Single-cell RNA-seq methods to interrogate virus-host interactions

Conventional and antibody-enhanced DENV infection of human macrophages induces differential immunotranscriptomic profiles

Dengue virus (DENV) is a mosquito-borne flavivirus which coexists as four genetically and immunologically distinct serotypes (DENV-1 to -4). In secondary heterologous DENV infection, pre-existing immunity is believed to contribute to severe disease through antibody-dependent enhancement (ADE). Although the elevated pathology observed in ADE conditions has been described, the cell-intrinsic mechanisms governing this process remain unclear. Using single-cell RNA sequencing (scRNAseq), we investigated the transcriptomic profiles of human monocyte-derived macrophages infected by DENV-2 in ADE compared to conventional infection conditions. Unsupervised analysis of scRNAseq data enabled the identification of two distinct cell populations in a heterogeneous cell culture, likely representing infected and bystander/uninfected cells. Differential gene expression and ingenuity pathway analyses revealed a number of significantly upregulated and downregulated genes and gene networks between cells infected by ADE compared to conventional infection. Specifically, these pathways indicated mechanisms such as suppressed interferon signaling and inflammatory chemokine transcription in cells infected via ADE. Further analysis revealed that transcriptomic changes were independent of viral RNA within infected cells, suggesting that the observed changes are reflective of cell-intrinsic responses and not simply a function of per-cell viral burden. The interpreted "bystander" cell population also demonstrated distinct profiles in ADE conditions, indicating an immunologically activated phenotype enriched for the expression of gene networks involved with protein translation, cytokine production, and antigen presentation. Together, these findings support the concept that DENV infection via ADE induces a qualitatively different transcriptomic response in infected cells, contributing to our understanding of ADE as a mechanistic driver of disease and pathogenesis.IMPORTANCEDengue virus (DENV) is a mosquito-borne human pathogen with a significant and growing global health burden. Although correlates of severe dengue disease are poorly understood, pre-existing immunity to DENV has been associated with severe disease risk and known to contribute to an alternative route of viral entry termed antibody-dependent enhancement (ADE). Using single-cell RNA sequencing, we identified distinct transcriptomic processes involved in antibody-mediated DENV entry compared to conventional receptor-mediated entry. These data provide meaningful insight into the discrete processes contributing to DENV pathogenesis in ADE conditions.

Droplet microfluidics: unveiling the hidden complexity of the human microbiome

The human body harbors diverse microbial communities essential for maintaining health and influencing disease processes. Droplet microfluidics, a precise and high-throughput platform for manipulating microscale droplets, has become vital in advancing microbiome research. This review introduces the foundational principles of droplet microfluidics, its operational capabilities, and wide-ranging applications. We emphasize its role in enhancing single-cell sequencing technologies, particularly genome and RNA sequencing, transforming our understanding of microbial diversity, gene expression, and community dynamics. We explore its critical function in isolating and cultivating traditionally unculturable microbes and investigating microbial activity and interactions, facilitating deeper insight into community behavior and metabolic functions. Lastly, we highlight its broader applications in microbial analysis and its potential to revolutionize human health research by driving innovations in diagnostics, therapeutic development, and personalized medicine. This review provides a comprehensive overview of droplet microfluidics' impact on microbiome research, underscoring its potential to transform our understanding of microbial dynamics and their relevance to health and disease.

GraphVelo allows for accurate inference of multimodal omics velocities and molecular mechanisms for single cells

RNA velocities and generalizations emerge as powerful approaches for extracting time-resolved information from high-throughput snapshot single-cell data. Yet, several inherent limitations restrict applying the approaches to genes not suitable for RNA velocity inference due to complex transcriptional dynamics, low expression, or lacking splicing dynamics, or data of non-transcriptomic modality. Here, we present GraphVelo, a graph-based machine learning procedure that uses as input the RNA velocities inferred from existing methods and infers velocity vectors lying in the tangent space of the low-dimensional manifold formed by the single cell data. GraphVelo preserves vector magnitude and direction information during transformations across different data representations. Tests on multiple synthetic and experimental scRNA-seq data including viral-host interactome and multi-omics datasets demonstrate that GraphVelo, together with downstream generalized dynamo analyses, extends RNA velocities to multi-modal data and reveals quantitative nonlinear regulation relations between genes, virus and host cells, and different layers of gene regulation.

GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells

RNA velocities and generalizations emerge as powerful approaches for extracting time-resolved information from high-throughput snapshot single-cell data. Yet, several inherent limitations restrict applying the approaches to genes not suitable for RNA velocity inference due to complex transcriptional dynamics, low expression, or lacking splicing dynamics, or data of non-transcriptomic modality. Here, we present GraphVelo, a graph-based machine learning procedure that uses as input the RNA velocities inferred from existing methods and infers velocity vectors lying in the tangent space of the low-dimensional manifold formed by the single cell data. GraphVelo preserves vector magnitude and direction information during transformations across different data representations. Tests on multiple synthetic and experimental scRNA-seq data including viral-host interactome and multi-omics datasets demonstrate that GraphVelo, together with downstream generalized dynamo analyses, extends RNA velocities to multi-modal data and reveals quantitative nonlinear regulation relations between genes, virus and host cells, and different layers of gene regulation.

Artificial Intelligence Methods in Infection Biology Research

Despite unprecedented achievements, the domain-specific application of artificial intelligence (AI) in the realm of infection biology was still in its infancy just a couple of years ago. This is largely attributable to the proneness of the infection biology community to shirk quantitative techniques. The so-called "sorting machine" paradigm was prevailing at that time, meaning that AI applications were primarily confined to the automation of tedious laboratory tasks. However, fueled by the severe acute respiratory syndrome coronavirus 2 pandemic, AI-driven applications in infection biology made giant leaps beyond mere automation. Instead, increasingly sophisticated tasks were successfully tackled, thereby ushering in the transition to the "Swiss army knife" paradigm. Incentivized by the urgent need to subdue a raging pandemic, AI achieved maturity in infection biology and became a versatile tool. In this chapter, the maturation of AI in the field of infection biology from the "sorting machine" paradigm to the "Swiss army knife" paradigm is outlined. Successful applications are illustrated for the three data modalities in the domain, that is, images, molecular data, and language data, with a particular emphasis on disentangling host-pathogen interactions. Along the way, fundamental terminology mentioned in the same breath as AI is elaborated on, and relationships between the subfields these terms represent are established. Notably, in order to dispel the fears of infection biologists toward quantitative methodologies and lower the initial hurdle, this chapter features a hands-on guide on software installation, virtual environment setup, data preparation, and utilization of pretrained models at its very end.

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.

Highlighting roles of autophagy in human diseases: a perspective from single-cell RNA sequencing analyses

Autophagy, the lysosome-driven breakdown of intracellular components, is pivotal in regulating eukaryotic cellular processes and maintaining homeostasis, making it physiologically important even under normal conditions. Cellular mechanisms involving autophagy include the response to nutrient deprivation, intracellular quality control, early development, and cell differentiation. Despite its established health significance, the role of autophagy in cancer and other diseases remains complex and not fully understood. A comprehensive understanding of autophagy is crucial to facilitate the development of novel therapies and drugs that can protect and improve human health. High-throughput technologies, such as single-cell RNA sequencing (scRNA-seq), have enabled researchers to study transcriptional landscapes at single-cell resolution, significantly advancing our knowledge of autophagy pathways across diverse physiological and pathological contexts. This review discusses the latest advances in scRNA-seq for autophagy research and highlights its potential in the molecular characterization of various diseases.

Single-cell transcriptional analysis of murine norovirus infection in a human intestinal cell line

Noroviruses are a major agent of acute gastroenteritis in humans, but host cell requirements for efficient replication in vitro have not been established. We engineered a human intestinal cell line (designated mCD300lf-hCaco2) expressing the murine norovirus (MNV) receptor, mouse CD300lf to become fully permissive for MNV replication. To explore the replicative machinery and host response of these cells, we performed a single-cell RNA sequencing (scRNA-seq) transcriptomics analysis of an MNV infection over time. Marked similarities were observed between certain global features of MNV infection in human cells compared to those previously reported in mouse cells by whole population transcriptomics such as downregulation of ribosome biogenesis, mitochondrial dysfunction, and cell cycle preference for G1. Our scRNA-seq analysis allowed further resolution of an infected cell population into distinct clusters with varying levels of viral RNA and interferon-stimulated gene ISG15 transcripts. Cells with high viral replication displayed downregulated ribosomal protein small (RPS) and large (RPL) genes and mitochondrial complexes I, III, IV, and V genes during exponential viral propagation. Ferritin subunit genes FTL and FTH1 were also downregulated during active MNV replication, suggesting that inhibition of iron metabolism may increase replication efficiency. Consistent with this, transcriptional activation of these genes with ferric ammonium citrate and overexpression of FTL lowered virus yields. Comparative studies of cells that support varying levels of norovirus replication efficiency, as determined by scRNA-seq may lead to improved human cell-based culture systems and effective viral interventions.IMPORTANCEHuman noroviruses cause acute gastroenteritis in all age groups. Vaccines and antiviral drugs are not yet available, in part, because it is difficult to propagate the viruses causing human disease in standard laboratory cell culture systems. In contrast, a norovirus found in mice [murine norovirus (MNV)] replicates efficiently in murine-based cell culture and has served as a model system. In this study, we established a new human intestinal cell line that was genetically modified to express the murine norovirus receptor so that the human cells became permissive to murine norovirus infection. We then defined the host response to MNV infection in the engineered human cell line at a single-cell resolution and identified cellular genes associated with the highest levels of MNV replication. This study may lead to the improvement of the current human norovirus cell culture systems and help to identify norovirus-host interactions that could be targeted for antiviral drugs.

