Single-Cell Virus Sequencing of Influenza Infections That Trigger Innate Immunity

Amino acids in the polymerase complex of shorebird-isolated H1N1 influenza virus impact replication and host-virus interactions in mammalian models

A diverse population of avian influenza A viruses (AIVs) are maintained in wild birds and ducks yet the zoonotic potential of AIVs in these environmental reservoirs and the host-virus interactions involved in mammalian infection are not well understood. In studies of a group of subtype H1N1 AIVs isolated from migratory wild birds during surveillance in North America, we previously identified eight amino acids in the polymerase genes PB2 and PB1 that were important for the transmissibility of these AIVs in a ferret model of human influenza virus transmission. In this current study we found that PB2 containing amino acids associated with transmissibility at 67, 152, 199, 508, and 649 and PB1 at 298, 642, and 667 were associated with more rapid viral replication kinetics, greater infectivity, more active polymerase complexes and greater kinetics of viral genome replication and transcription. Pathogenicity in the mouse model was also impacted, evident as greater weight loss and lung pathology associated with greater inflammatory lung cytokine expression. Further, these AIVs all contained the avian-type amino acids of PB2-E627, D701, G590, Q591 and T271. Therefore, our study provides novel insights into the role of the AIV polymerase complex in the zoonotic transmission of AIVs in mammals.

All the single cells: if you like it then you should put some virus on it

Across a rich 70-year history, single-cell virology has revealed the impact of host and pathogen heterogeneity during virus infections. Recent technological innovations have enabled higher-resolution analyses of cellular and viral heterogeneity. Furthermore, single-cell analysis has revealed extreme phenotypes and provided additional insights into host-pathogen dynamics. Using a single-cell approach to explore fundamental virology questions, contemporary researchers have contributed to a revival of interest in single-cell virology with increased insights and enthusiasm.

Structure and dynamics of enterovirus genotype networks

Like all biological populations, viral populations exist as networks of genotypes connected through mutation. Mapping the topology of these networks and quantifying population dynamics across them is crucial to understanding how populations adapt to changes in their selective environment. The influence of mutational networks is especially profound in viral populations that rapidly explore their mutational neighborhoods via high mutation rates. Using a single-cell sequencing method, scRNA-seq-enabled acquisition of mRNA and consensus haplotypes linking individual genotypes and host transcriptomes (SEARCHLIGHT), we captured and assembled viral haplotypes from hundreds of individual infected cells, revealing the complexity of viral population structures. We obtained these genotypes in parallel with host cell transcriptome information, enabling us to link host cell transcriptional phenotypes to the genetic structures underlying virus adaptation. Our examination of these structures reveals the common evolutionary dynamics of enterovirus populations and illustrates how viral populations reach through mutational "tunnels" to span evolutionary landscapes and maintain connection with multiple adaptive genotypes simultaneously.

Exposure of negative-sense viral RNA in the cytoplasm initiates innate immunity to West Nile virus

For many RNA viruses, immunity is triggered when RIG-I-like receptors (RLRs) detect viral RNA. However, only a minority of infected cells undergo innate immune activation. By examining these "first responder" cells during West Nile virus infection, we found that specific accumulation of anti- genomic negative-sense viral RNA (-vRNA) underlies innate immune activation and that RIG-I preferentially interacts with -vRNA. However, flaviviruses sequester -vRNA into membrane-bound replication compartments away from cytosolic sensors. We found that single-stranded -vRNA accumulates outside of replication compartments in "first responder" cells, rendering it accessible to RLRs. Exposure of this -vRNA occurs at late timepoints of infection, is linked to viral assembly, and depends on the expression of viral structural proteins. These findings reveal that while most infected cells replicate high levels of vRNA, release of -vRNA from replication compartments during assembly occurs at low frequency and is critical for initiation of innate immunity during flavivirus infection.

Advances in single-cell long-read sequencing technologies

With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.

