Microfluidic Immuno-Serolomic Assay Reveals Systems Level Association with COVID-19 Pathology and Vaccine Protection.

How to develop highly informative serology assays to evaluate the quality of immune protection against coronavirus disease-19 (COVID-19) has been a global pursuit over the past years. Here, a microfluidic high-plex immuno-serolomic assay is developed to simultaneously measure50 plasma or serum samples for50 soluble markers including 35proteins, 11 anti-spike/receptor binding domian (RBD) IgG antibodies spanningmajor variants, and controls. This assay demonstrates the quintuplicate test in a single run with high throughput, low sample volume, high reproducibilityand accuracy. It is applied to the measurement of 1012 blood samples including in-depth analysis of sera from 127 patients and 21 healthy donors over multiple time points, either with acute COVID infection or vaccination. The protein analysis reveals distinct immune mediator modules that exhibit a reduced degree of diversity in protein-protein cooperation in patients with hematologic malignancies or receiving B cell depletion therapy. Serological analysis identifies that COVID-infected patients with hematologic malignancies display impaired anti-RBD antibody response despite high level of anti-spike IgG, which can be associated with limited clonotype diversity and functional deficiency in B cells. These findings underscore the importance to individualize immunization strategies for these high-risk patients and provide an informative tool to monitor their responses at the systems level.

Machine learning and integrative analysis identify the common pathogenesis of azoospermia complicated with COVID-19.

Background: Although more recent evidence has indicated COVID-19 is prone to azoospermia, the common molecular mechanism of its occurrence remains to be elucidated. The aim of the present study is to further investigate the mechanism of this complication. Methods: To discover the common differentially expressed genes (DEGs) and pathways of azoospermia and COVID-19, integrated weighted co-expression network (WGCNA), multiple machine learning analyses, and single-cell RNA-sequencing (scRNA-seq) were performed. Results: Therefore, we screened two key network modules in the obstructive azoospermia (OA) and non-obstructive azoospermia (NOA) samples. The differentially expressed genes were mainly related to the immune system and infectious virus diseases. We then used multiple machine learning methods to detect biomarkers that differentiated OA from NOA. Enrichment analysis showed that azoospermia patients and COVID-19 patients shared a common IL-17 signaling pathway. In addition, GLO1, GPR135, DYNLL2, and EPB41L3 were identified as significant hub genes in these two diseases. Screening of two different molecular subtypes revealed that azoospermia-related genes were associated with clinicopathological characteristics of age, hospital-free-days, ventilator-free-days, charlson score, and d-dimer of patients with COVID-19 (P < 0.05). Finally, we used the Xsum method to predict potential drugs and single-cell sequencing data to further characterize whether azoospermia-related genes could validate the biological patterns of impaired spermatogenesis in cryptozoospermia patients. Conclusion: Our study performs a comprehensive and integrated bioinformatics analysis of azoospermia and COVID-19. These hub genes and common pathways may provide new insights for further mechanism research.

Research highlights of renal transplantation in 2020: voice from China

Renal transplantation is the optimal approach to improve the quality of life and restore normal life for patients with end-stage renal diseases. With the development of medical techniques and immunosuppressants, the short-term survival of renal graft has been significantly prolonged, whereas the long-term survival remains to be urgently solved. Renal ischemia-reperfusion injury (IRI), acute rejection, chronic renal allograft dysfunction, renal fibrosis and other factors are still the major problems affecting the survival of renal graft. Relevant researches have always been hot spots in the field of renal transplantation. Meantime, 2020 is an extraordinary year. The novel coronavirus pneumonia (COVID-19) pandemic severely affects the development of all walks of life. Researches related to renal transplantation have also sprung up. In this article, the frontier hotspots of clinical and basic studies related to renal transplantation and the COVID-19 related researches in the field of renal transplantation in China were reviewed, aiming to provide novel therapeutic ideas and strategies.Copyright © 2021 Journal of Zhongshan University. All Rights Reserved.