Unraveling flavivirus pathogenesis: from bulk to single-cell RNA-sequencing strategies

The global spread of flaviviruses has triggered major outbreaks worldwide, significantly impacting public health, society, and economies. This has intensified research efforts to understand how flaviviruses interact with their hosts and manipulate the immune system, underscoring the need for advanced research tools. RNA-sequencing (RNA-seq) technologies have revolutionized our understanding of flavivirus infections by offering transcriptome analysis to dissect the intricate dynamics of virus-host interactions. Bulk RNA-seq provides a macroscopic overview of gene expression changes in virus-infected cells, offering insights into infection mechanisms and host responses at the molecular level. Single-cell RNA sequencing (scRNAseq) provides unprecedented resolution by analyzing individual infected cells, revealing remarkable cellular heterogeneity within the host response. A particularly innovative advancement, virus-inclusive single-cell RNA sequencing (viscRNA-seq), addresses the challenges posed by non-polyadenylated flavivirus genomes, unveiling intricate details of virus-host interactions. In this review, we discuss the contributions of bulk RNA-seq, scRNA-seq, and viscRNA-seq to the field, exploring their implications in cell line experiments and studies on patients infected with various flavivirus species. Comprehensive transcriptome analyses from RNA-seq technologies are pivotal in accelerating the development of effective diagnostics and therapeutics, paving the way for innovative treatments and enhancing our preparedness for future outbreaks.

Primary nasal influenza infection rewires tissue-scale memory response dynamics

The nasal mucosa is often the initial site of respiratory viral infection, replication, and transmission. Understanding how infection shapes tissue-scale primary and memory responses is critical for designing mucosal therapeutics and vaccines. We generated a single-cell RNA-sequencing atlas of the murine nasal mucosa, sampling three regions during primary influenza infection and rechallenge. Compositional analysis revealed restricted infection to the respiratory mucosa with stepwise changes in immune and epithelial cell subsets and states. We identified and characterized a rare subset of Krt13+ nasal immune-interacting floor epithelial (KNIIFE) cells, which concurrently increased with tissue-resident memory T (TRM)-like cells. Proportionality analysis, cell-cell communication inference, and microscopy underscored the CXCL16-CXCR6 axis between KNIIFE and TRM cells. Secondary influenza challenge induced accelerated and coordinated myeloid and lymphoid responses without epithelial proliferation. Together, this atlas serves as a reference for viral infection in the upper respiratory tract and highlights the efficacy of local coordinated memory responses.

Adapting the rhizome concept to an extended definition of viral quasispecies and the implications for molecular evolution

The rhizome concept proposed by Gilles Deleuze and Félix Guattari offers a novel perspective on the organization and interdependence of complex constellations of heterogeneous entities, their mapping and their ruptures. The emphasis of the present study is placed on the dynamics of contacts and communication among such entities that arise from experimentation, without any favored hierarchy or origin. When applied to biological evolution, the rhizome concept integrates all types of heterogeneity resulting from "symbiotic" relationships among living beings (or their genomic material), horizontal genetic transfer, recombination and mutation, and breaks away from the approach that gives rise to the phylogenetic tree of life. It has already been applied to describe the dynamics and evolution of RNA viruses. Thus, here we introduce a novel framework for the interpretation the viral quasispecies concept, which explains the evolution of RNA virus populations as the result of dynamic interconnections and multifaceted interdependence between highly heterogeneous viral sequences and its inherently heterogeneous host cells. The rhizome network perspective underlines even further the medical implications of the broad mutant spectra of viruses that are in constant flow, given the multiple pathways they have available for fitness loss and gain.