High-throughput sequencing-based neutralization assay reveals how repeated vaccinations impact titers to recent human H1N1 influenza strains

The high genetic diversity of influenza viruses means that traditional serological assays have too low throughput to measure serum antibody neutralization titers against all relevant strains. To overcome this challenge, we have developed a sequencing-based neutralization assay that simultaneously measures titers against many viral strains using small serum volumes via a workflow similar to traditional neutralization assays. The key innovation is to incorporate unique nucleotide barcodes into the hemagglutinin (HA) genomic segment, and then pool viruses with numerous different barcoded HA variants and quantify infectivity of all of them simultaneously using next-generation sequencing. With this approach, a single researcher performed the equivalent of 2,880 traditional neutralization assays (80 serum samples against 36 viral strains) in approximately one month. We applied the sequencing-based assay to quantify the impact of influenza vaccination on neutralization titers against recent human H1N1 strains for individuals who had or had not also received a vaccine in the previous year. We found that the viral strain specificities of the neutralizing antibodies elicited by vaccination vary among individuals, and that vaccination induced a smaller increase in titers for individuals who had also received a vaccine the previous year-although the titers six months after vaccination were similar in individuals with and without the previous-year vaccination. We also identified a subset of individuals with low titers to a subclade of recent H1N1 even after vaccination. This study demonstrates the utility of high-throughput sequencing-based neutralization assays that enable titers to be simultaneously measured against many different viral strains. We provide a detailed experimental protocol (DOI: https://dx.doi.org/10.17504/protocols.io.kqdg3xdmpg25/v1) and a computational pipeline (https://github.com/jbloomlab/seqneut-pipeline) for the sequencing-based neutralization assays to facilitate the use of this method by others.

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.

Single-cell herpes simplex virus type 1 infection of neurons using drop-based microfluidics reveals heterogeneous replication kinetics

Single-cell analyses of viral infections reveal heterogeneity that is not detected by traditional population-level studies. This study applies drop-based microfluidics to investigate the dynamics of herpes simplex virus type 1 (HSV-1) infection of neurons at the single-cell level. We used micrometer-scale Matrigel beads, termed microgels, to culture individual murine superior cervical ganglia (SCG) neurons or epithelial cells. Microgel-cultured cells are encapsulated in individual media-in-oil droplets with a dual-fluorescent reporter HSV-1, enabling real-time observation of viral gene expression and replication. Infection within drops revealed that the kinetics of initial viral gene expression and replication were dependent on the inoculating dose. Notably, increasing inoculating doses led to earlier onset of viral gene expression and more frequent productive viral replication. These observations provide crucial insights into the complexity of HSV-1 infection in neurons and emphasize the importance of studying single-cell outcomes of viral infection. These techniques for cell culture and infection in drops provide a foundation for future virology and neurobiology investigations.

Unraveling the intricacies of host-pathogen interaction through single-cell genomics

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single-cell level. We review various studies that have used these tools to better understand host-pathogen dynamics in a variety of infectious disease contexts, including viral, bacterial, and parasitic diseases. We conclude by discussing how single-cell genomics can advance our understanding of host-pathogen interactions.

Single-cell RNA sequencing to understand host-virus interactions

Single-cell RNA sequencing (scRNA-seq) has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution. This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses. The applications of scRNA-seq in various virological studies are discussed in depth, which broaden the understanding of the immune atlas, host-virus interactions, and immune repertoire. scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.

The use of single-cell RNA-seq to study heterogeneity at varying levels of virus-host interactions

The outcome of viral infection depends on the diversity of the infecting viral population and the heterogeneity of the cell population that is infected. Until almost a decade ago, the study of these dynamic processes during viral infection was challenging and limited to certain targeted measurements. Presently, with the use of single-cell sequencing technology, the complex interface defined by the interactions of cells with infecting virus can now be studied across the breadth of the transcriptome in thousands of individual cells simultaneously. In this review, we will describe the use of single-cell RNA sequencing (scRNA-seq) to study the heterogeneity of viral infections, ranging from individual virions to the immune response between infected individuals. In addition, we highlight certain key experimental limitations and methodological decisions that are critical to analyzing scRNA-seq data at each scale.

