approaches for segmenting cells on the basis of supervised pixel classification and pretrained deep learning models. The extracted single-cell data are then read, processed and analyzed in R. The protocol describes the use of community-established data containers, facilitating the application of R/Bioconductor packages for dimensionality reduction, single-cell visualization and phenotyping. We provide instructions for performing spatially resolved single-cell analysis, including community analysis, cellular neighborhood detection and cell-cell interaction testing using the imcRtools R/Bioconductor package. The workflow has been previously applied to imaging mass cytometry data, but can be easily adapted to other highly multiplexed imaging technologies. This protocol can be implemented by researchers with basic bioinformatics training, and the analysis of the provided dataset can be completed within 5-6 h. An extended version is available at https://bodenmillergroup.github.io/IMCDataAnalysis/ .