Bioinformatics and molecular biology tools for diagnosis, prevention, treatment and prognosis of COVID-19

Since December 2019, a new form of Severe Acute Respiratory Syndrome (SARS) has emerged worldwide, caused by SARS coronavirus 2 (SARS-CoV-2). This disease was called COVID-19 and was declared a pandemic by the World Health Organization in March 2020. Symptoms can vary from a common cold to severe pneumonia, hypoxemia, respiratory distress, and death. During this period of world stress, the medical and scientific community were able to acquire information and generate scientific data at unprecedented speed, to better understand the disease and facilitate vaccines and therapeutics development. Notably, bioinformatics tools were instrumental in decoding the viral genome and identifying critical targets for COVID-19 diagnosis and therapeutics. Through the integration of omics data, bioinformatics has also improved our understanding of disease pathogenesis and virus-host interactions, facilitating the development of targeted treatments and vaccines. Furthermore, molecular biology techniques have accelerated the design of sensitive diagnostic tests and the characterization of immune responses, paving the way for precision medicine approaches in treating COVID-19. Our analysis highlights the indispensable contributions of bioinformatics and molecular biology to the global effort against COVID-19. In this review, we aim to revise the COVID-19 features, diagnostic, prevention, treatment options, and how molecular biology, modern bioinformatic tools, and collaborations have helped combat this pandemic. An integrative literature review was performed, searching articles on several sites, including PUBMED and Google Scholar indexed in referenced databases, prioritizing articles from the last 3 years. The lessons learned from this COVID-19 pandemic will place the world in a much better position to respond to future pandemics.

A cell atlas of the adult female Aedes aegypti midgut revealed by single-cell RNA sequencing

Aedes aegypti is a primary vector for transmitting various arboviruses, including Yellow fever, dengue and Zika virus. The mosquito midgut is the principal organ for blood meal digestion, nutrient absorption and the initial site of arbovirus infection. Although a previous study delineated midgut's transcriptome of Ae. aegypti at the single-nucleus resolution, there still lacks an established protocol for isolating and RNA sequencing of single cells of Ae. aegypti midgut, which is required for investigating arbovirus-midgut interaction at the single-cell level. Here, we established an atlas of the midgut cells for Ae. aegypti by single-cell RNA sequencing. We annotated the cell clusters including intestinal stem cells/enteroblasts (ISC/EB), cardia cells (Cardia), enterocytes (EC, EC-like), enteroendocrine cells (EE), visceral muscle (VM), fat body cells (FBC) and hemocyte cells (HC). This study will provide a foundation for further studies of arbovirus infection in mosquito midgut at the single-cell level.

Single-cell analysis reveals an antiviral network that controls Zika virus infection in human dendritic cells

Zika virus (ZIKV) is a mosquito-borne flavivirus that caused an epidemic in the Americas in 2016 and is linked to severe neonatal birth defects, including microcephaly and spontaneous abortion. To better understand the host response to ZIKV infection, we adapted the 10× Genomics Chromium single-cell RNA sequencing (scRNA-seq) assay to simultaneously capture viral RNA and host mRNA. Using this assay, we profiled the antiviral landscape in a population of human monocyte-derived dendritic cells infected with ZIKV at the single-cell level. The bystander cells, which lacked detectable viral RNA, expressed an antiviral state that was enriched for genes coinciding predominantly with a type I interferon (IFN) response. Within the infected cells, viral RNA negatively correlated with type I IFN-dependent and -independent genes (the antiviral module). We modeled the ZIKV-specific antiviral state at the protein level, leveraging experimentally derived protein interaction data. We identified a highly interconnected network between the antiviral module and other host proteins. In this work, we propose a new paradigm for evaluating the antiviral response to a specific virus, combining an unbiased list of genes that highly correlate with viral RNA on a per-cell basis with experimental protein interaction data.

IMPORTANCE

Zika virus (ZIKV) remains a public health threat given its potential for re-emergence and the detrimental fetal outcomes associated with infection during pregnancy. Understanding the dynamics between ZIKV and its host is critical to understanding ZIKV pathogenesis. Through ZIKV-inclusive single-cell RNA sequencing (scRNA-seq), we demonstrate on the single-cell level the dynamic interplay between ZIKV and the host: the transcriptional program that restricts viral infection and ZIKV-mediated inhibition of that response. Our ZIKV-inclusive scRNA-seq assay will serve as a useful tool for gaining greater insight into the host response to ZIKV and can be applied more broadly to the flavivirus field.

OV Modulators of the Paediatric Brain TIME: Current Status, Combination Strategies, Limitations and Future Directions

Oncolytic viruses (OVs) are characterised by their preference for infecting and replicating in tumour cells either naturally or after genetic modification, resulting in oncolysis. Furthermore, OVs can elicit both local and systemic anticancer immune responses while specifically infecting and lysing tumour cells. These characteristics render them a promising therapeutic approach for paediatric brain tumours (PBTs). PBTs are frequently marked by a cold tumour immune microenvironment (TIME), which suppresses immunotherapies. Recent preclinical and clinical studies have demonstrated the capability of OVs to induce a proinflammatory immune response, thereby modifying the TIME. In-depth insights into the effect of OVs on different cell types in the TIME may therefore provide a compelling basis for using OVs in combination with other immunotherapy modalities. However, certain limitations persist in our understanding of oncolytic viruses' ability to regulate the TIME to enhance anti-tumour activity. These limitations primarily stem from the translational limitations of model systems, the difficulties associated with tracking reliable markers of efficacy throughout the course of treatment and the role of pre-existing viral immunity. In this review, we describe the different alterations observed in the TIME in PBTs due to OV treatment, combination therapies of OVs with different immunotherapies and the hurdles limiting the development of effective OV therapies while suggesting future directions based on existing evidence.