Diversity and Complexity of Internally Deleted Viral Genomes in Influenza A Virus Subpopulations with Enhanced Interferon-Inducing Phenotypes

Influenza A virus (IAV) populations harbor large subpopulations of defective-interfering particles characterized by internally deleted viral genomes. These internally deleted genomes have demonstrated the ability to suppress infectivity and boost innate immunity, rendering them promising for therapeutic and immunogenic applications. In this study, we aimed to investigate the diversity and complexity of the internally deleted IAV genomes within a panel of plaque-purified avian influenza viruses selected for their enhanced interferon-inducing phenotypes. Our findings unveiled that the abundance and diversity of internally deleted viral genomes were contingent upon the viral subculture and plaque purification processes. We observed a heightened occurrence of internally deleted genomes with distinct junctions in viral clones exhibiting enhanced interferon-inducing phenotypes, accompanied by additional truncation in the nonstructural 1 protein linker region (NS1Δ76-86). Computational analyses suggest the internally deleted IAV genomes can encode a broad range of carboxy-terminally truncated and intrinsically disordered proteins with variable lengths and amino acid composition. Further research is imperative to unravel the underlying mechanisms driving the increased diversity of internal deletions within the genomes of viral clones exhibiting enhanced interferon-inducing capacities and to explore their potential for modulating cellular processes and immunity.

Single-cell Herpes Simplex Virus type-1 infection of neurons using drop-based microfluidics reveals heterogeneous replication kinetics

Single-cell analyses of viral infections often reveal heterogeneity that is not detected by traditional population-level studies. This study applies drop-based microfluidics to investigate the dynamics of HSV-1 infection of neurons at the single-cell level. We used micron-scale Matrigel beads, termed microgels, to culture individual murine Superior Cervical ganglia (SCG) neurons or epithelial cells. Microgel-cultured cells are subsequently enclosed in individual media-in-oil droplets with a dual fluorescent-reporter HSV-1, enabling real-time observation of viral gene expression and replication. Infection within drops revealed that the kinetics of initial viral gene expression and replication were dependent on the inoculating dose. Notably, increasing inoculating doses led to earlier onset of viral gene expression and more frequent productive viral replication. These observations provide crucial insights into the complexity of HSV-1 infection in neurons and emphasize the importance of studying single-cell outcomes of viral infection. The innovative techniques presented here for cell culture and infection in drops provide a foundation for future virology and neurobiology investigations.

Influenza virus transcription and progeny production are poorly correlated in single cells

The ultimate success of a viral infection at the cellular level is determined by the number of progeny virions produced. However, most single-cell studies of infection quantify the expression of viral transcripts and proteins, rather than the amount of progeny virions released from infected cells. Here, we overcome this limitation by simultaneously measuring transcription and progeny production from single influenza virus-infected cells by embedding nucleotide barcodes in the viral genome. We find that viral transcription and progeny production are poorly correlated in single cells. The cells that transcribe the most viral mRNA do not produce the most viral progeny and often represent aberrant infections that fail to express the influenza NS gene. However, only some of the discrepancy between transcription and progeny production can be explained by viral gene absence or mutations: there is also a wide range of progeny production among cells infected by complete unmutated virions. Overall, our results show that viral transcription is a relatively poor predictor of an infected cell's contribution to the progeny population.

Unambiguous detection of SARS-CoV-2 subgenomic mRNAs with single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-Seq) studies have provided critical insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). scRNA-Seq library preparation methods and data processing workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. Here, we compare different scRNA-Seq library preparation methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs). We show that compared to 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') libraries or 10X Genomics Chromium Next GEM Single Cell V(D)J (10X 5') libraries sequenced with standard read configurations, 10X 5' libraries sequenced with an extended length read 1 (R1) that covers both cell barcode and transcript sequence (termed "10X 5' with extended R1") increase the number of unambiguous reads spanning leader-sgmRNA junction sites. We further present a data processing workflow, single-cell coronavirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to viral sgmRNAs or viral genomic RNA (gRNA). We find that combining 10X 5' with extended R1 library preparation/sequencing and scCoVseq data processing maximizes the number of viral UMIs per cell quantified by scRNA-Seq. Corresponding sgmRNA expression levels are highly correlated with expression in matched bulk RNA-Seq data sets quantified with established tools for SARS-CoV-2 analysis. Using this scRNA-Seq approach, we find that SARS-CoV-2 gene expression is highly correlated across individual infected cells, which suggests that the proportion of viral sgmRNAs remains generally consistent throughout infection. Taken together, these results and corresponding data processing workflow enable robust quantification of coronavirus sgmRNA expression at single-cell resolution, thereby supporting high-resolution studies of viral RNA processes in individual cells. IMPORTANCE Single-cell RNA sequencing (scRNA-Seq) has emerged as a valuable tool to study host-virus interactions, especially for coronavirus disease 2019 (COVID-19). Here we compare the performance of different scRNA-Seq library preparation methods and sequencing strategies to detect SARS-CoV-2 RNAs and develop a data processing workflow to quantify unambiguous sequence reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. After establishing a workflow that maximizes the detection of SARS-CoV-2 subgenomic mRNAs, we explore patterns of SARS-CoV-2 gene expression across cells with variable levels of total viral RNA, assess host gene expression differences between infected and bystander cells, and identify non-canonical and lowly abundant SARS-CoV-2 RNAs. The sequencing and data processing strategies developed here can enhance studies of coronavirus RNA biology at single-cell resolution and thereby contribute to our understanding of viral pathogenesis.