High-throughput microfluidic droplets in biomolecular analytical system: A review.

Droplet microfluidic technology has revolutionized biomolecular analytical research, as it has the capability to reserve the genotype-to-phenotype linkage and assist for revealing the heterogeneity. Massive and uniform picolitre droplets feature dividing solution to the level that single cell and single molecule in each droplet can be visualized, barcoded, and analyzed. Then, the droplet assays can unfold intensive genomic data, offer high sensitivity, and screen and sort from a large number of combinations or phenotypes. Based on these unique advantages, this review focuses on up-to-date research concerning diverse screening applications utilizing droplet microfluidic technology. The emerging progress of droplet microfluidic technology is first introduced, including efficient and scaling-up in droplets encapsulation, and prevalent batch operations. Then the new implementations of droplet-based digital detection assays and single-cell muti-omics sequencing are briefly examined, along with related applications such as drug susceptibility testing, multiplexing for cancer subtype identification, interactions of virus-to-host, and multimodal and spatiotemporal analysis. Meanwhile, we specialize in droplet-based large-scale combinational screening regarding desired phenotypes, with an emphasis on sorting for immune cells, antibodies, enzymatic properties, and proteins produced by directed evolution methods. Finally, some challenges, deployment and future perspective of droplet microfluidics technology in practice are also discussed.

Contribution of Retrotransposons to the Pathogenesis of Type 1 Diabetes and Challenges in Analysis Methods.

Type 1 diabetes (T1D) is one of the most common chronic diseases of the endocrine system, associated with several life-threatening comorbidities. While the etiopathogenesis of T1D remains elusive, a combination of genetic susceptibility and environmental factors, such as microbial infections, are thought to be involved in the development of the disease. The prime model for studying the genetic component of T1D predisposition encompasses polymorphisms within the HLA (human leukocyte antigen) region responsible for the specificity of antigen presentation to lymphocytes. Apart from polymorphisms, genomic reorganization caused by repeat elements and endogenous viral elements (EVEs) might be involved in T1D predisposition. Such elements are human endogenous retroviruses (HERVs) and non-long terminal repeat (non-LTR) retrotransposons, including long and short interspersed nuclear elements (LINEs and SINEs). In line with their parasitic origin and selfish behaviour, retrotransposon-imposed gene regulation is a major source of genetic variation and instability in the human genome, and may represent the missing link between genetic susceptibility and environmental factors long thought to contribute to T1D onset. Autoreactive immune cell subtypes with differentially expressed retrotransposons can be identified with single-cell transcriptomics, and personalized assembled genomes can be constructed, which can then serve as a reference for predicting retrotransposon integration/restriction sites. Here we review what is known to date about retrotransposons, we discuss the involvement of viruses and retrotransposons in T1D predisposition, and finally we consider challenges in retrotransposons analysis methods.

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.

Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously. Analysis of scRNA-seq data plays an important role in the study of cell states and phenotypes, and has helped elucidate biological processes, such as those occurring during the development of complex organisms, and improved our understanding of disease states, such as cancer, diabetes, and coronavirus disease 2019 (COVID-19). Deep learning, a recent advance of artificial intelligence that has been used to address many problems involving large datasets, has also emerged as a promising tool for scRNA-seq data analysis, as it has a capacity to extract informative and compact features from noisy, heterogeneous, and high-dimensional scRNA-seq data to improve downstream analysis. The present review aims at surveying recently developed deep learning techniques in scRNA-seq data analysis, identifying key steps within the scRNA-seq data analysis pipeline that have been advanced by deep learning, and explaining the benefits of deep learning over more conventional analytic tools. Finally, we summarize the challenges in current deep learning approaches faced within scRNA-seq data and discuss potential directions for improvements in deep learning algorithms for scRNA-seq data analysis.

Early peripheral blood MCEMP1 and HLA-DRA expression predicts COVID-19 prognosis.