Single-cell sequencing reveals lung cell fate evolution initiated by smoking to explore gene predictions of correlative diseases

Continuous smoking leads to adaptive regulation and physiological changes in lung tissue and cells, and is an inductive factor for many diseases, making smokers face the risk of malignant and nonmalignant diseases. The impact of research in this area is getting more and more in-depth, but the stimulant effect, mechanism of action and response mechanism of the main cells in the lungs caused by smoke components have not yet been fully elucidated, and the early diagnosis and identification of various diseases induced by smoke toxins have not yet formed a systematic relationship method. In this study, single-cell transcriptome data were generated from three lung samples of smokers and nonsmokers through scRNA-seq technology, revealing the influence of smoking on lung tissue and cells and the changes in immune response. The results show that: through UMAP cell clustering, 16 intermediate cell states of 23 cell clusters of the four main cell types in the lung are revealed, the differences of the main cell groups between smokers and nonsmokers are explained, and the human lung cells are clarified. Components and their marker genes, screen for new marker genes that can be used in the evolution of intermediate-state cells, and at the same time, the analysis of lung cell subgroups reveals the changes in the intermediate state of cells under smoke stimulation, forming a subtype intermediate state cell map. Pseudo-time ordering analysis, to determine the pattern of dynamic processes experienced by cells, differential expression analysis of different branch cells, to clarify the expression rules of cells at different positions, to clarify the evolution process of the intermediate state of cells, and to clarify the response of lung tissue and cells to smoke components mechanism. The development of this study provides new diagnosis and treatment ideas for early disease detection, identification, disease prevention and treatment of patients with smoking-related diseases, and lays a theoretical foundation based on cell and molecular regulation.

Primary nasal viral infection rewires the tissue-scale memory response

The nasal mucosa is frequently the initial site of respiratory viral infection, replication, and transmission. Recent work has started to clarify the independent responses of epithelial, myeloid, and lymphoid cells to viral infection in the nasal mucosa, but their spatiotemporal coordination and relative contributions remain unclear. Furthermore, understanding whether and how primary infection shapes tissue-scale memory responses to secondary challenge is critical for the rational design of nasal-targeting therapeutics and vaccines. Here, we generated a single-cell RNA-sequencing (scRNA-seq) atlas of the murine nasal mucosa sampling three distinct regions before and during primary and secondary influenza infection. Primary infection was largely restricted to respiratory mucosa and induced stepwise changes in cell type, subset, and state composition over time. Type I Interferon (IFN)-responsive neutrophils appeared 2 days post infection (dpi) and preceded transient IFN-responsive/cycling epithelial cell responses 5 dpi, which coincided with broader antiviral monocyte and NK cell accumulation. By 8 dpi, monocyte-derived macrophages (MDMs) expressing Cxcl9 and Cxcl16 arose alongside effector cytotoxic CD8 and Ifng-expressing CD4 T cells. Following viral clearance (14 dpi), rare, previously undescribed Krt13+ nasal immune-interacting floor epithelial (KNIIFE) cells expressing multiple genes with immune communication potential increased concurrently with tissue-resident memory T (TRM)-like cells and early IgG+/IgA+ plasmablasts. Proportionality analysis coupled with cell-cell communication inference, alongside validation by in situ microscopy, underscored the CXCL16-CXCR6 signaling axis between MDMs and effector CD8 T cells 8dpi and KNIIFE cells and TRM cells 14 dpi. Secondary influenza challenge with a homologous or heterologous strain administered 60 dpi induced an accelerated and coordinated myeloid and lymphoid response without epithelial proliferation, illustrating how tissue-scale memory to natural infection engages both myeloid and lymphoid cells to reduce epithelial regenerative burden. Together, this atlas serves as a reference for viral infection in the upper respiratory tract and highlights the efficacy of local coordinated memory responses upon rechallenge.

Single cell RNA-seq: a novel tool to unravel virus-host interplay

Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.