Polypharmacology-based kinome screen identifies new regulators of KSHV reactivation

Kaposi's sarcoma-associated herpesvirus (KSHV) causes several human diseases including Kaposi's sarcoma (KS), a leading cause of cancer in Africa and in patients with AIDS. KS tumor cells harbor KSHV predominantly in a latent form, while typically <5% contain lytic replicating virus. Because both latent and lytic stages likely contribute to cancer initiation and progression, continued dissection of host regulators of this biological switch will provide insights into fundamental pathways controlling the KSHV life cycle and related disease pathogenesis. Several cellular protein kinases have been reported to promote or restrict KSHV reactivation, but our knowledge of these signaling mediators and pathways is incomplete. We employed a polypharmacology-based kinome screen to identify specific kinases that regulate KSHV reactivation. Those identified by the screen and validated by knockdown experiments included several kinases that enhance lytic reactivation: ERBB2 (HER2 or neu), ERBB3 (HER3), ERBB4 (HER4), MKNK2 (MNK2), ITK, TEC, and DSTYK (RIPK5). Conversely, ERBB1 (EGFR1 or HER1), MKNK1 (MNK1) and FRK (PTK5) were found to promote the maintenance of latency. Mechanistic characterization of ERBB2 pro-lytic functions revealed a signaling connection between ERBB2 and the activation of CREB1, a transcription factor that drives KSHV lytic gene expression. These studies provided a proof-of-principle application of a polypharmacology-based kinome screen for the study of KSHV reactivation and enabled the discovery of both kinase inhibitors and specific kinases that regulate the KSHV latent-to-lytic replication switch.

Cellular state landscape and herpes simplex virus type 1 infection progression are connected

Prediction, prevention and treatment of virus infections require understanding of cell-to-cell variability that leads to heterogenous disease outcomes, but the source of this heterogeneity has yet to be clarified. To study the multimodal response of single human cells to herpes simplex virus type 1 (HSV-1) infection, we mapped high-dimensional viral and cellular state spaces throughout the infection using multiplexed imaging and quantitative single-cell measurements of viral and cellular mRNAs and proteins. Here we show that the high-dimensional cellular state scape can predict heterogenous infections, and cells move through the cellular state landscape according to infection progression. Spatial information reveals that infection changes the cellular state of both infected cells and of their neighbors. The multiplexed imaging of HSV-1-induced cellular modifications links infection progression to changes in signaling responses, transcriptional activity, and processing bodies. Our data show that multiplexed quantification of responses at the single-cell level, across thousands of cells helps predict infections and identify new targets for antivirals.