BACKGROUND: Mass vaccination has dramatically reduced the incidence of severe COVID-19, with most cases now presenting as self-limiting upper respiratory tract infections. However, those with co-morbidities, the elderly and immunocompromised, as well as the unvaccinated, remain disproportionately vulnerable to severe COVID-19 and its sequelae. Furthermore, as the effectiveness of vaccination wanes with time, immune escape SARS-CoV-2 variants could emerge to cause severe COVID-19. Reliable prognostic biomarkers for severe disease could be used as early indicator of re-emergence of severe COVID-19 as well as for triaging of patients for antiviral therapy. METHODS: We performed a systematic review and re-analysis of 7 publicly available datasets, analysing a total of 140 severe and 181 mild COVID-19 patients, to determine the most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients. In addition, we included an independent cohort where blood transcriptomics of COVID-19 patients were prospectively and longitudinally monitored previously, to track the time in which these gene expression changes occur before nadir of respiratory function. Single cell RNA-sequencing of peripheral blood mononuclear cells from publicly available datasets was then used to determine the immune cell subsets involved. FINDINGS: The most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients were MCEMP1, HLA-DRA and ETS1 across the 7 transcriptomics datasets. Moreover, we found significantly heightened MCEMP1 and reduced HLA-DRA expression as early as four days before the nadir of respiratory function, and the differential expression of MCEMP1 and HLA-DRA occurred predominantly in CD14+ cells. The online platform which we developed is publicly available at https://kuanrongchan-covid19-severity-app-t7l38g.streamlitapp.com/, for users to query gene expression differences between severe and mild COVID-19 patients in these datasets. INTERPRETATION: Elevated MCEMP1 and reduced HLA-DRA gene expression in CD14+ cells during the early phase of disease are prognostic of severe COVID-19. FUNDING: K.R.C is funded by the National Medical Research Council (NMRC) of Singapore under the Open Fund Individual Research Grant (MOH-000610). E.E.O. is funded by the NMRC Senior Clinician-Scientist Award (MOH-000135-00). J.G.H.L. is funded by the NMRC under the Clinician-Scientist Award (NMRC/CSAINV/013/2016-01). S.K. is funded by the NMRC under the Transition Award. This study was sponsored in part by a generous gift from The Hour Glass.

Heterogeneity of neutrophils and inflammatory responses in patients with COVID-19 and healthy controls.

Severe respiratory viral infections, including SARS-CoV-2, have resulted in high mortality rates despite corticosteroids and other immunomodulatory therapies. Despite recognition of the pathogenic role of neutrophils, in-depth analyses of this cell population have been limited, due to technical challenges of working with neutrophils. We undertook an unbiased, detailed analysis of neutrophil responses in adult patients with COVID-19 and healthy controls, to determine whether distinct neutrophil phenotypes could be identified during infections compared to the healthy state. Single-cell RNA sequencing analysis of peripheral blood neutrophils from hospitalized patients with mild or severe COVID-19 disease and healthy controls revealed distinct mature neutrophil subpopulations, with relative proportions linked to disease severity. Disruption of predicted cell-cell interactions, activated oxidative phosphorylation genes, and downregulated antiviral and host defense pathway genes were observed in neutrophils obtained during severe compared to mild infections. Our findings suggest that during severe infections, there is a loss of normal regulatory neutrophil phenotypes seen in healthy subjects, coupled with the dropout of appropriate cellular interactions. Given that neutrophils are the most abundant circulating leukocytes with highly pathogenic potential, current immunotherapies for severe infections may be optimized by determining whether they aid in restoring an appropriate balance of neutrophil subpopulations.

Single-cell multi-omics integration for unpaired data by a siamese network with graph-based contrastive loss.