Transcriptomic Responses to Koi Herpesvirus in Isolated Blood Leukocytes from Infected Common Carp

Koi herpesvirus (KHV, CyHV-3) causes severe economic losses in carp farms. Its eradication is challenging due to the establishment of latency in blood leukocytes and other tissues. To understand the molecular mechanisms leading to KHV infection in leukocytes, common carp were bath-exposed to KHV at 17 °C. After confirming the presence of viral transcripts in blood leukocytes at ten days post infection, RNA-Seq was performed on peripheral blood leukocytes on the Illumina NovaSeq. KHV infection triggered a robust immune response mediated by pattern recognition receptors, mainly toll-like receptors (tlr2, tlr5, tlr7, and tlr13), urokinase plasminogen activator surface receptor-like, galectin proteins, and lipid mediators such as leukotriene B4 receptor 1. Enriched pathways showed increased mitochondria oxidative phosphorylation and the activation of signalling pathways such as mitogen-activated protein kinases (MAPKs) and vascular endothelial growth factor (VEGF). KHV-infected leukocytes showed low production of reactive oxygen species (ROS) and glutathione metabolism, high iron export and phagocytosis activity, and low autophagy. Macrophage polarization was deduced from the up-regulation of genes such as arginase non-hepatic 1-like, macrophage mannose receptor-1, crem, il-10, and il-13 receptors, while markers for cytotoxic T cells were observed to be down-regulated. Further work is required to characterise these leukocyte subsets and the molecular events leading to KHV latency in blood leukocytes.

Systems immunology of transcriptional responses to viral infection identifies conserved antiviral pathways across macaques and humans

Viral pandemics and epidemics pose a significant global threat. While macaque models of viral disease are routinely used, it remains unclear how conserved antiviral responses are between macaques and humans. Therefore, we conducted a cross-species analysis of transcriptomic data from over 6,088 blood samples from macaques and humans infected with one of 31 viruses. Our findings demonstrate that irrespective of primate or viral species, there are conserved antiviral responses that are consistent across infection phase (acute, chronic, or latent) and viral genome type (DNA or RNA viruses). Leveraging longitudinal data from experimental challenges, we identify virus-specific response kinetics such as host responses to Coronaviridae and Orthomyxoviridae infections peaking 1-3 days earlier than responses to Filoviridae and Arenaviridae viral infections. Our results underscore macaque studies as a powerful tool for understanding viral pathogenesis and immune responses that translate to humans, with implications for viral therapeutic development and pandemic preparedness.

Mechanistic insights into bone remodelling dysregulation by human viral pathogens

Bone-related diseases (osteopathologies) associated with human virus infections have increased around the globe. Recent findings have highlighted the intricate interplay between viral infection, the host immune system and the bone remodelling process. Viral infections can disrupt bone homeostasis, contributing to conditions such as arthritis and soft tissue calcifications. Osteopathologies can occur after arbovirus infections such as chikungunya virus, dengue virus and Zika virus, as well as respiratory viruses, such as severe acute respiratory syndrome coronavirus 2 and enteroviruses such as Coxsackievirus B. Here we explore how human viruses dysregulate bone homeostasis, detailing viral factors, molecular mechanisms, host immune response changes and bone remodelling that ultimately result in osteopathologies. We highlight model systems and technologies to advance mechanistic understanding of viral-mediated bone alterations. Finally, we propose potential prophylactic and therapeutic strategies, introduce 'osteovirology' as a research field highlighting the underestimated roles of viruses in bone-related diseases, and discuss research avenues for further investigation.

Single cell analysis reveals an antiviral network that controls Zika virus infection in human dendritic cells

Zika virus (ZIKV) is a mosquito-borne flavivirus that caused an epidemic in the Americas in 2016 and is linked to severe neonatal birth defects, including microcephaly and spontaneous abortion. To better understand the host response to ZIKV infection, we adapted the 10x Genomics Chromium single cell RNA sequencing (scRNA-seq) assay to simultaneously capture viral RNA and host mRNA. Using this assay, we profiled the antiviral landscape in a population of human moDCs infected with ZIKV at the single cell level. The bystander cells, which lacked detectable viral RNA, expressed an antiviral state that was enriched for genes coinciding predominantly with a type I interferon (IFN) response. Within the infected cells, viral RNA negatively correlated with type I IFN dependent and independent genes (antiviral module). We modeled the ZIKV specific antiviral state at the protein level leveraging experimentally derived protein-interaction data. We identified a highly interconnected network between the antiviral module and other host proteins. In this work, we propose a new paradigm for evaluating the antiviral response to a specific virus, combining an unbiased list of genes that highly correlate with viral RNA on a per cell basis with experimental protein interaction data. Our ZIKV-inclusive scRNA-seq assay will serve as a useful tool to gaining greater insight into the host response to ZIKV and can be applied more broadly to the flavivirus field.