Culture-Independent Workflow for Nanopore MinION-Based Sequencing of Influenza A Virus

Whole-genome sequencing (WGS) of influenza A virus (IAV) is crucial for identifying diverse subtypes and newly evolved variants and for selecting vaccine strains. In developing countries, where facilities are often inadequate, WGS is challenging to perform using conventional next-generation sequencers. In this study, we established a culture-independent, high-throughput native barcode amplicon sequencing workflow that can sequence all influenza subtypes directly from a clinical specimen. All segments of IAV in 19 clinical specimens, irrespective of their subtypes, were amplified simultaneously using a two-step reverse transcriptase PCR (RT-PCR) system. First, the library was prepared using the ligation sequencing kit, barcoded individually using the native barcodes, and sequenced on the MinION MK 1C platform with real-time base-calling. Then, subsequent data analyses were performed with the appropriate tools. WGS of 19 IAV-positive clinical samples was carried out successfully with 100% coverage and 3,975-fold mean coverage for all segments. This easy-to-install and low-cost capacity-building protocol took only 24 h complete from extracting RNA to obtaining finished sequences. Overall, we developed a high-throughput portable sequencing workflow ideal for resource-limited clinical settings, aiding in real-time surveillance, outbreak investigation, and the detection of emerging viruses and genetic reassortment events. However, further evaluation is required to compare its accuracy with other high-throughput sequencing technologies to validate the widespread application of these findings, including WGS from environmental samples. IMPORTANCE The Nanopore MinION-based influenza sequencing approach we are proposing makes it possible to sequence the influenza A virus, irrespective of its diverse serotypes, directly from clinical and environmental swab samples, so that we are not limited to virus culture. This third-generation, portable, multiplexing, and real-time sequencing strategy is highly convenient for local sequencing, particularly in low- and middle-income countries like Bangladesh. Furthermore, the cost-efficient sequencing method could provide new opportunities to respond to the early phase of an influenza pandemic and enable the timely detection of the emerging subtypes in clinical samples. Here, we meticulously described the entire process that might help the researcher who will follow this methodology in the future. Our findings suggest that this proposed method is ideal for clinical and academic settings and will aid in real-time surveillance and in the detection of potential outbreak agents and newly evolved viruses.

Maximal interferon induction by influenza lacking NS1 is infrequent owing to requirements for replication and export

Influenza A virus exhibits high rates of replicative failure due to a variety of genetic defects. Most influenza virions cannot, when acting as individual particles, complete the entire viral life cycle. Nevertheless influenza is incredibly successful in the suppression of innate immune detection and the production of interferons, remaining undetected in >99% of cells in tissue-culture models of infection. Notably, the same variation that leads to replication failure can, by chance, inactivate the major innate immune antagonist in influenza A virus, NS1. What explains the observed rarity of interferon production in spite of the frequent loss of this, critical, antagonist? By studying how genetic and phenotypic variation in a viral population lacking NS1 correlates with interferon production, we have built a model of the "worst-case" failure from an improved understanding of the steps at which NS1 acts in the viral life cycle to prevent the triggering of an innate immune response. In doing so, we find that NS1 prevents the detection of de novo innate immune ligands, defective viral genomes, and viral export from the nucleus, although only generation of de novo ligands appears absolutely required for enhanced detection of virus in the absence of NS1. Due to this, the highest frequency of interferon production we observe (97% of infected cells) requires a high level of replication in the presence of defective viral genomes with NS1 bearing an inactivating mutation that does not impact its partner encoded on the same segment, NEP. This is incredibly unlikely to occur given the standard variation found within a viral population, and would generally require direct, artificial, intervention to achieve at an appreciable rate. Thus from our study, we procure at least a partial explanation for the seeming contradiction between high rates of replicative failure and the rarity of the interferon response to influenza infection.

Semi-infectious particles contribute substantially to influenza virus within-host dynamics when infection is dominated by spatial structure

Influenza is an ribonucleic acid virus with a genome that comprises eight segments. Experiments show that the vast majority of virions fail to express one or more gene segments and thus cannot cause a productive infection on their own. These particles, called semi-infectious particles (SIPs), can induce virion production through complementation when multiple SIPs are present in an infected cell. Previous within-host influenza models did not explicitly consider SIPs and largely ignore the potential effects of coinfection during virus infection. Here, we constructed and analyzed two distinct models explicitly keeping track of SIPs and coinfection: one without spatial structure and the other implicitly considering spatial structure. While the model without spatial structure fails to reproduce key aspects of within-host influenza virus dynamics, we found that the model implicitly considering the spatial structure of the infection process makes predictions that are consistent with biological observations, highlighting the crucial role that spatial structure plays during an influenza infection. This model predicts two phases of viral growth prior to the viral peak: a first phase driven by fully infectious particles at the initiation of infection followed by a second phase largely driven by coinfections of fully infectious particles and SIPs. Fitting this model to two sets of data, we show that SIPs can contribute substantially to viral load during infection. Overall, the model provides a new interpretation of the in vivo exponential viral growth observed in experiments and a mechanistic explanation for why the production of large numbers of SIPs does not strongly impede viral growth. Being simple and predictive, our model framework serves as a useful tool to understand coinfection dynamics in spatially structured acute viral infections.