BACKGROUND: Single-cell omics technology is rapidly developing to measure the epigenome, genome, and transcriptome across a range of cell types. However, it is still challenging to integrate omics data from different modalities. Here, we propose a variation of the Siamese neural network framework called MinNet, which is trained to integrate multi-omics data on the single-cell resolution by using graph-based contrastive loss. RESULTS: By training the model and testing it on several benchmark datasets, we showed its accuracy and generalizability in integrating scRNA-seq with scATAC-seq, and scRNA-seq with epitope data. Further evaluation demonstrated our model's unique ability to remove the batch effect, a common problem in actual practice. To show how the integration impacts downstream analysis, we established model-based smoothing and cis-regulatory element-inferring method and validated it with external pcHi-C evidence. Finally, we applied the framework to a COVID-19 dataset to bolster the original work with integration-based analysis, showing its necessity in single-cell multi-omics research. CONCLUSIONS: MinNet is a novel deep-learning framework for single-cell multi-omics sequencing data integration. It ranked top among other methods in benchmarking and is especially suitable for integrating datasets with batch and biological variances. With the single-cell resolution integration results, analysis of the interplay between genome and transcriptome can be done to help researchers understand their data and question.

Natural Killer Cells in SARS-CoV-2 Infection: Pathophysiology and Therapeutic Implications.

Natural Killer (NK) cells are lymphocytes of the innate immunity that play a crucial role in the control of viral infections in the absence of a prior antigen sensitization. Indeed, they display rapid effector functions against target cells with the capability of direct cell killing and antibody-dependent cell-mediated cytotoxicity. Furthermore, NK cells are endowed with immune-modulatory functions innate and adaptive immune responses via the secretion of chemokines/cytokines and by undertaking synergic crosstalks with other innate immune cells, including monocyte/macrophages, dendritic cells and neutrophils. Recently, the Coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread globally. Although the specific role of NK cells in COVID-19 pathophysiology still need to be explored, mounting evidence indicates that NK cell tissue distribution and effector functions could be affected by SARS-CoV-2 infection and that a prompt NK cell response could determine a good clinical outcome in COVID-19 patients. In this review, we give a comprehensive overview of how SARS-CoV-2 infection interferes with NK cell antiviral effectiveness and their crosstalk with other innate immune cells. We also provide a detailed characterization of the specific NK cell subsets in relation to COVID-19 patient severity generated from publicly available single cell RNA sequencing datasets. Finally, we summarize the possible NK cell-based therapeutic approaches against SARS-CoV-2 infection and the ongoing clinical trials updated at the time of submission of this review. We will also discuss how a deep understanding of NK cell responses could open new possibilities for the treatment and prevention of SARS-CoV-2 infection.

Organoids as tools for fundamental discovery and translation-A Keystone Symposia report.

Complex three-dimensional in vitro organ-like models, or organoids, offer a unique biological tool with distinct advantages over two-dimensional cell culture systems, which can be too simplistic, and animal models, which can be too complex and may fail to recapitulate human physiology and pathology. Significant progress has been made in driving stem cells to differentiate into different organoid types, though several challenges remain. For example, many organoid models suffer from high heterogeneity, and it can be difficult to fully incorporate the complexity of in vivo tissue and organ development to faithfully reproduce human biology. Successfully addressing such limitations would increase the viability of organoids as models for drug development and preclinical testing. On April 3-6, 2022, experts in organoid development and biology convened at the Keystone Symposium "Organoids as Tools for Fundamental Discovery and Translation" to discuss recent advances and insights from this relatively new model system into human development and disease.

Spatial Mapping of Genes Implicated in SARS-CoV-2 Neuroinvasion to Dorsolateral Prefrontal Cortex Gray Matter.