Heat Inactivation of Nipah Virus for Downstream Single-Cell RNA Sequencing Does Not Interfere with Sample Quality

Single-cell RNA sequencing (scRNA-seq) technologies are instrumental to improving our understanding of virus-host interactions in cell culture infection studies and complex biological systems because they allow separating the transcriptional signatures of infected versus non-infected bystander cells. A drawback of using biosafety level (BSL) 4 pathogens is that protocols are typically developed without consideration of virus inactivation during the procedure. To ensure complete inactivation of virus-containing samples for downstream analyses, an adaptation of the workflow is needed. Focusing on a commercially available microfluidic partitioning scRNA-seq platform to prepare samples for scRNA-seq, we tested various chemical and physical components of the platform for their ability to inactivate Nipah virus (NiV), a BSL-4 pathogen that belongs to the group of nonsegmented negative-sense RNA viruses. The only step of the standard protocol that led to NiV inactivation was a 5 min incubation at 85 °C. To comply with the more stringent biosafety requirements for BSL-4-derived samples, we included an additional heat step after cDNA synthesis. This step alone was sufficient to inactivate NiV-containing samples, adding to the necessary inactivation redundancy. Importantly, the additional heat step did not affect sample quality or downstream scRNA-seq results.

Single-Cell RNA-Sequencing of RVFV Infection

On the RNA level, viral infections are characterized by perturbations in the host cell transcriptome as well as the development of viral genetic information. Investigating the abundance and dynamic of RNA molecules can provide ample information to understand many aspects of the infection, from viral replication to pathogenesis. A key aspect therein is the resolution of the data, as infections are generally highly heterogeneous. Even in simple model systems such as cell lines, viral infections happen in a very asynchronous way. Quantifying RNAs at single-cell resolution can therefore substantially increase our understanding of these processes.Whereas measuring the RNA in bulk, that is, in samples containing thousands to hundreds of thousands of cells, is established and widely used since many years, methods for studying not only just a few different RNAs in individual cells became widely available only recently. Here, I outline and compare current concepts and methodologies for using single-cell RNA-sequencing to study virus infections. This covers sample preparation, cell preservation, biosafety considerations, and various experimental methods, with a special focus on the aspects that are important for studying virus infections. Since there is not "the one" method for doing single-cell RNA-sequencing, I will not provide a detailed protocol. Rather, this chapter should serve as a primer for getting started with single-cell RNA-sequencing experiments of virus infections and discusses the criteria that allow readers to choose the best procedures for their specific research question.

From bench to bedside via bytes: Multi-omic immunoprofiling and integration using machine learning and network approaches

A significant surge in research endeavors leverages the vast potential of high-throughput omic technology platforms for broad profiling of biological responses to vaccines and cutting-edge immunotherapies and stem-cell therapies under development. These profiles capture different aspects of core regulatory and functional processes at different scales of resolution from molecular and cellular to organismal. Systems approaches capture the complex and intricate interplay between these layers and scales. Here, we summarize experimental data modalities, for characterizing the genome, epigenome, transcriptome, proteome, metabolome, and antibody-ome, that enable us to generate large-scale immune profiles. We also discuss machine learning and network approaches that are commonly used to analyze and integrate these modalities, to gain insights into correlates and mechanisms of natural and vaccine-mediated immunity as well as therapy-induced immunomodulation.

Development trends of human organoid-based COVID-19 research based on bibliometric analysis

Coronavirus disease 2019 (COVID-19), a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has posed a catastrophic threat to human health worldwide. Human stem cell-derived organoids serve as a promising platform for exploring SARS-CoV-2 infection. Several review articles have summarized the application of human organoids in COVID-19, but the research status and development trend of this field have seldom been systematically and comprehensively studied. In this review, we use bibliometric analysis method to identify the characteristics of organoid-based COVID-19 research. First, an annual trend of publications and citations, the most contributing countries or regions and organizations, co-citation analysis of references and sources and research hotspots are determined. Next, systematical summaries of organoid applications in investigating the pathology of SARS-CoV-2 infection, vaccine development and drug discovery, are provided. Lastly, the current challenges and future considerations of this field are discussed. The present study will provide an objective angle to identify the current trend and give novel insights for directing the future development of human organoid applications in SARS-CoV-2 infection.