Introduction: SARS-CoV-2 is the newest beta coronavirus family member to demonstrate neuroinvasive capability in severe cases of infection. Despite much research activity in the SARS-CoV-2/COVID-19 space, the gene-level biology of this phenomenon remains poorly understood. In the present analysis, we leveraged spatial transcriptomics methodologies to examine relevant gene heterogeneity in tissue retrieved from the human prefrontal cortex. Methods: Expression profiles of genes with established relations to the SARS-CoV-2 neuroinvasion process were spatially resolved in dorsolateral prefrontal cortex tissue (N = 4). Spotplots were generated with mapping to six (6) previously defined gray matter layers. Results: Docking gene BSG, processing gene CTSB, and viral defense gene LY6E demonstrated similar spatial enrichment. Docking gene ACE2 and transmembrane series proteases involved in spike protein processing were lowly expressed across DLPFC samples. Numerous other findings were obtained. Conclusion: Efforts to spatially represent expression levels of key SARS-CoV-2 brain infiltration genes remain paltry to date. Understanding the sobering history of beta coronavirus neuroinvasion represents a weak point in viral research. Here we provide the first efforts to characterize a motley of such genes in the dorsolateral prefrontal cortex.

New insights into the pathogenesis and management of rheumatoid arthritis.

Over the past few decades, understanding of the pathogenesis of rheumatoid arthritis (RA) has improved substantially. Insights into the cellular and molecular mechanisms involved in RA have enabled the discovery of new therapeutic targets and led to the development of biologics and targeted synthetic disease-modifying antirheumatic drugs. In parallel with the improvement in therapies, the evolution of strategies in the management of RA has also contributed considerably to better outcomes in patients. Major changes include the development of disease activity measures, formulation of the treat-to-target principles as well as increased attention to comorbidities. The presence of comorbidities such as cardiovascular diseases may increase the mortality of RA patients, affect their treatment strategies and result in worse outcomes. Therefore, prevention and management of certain high-risk comorbidities have become increasingly important in the long-term treatment of RA. In this study, we summarized new insights into the pathogenesis and management of rheumatoid arthritis and associated comorbidities, with a special focus on the 2021 update of the American College of Rheumatology (ACR) guideline for RA and key reports presented at the 2021 ACR convergence.

Discovery and characterization of SARS-CoV-2 reactive and neutralizing antibodies from humanized CAMouseHG mice through rapid hybridoma screening and high-throughput single-cell V(D)J sequencing.

The coronavirus disease 2019 pandemic has caused more than 532 million infections and 6.3 million deaths to date. The reactive and neutralizing fully human antibodies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are effective detection tools and therapeutic measures. During SARS-CoV-2 infection, a large number of SARS-CoV-2 reactive and neutralizing antibodies will be produced. Most SARS-CoV-2 reactive and neutralizing fully human antibodies are isolated from human and frequently encoded by convergent heavy-chain variable genes. However, SARS-CoV-2 viruses can mutate rapidly during replication and the resistant variants of neutralizing antibodies easily survive and evade the immune response, especially in the face of such focused antibody responses in humans. Therefore, additional tools are needed to develop different kinds of fully human antibodies to compensate for current deficiency. In this study, we utilized antibody humanized CAMouseHG mice to develop a rapid antibody discovery method and examine the antibody repertoire of SARS-CoV-2 RBD-reactive hybridoma cells derived from CAMouseHG mice by using high-throughput single-cell V(D)J sequencing analysis. CAMouseHG mice were immunized by 28-day rapid immunization method. After electrofusion and semi-solid medium screening on day 12 post-electrofusion, 171 hybridoma clones were generated based on the results of SARS-CoV-2 RBD binding activity assay. A rather obvious preferential usage of IGHV6-1 family was found in these hybridoma clones derived from CAMouseHG mice, which was significantly different from the antibodies found in patients with COVID-19. After further virus neutralization screening and antibody competition assays, we generated a noncompeting two-antibody cocktail, which showed a potent prophylactic protective efficacy against SARS-CoV-2 in cynomolgus macaques. These results indicate that humanized CAMouseHG mice not only provide a valuable platform to obtain fully human reactive and neutralizing antibodies but also have a different antibody repertoire from humans. Thus, humanized CAMouseHG mice can be used as a good complementary tool in discovery of fully human therapeutic and diagnostic antibodies.

Single-cell transcriptomics reveals common epithelial response patterns in human acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) occurs frequently in critically ill patients and is associated with adverse outcomes. Cellular mechanisms underlying AKI and kidney cell responses to injury remain incompletely understood. METHODS: We performed single-nuclei transcriptomics, bulk transcriptomics, molecular imaging studies, and conventional histology on kidney tissues from 8 individuals with severe AKI (stage 2 or 3 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria). Specimens were obtained within 1-2 h after individuals had succumbed to critical illness associated with respiratory infections, with 4 of 8 individuals diagnosed with COVID-19. Control kidney tissues were obtained post-mortem or after nephrectomy from individuals without AKI. RESULTS: High-depth single cell-resolved gene expression data of human kidneys affected by AKI revealed enrichment of novel injury-associated cell states within the major cell types of the tubular epithelium, in particular in proximal tubules, thick ascending limbs, and distal convoluted tubules. Four distinct, hierarchically interconnected injured cell states were distinguishable and characterized by transcriptome patterns associated with oxidative stress, hypoxia, interferon response, and epithelial-to-mesenchymal transition, respectively. Transcriptome differences between individuals with AKI were driven primarily by the cell type-specific abundance of these four injury subtypes rather than by private molecular responses. AKI-associated changes in gene expression between individuals with and without COVID-19 were similar. CONCLUSIONS: The study provides an extensive resource of the cell type-specific transcriptomic responses associated with critical illness-associated AKI in humans, highlighting recurrent disease-associated signatures and inter-individual heterogeneity. Personalized molecular disease assessment in human AKI may foster the development of tailored therapies.

Novel insight on marker genes and pathogenic peripheral neutrophil subtypes in acute pancreatitis.

Acute pancreatitis is a common critical and acute gastrointestinal disease worldwide, with an increasing percentage of morbidity. However, the gene expression pattern in peripheral blood has not been fully analyzed. In addition, the mechanism of coronavirus disease 2019 (COVID-19)-induced acute pancreatitis has not been investigated. Here, after bioinformatic analysis with machine-learning methods of the expression data of peripheral blood cells and validation in local patients, two functional gene modules in peripheral blood cells of acute pancreatitis were identified, and S100A6, S100A9, and S100A12 were validated as predictors of severe pancreatitis. Additionally, through a combination analysis of bulk sequencing and single-cell sequencing data of COVID-19 patients, a pivotal subtype of neutrophils with strong activation of the interferon-related pathway was identified as a pivotal peripheral blood cell subtype for COVID-19-induced acute pancreatitis. These results could facilitate the prognostic prediction of acute pancreatitis and research on COVID-19-induced acute pancreatitis.

Single-cell transcriptome landscape and antigen receptor dynamic during SARS-CoV-2 vaccination.

Vaccination by inactivated vaccine is an effective strategy to prevent the COVID-19 pandemic. However, the detailed molecular immune response at single-cell level is poorly understood. In this study, we systematically delineated the landscape of the pre- and post-vaccination single-cell transcriptome, TCR (T cell antigen receptor) and BCR (B cell antigen receptor) expression profile of vaccinated candidates. The bulk TCR sequencing analysis of COVID-19 patients was also performed. Enrichment of a clonal CD8+ T cell cluster expressing specific TCR was identified in both vaccination candidates and COVID-19 patients. These clonal CD8+ T cells showed high expression of cytotoxicity, phagosome and antigen presentation related genes. The cell-cell interaction analysis revealed that monocytes and dendritic cells could interact with these cells and initiate phagocytosis via ICAM1-ITGAM and ITGB2 signaling. Together, our study systematically deciphered the detailed immunological response during SARS-CoV-2 vaccination and infection. It may facilitate understanding the immune response and the T-cell therapy against COVID-19.

Screening of cell-virus, cell-cell, gene-gene crosstalk among animal kingdom at single cell resolution.