Neutrophil heterogeneity and aging: implications for COVID-19 and wound healing

Neutrophils play a critical role in the immune response to infection and tissue injury. However, recent studies have shown that neutrophils are a heterogeneous population with distinct subtypes that differ in their functional properties. Moreover, aging can alter neutrophil function and exacerbate immune dysregulation. In this review, we discuss the concept of neutrophil heterogeneity and how it may be affected by aging. We then examine the implications of neutrophil heterogeneity and aging for COVID-19 pathogenesis and wound healing. Specifically, we summarize the evidence for neutrophil involvement in COVID-19 and the potential mechanisms underlying neutrophil recruitment and activation in this disease. We also review the literature on the role of neutrophils in the wound healing process and how aging and neutrophil heterogeneity may impact wound healing outcomes. Finally, we discuss the potential for neutrophil-targeted therapies to improve clinical outcomes in COVID-19 and wound healing.

An atlas of immune cell transcriptomes in human immunodeficiency virus-infected immunological non-responders identified marker genes that control viral replication

BACKGROUND

Previous studies have examined the bulk transcriptome of peripheral blood immune cells in acquired immunodeficiency syndrome patients experiencing immunological non-responsiveness. This study aimed to investigate the characteristics of specific immune cell subtypes in acquired immunodeficiency syndrome patients who exhibit immunological non-responsiveness.

METHODS

A single-cell transcriptome sequencing of peripheral blood mononuclear cells obtained from both immunological responders (IRs) (CD4 + T-cell count >500) and immunological non-responders (INRs) (CD4 + T-cell count <300) was conducted. The transcriptomic profiles were used to identify distinct cell subpopulations, marker genes, and differentially expressed genes aiming to uncover potential genetic factors associated with immunological non-responsiveness.

RESULTS

Among the cellular subpopulations analyzed, the ratios of monocytes, CD16 + monocytes, and exhausted B cells demonstrated the most substantial differences between INRs and IRs, with fold changes of 39.79, 11.08, and 2.71, respectively. In contrast, the CD4 + T cell ratio was significantly decreased (0.39-fold change) in INRs compared with that in IRs. Similarly, the ratios of natural killer cells and terminal effector CD8 + T cells were also lower (0.37-fold and 0.27-fold, respectively) in the INRs group. In addition to several well-characterized immune cell-specific markers, we identified a set of 181 marker genes that were enriched in biological pathways associated with human immunodeficiency virus (HIV) replication. Notably, ISG15 , IFITM3 , PLSCR1 , HLA-DQB1 , CCL3L1 , and DDX5 , which have been demonstrated to influence HIV replication through their interaction with viral proteins, emerged as significant monocyte marker genes. Furthermore, the differentially expressed genes in natural killer cells were also enriched in biological pathways associated with HIV replication.

CONCLUSIONS

We generated an atlas of immune cell transcriptomes in HIV-infected IRs and INRs. Host genes associated with HIV replication were identified as markers of, and were found to be differentially expressed in, different types of immune cells.

Understanding virus-host interactions in tissues

Although virus-host interactions are usually studied in a single cell type using in vitro assays in immortalized cell lines or isolated cell populations, it is important to remember that what is happening inside one infected cell does not translate to understanding how an infected cell behaves in a tissue, organ or whole organism. Infections occur in complex tissue environments, which contain a host of factors that can alter the course of the infection, including immune cells, non-immune cells and extracellular-matrix components. These factors affect how the host responds to the virus and form the basis of the protective response. To understand virus infection, tools are needed that can profile the tissue environment. This Review highlights methods to study virus-host interactions in the infection microenvironment.

RevGel-seq: instrument-free single-cell RNA sequencing using a reversible hydrogel for cell-specific barcoding

Progress in sample preparation for scRNA-seq is reported based on RevGel-seq, a reversible-hydrogel technology optimized for samples of fresh cells. Complexes of one cell paired with one barcoded bead are stabilized by a chemical linker and dispersed in a hydrogel in the liquid state. Upon gelation on ice the complexes are immobilized and physically separated without requiring nanowells or droplets. Cell lysis is triggered by detergent diffusion, and RNA molecules are captured on the adjacent barcoded beads for further processing with reverse transcription and preparation for cDNA sequencing. As a proof of concept, analysis of PBMC using RevGel-seq achieves results similar to microfluidic-based technologies when using the same original sample and the same data analysis software. In addition, a clinically relevant application of RevGel-seq is presented for pancreatic islet cells. Furthermore, characterizations carried out on cardiomyocytes demonstrate that the hydrogel technology readily accommodates very large cells. Standard analyses are in the 10,000-input cell range with the current gelation device, in order to satisfy common requirements for single-cell research. A convenient stopping point after two hours has been established by freezing at the cell lysis step, with full preservation of gene expression profiles. Overall, our results show that RevGel-seq represents an accessible and efficient instrument-free alternative, enabling flexibility in terms of experimental design and timing of sample processing, while providing broad coverage of cell types.