BACKGROUND: The exact animal origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains obscure and understanding its host range is vital for preventing interspecies transmission. METHODS: Herein, we applied single-cell sequencing to multiple tissues of 20 species (30 data sets) and integrated them with public resources (45 data sets covering 26 species) to expand the virus receptor distribution investigation. While the binding affinity between virus and receptor is essential for viral infectivity, understanding the receptor distribution could predict the permissive organs and tissues when infection occurs. RESULTS: Based on the transcriptomic data, the expression profiles of receptor or associated entry factors for viruses capable of causing respiratory, blood, and brain diseases were described in detail. Conserved cellular connectomes and regulomes were also identified, revealing fundamental cell-cell and gene-gene cross-talks from reptiles to humans. CONCLUSIONS: Overall, our study provides a resource of the single-cell atlas of the animal kingdom which could help to identify the potential host range and tissue tropism of viruses and reveal the host-virus co-evolution.

Single-cell transcriptomic atlas reveals distinct immunological responses between COVID-19 vaccine and natural SARS-CoV-2 infection.

To control the ongoing coronavirus disease-2019 (COVID-19) pandemic, CoronaVac (Sinovac), an inactivated vaccine, has been granted emergency use authorization by many countries. However, the underlying mechanisms of the inactivated COVID-19 vaccine-induced immune response remain unclear, and little is known about its features compared to (Severe acute respiratory syndrome coronavirus 2) SARS-CoV-2 infection. Here, we implemented single-cell RNA sequencing (scRNA-seq) to profile longitudinally collected PBMCs (peripheral blood mononuclear cells) in six individuals immunized with CoronaVac and compared these to the profiles of COVID-19 infected patients from a Single Cell Consortium. Both inactivated vaccines and SARS-CoV-2 infection altered the proportion of different immune cell types, caused B cell activation and differentiation, and induced the expression of genes associated with antibody production in the plasma. The inactivated vaccine and SARS-COV-2 infection also caused alterations in peripheral immune activity such as interferon response, inflammatory cytokine expression, innate immune cell apoptosis and migration, effector T cell exhaustion and cytotoxicity, however, the magnitude of change was greater in COVID-19 patients, especially those with severe disease, than in immunized individuals. Further analyses revealed a distinct peripheral immune cell phenotype associated with CoronaVac immunization (HLA class II upregulation and IL21R upregulation in naïve B cells) versus SARS-CoV-2 infection (HLA class II downregulation and IL21R downregulation in naïve B cells from severe disease individuals). There were also differences in the expression of important genes associated with proinflammatory cytokines and thrombosis. In conclusion, this study provides a single-cell atlas of the systemic immune response to CoronaVac immunization and revealed distinct immune responses between inactivated vaccines and SARS-CoV-2 infection.

Tongue immune compartment analysis reveals spatial macrophage heterogeneity.

The tongue is a unique muscular organ situated in the oral cavity where it is involved in taste sensation, mastication, and articulation. As a barrier organ, which is constantly exposed to environmental pathogens, the tongue is expected to host an immune cell network ensuring local immune defence. However, the composition and the transcriptional landscape of the tongue immune system are currently not completely defined. Here, we characterised the tissue-resident immune compartment of the murine tongue during development, health and disease, combining single-cell RNA-sequencing with in situ immunophenotyping. We identified distinct local immune cell populations and described two specific subsets of tongue-resident macrophages occupying discrete anatomical niches. Cx3cr1+ macrophages were located specifically in the highly innervated lamina propria beneath the tongue epidermis and at times in close proximity to fungiform papillae. Folr2+ macrophages were detected in deeper muscular tissue. In silico analysis indicated that the two macrophage subsets originate from a common proliferative precursor during early postnatal development and responded differently to systemic LPS in vivo. Our description of the under-investigated tongue immune system sets a starting point to facilitate research on tongue immune-physiology and pathology including cancer and taste disorders.