Influenza A virus reassortment is strain dependent

RNA viruses can exchange genetic material during coinfection, an interaction that creates novel strains with implications for viral evolution and public health. Influenza A viral genetic exchange can occur when genome segments from distinct strains reassort in coinfected cells. Predicting potential genomic reassortment between influenza strains has been a long-standing goal. Experimental coinfection studies have shed light on factors that limit or promote reassortment. However, determining the reassortment potential between diverse Influenza A strains has remained elusive. To address this challenge, we developed a high throughput genotyping approach to quantify reassortment among a diverse panel of human influenza virus strains encompassing two pandemics (swine and avian origin), three specific epidemics, and both circulating human subtypes A/H1N1 and A/H3N2. We found that reassortment frequency (the proportion of reassortants generated) is an emergent property of specific pairs of strains where strain identity is a predictor of reassortment frequency. We detect little evidence that antigenic subtype drives reassortment as intersubtype (H1N1xH3N2) and intrasubtype reassortment frequencies were, on average, similar. Instead, our data suggest that certain strains bias the reassortment frequency up or down, independently of the coinfecting partner. We observe that viral productivity is also an emergent property of coinfections, but uncorrelated to reassortment frequency; thus viral productivity is a separate factor affecting the total number of reassortants produced. Assortment of individual segments among progeny and pairwise segment combinations within progeny generally favored homologous combinations. These outcomes were not related to strain similarity or shared subtype but reassortment frequency was closely correlated to the proportion of both unique genotypes and of progeny with heterologous pairwise segment combinations. We provide experimental evidence that viral genetic exchange is potentially an individual social trait subject to natural selection, which implies the propensity for reassortment is not evenly shared among strains. This study highlights the need for research incorporating diverse strains to discover the traits that shift the reassortment potential to realize the goal of predicting influenza virus evolution resulting from segment exchange.

Unambiguous detection of SARS-CoV-2 subgenomic mRNAs with single cell RNA sequencing

Single cell RNA sequencing (scRNA-Seq) studies have provided critical insight into the pathogenesis of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), the causative agent of COronaVIrus Disease 2019 (COVID-19). scRNA-Seq workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. Here, we compare different scRNA-Seq methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs). We present a data processing strategy, single cell CoronaVirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to sgmRNAs or genomic RNA (gRNA). Compared to standard 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') and Chromium Next GEM Single Cell V(D)J (10X 5') sequencing, we find that 10X 5' with an extended read 1 (R1) sequencing strategy maximizes the detection of sgmRNAs by increasing the number of unambiguous reads spanning leader-sgmRNA junction sites. Using this method, we show that viral gene expression is highly correlated across cells suggesting a relatively consistent proportion of viral sgmRNA production throughout infection. Our method allows for quantification of coronavirus sgmRNA expression at single-cell resolution, and thereby supports high resolution studies of the dynamics of coronavirus RNA synthesis.

Polypharmacology-based kinome screen identifies new regulators of KSHV reactivation

Kaposi's sarcoma-associated herpesvirus (KSHV) causes several human diseases including Kaposi's sarcoma (KS), a leading cause of cancer in Africa and in patients with AIDS. KS tumor cells harbor KSHV predominantly in a latent form, while typically <5% contain lytic replicating virus. Because both latent and lytic stages likely contribute to cancer initiation and progression, continued dissection of host regulators of this biological switch will provide insights into fundamental pathways controlling the KSHV life cycle and related disease pathogenesis. Several cellular protein kinases have been reported to promote or restrict KSHV reactivation, but our knowledge of these signaling mediators and pathways is incomplete. We employed a polypharmacology-based kinome screen to identifiy specific kinases that regulate KSHV reactivation. Those identified by the screen and validated by knockdown experiments included several kinases that enhance lytic reactivation: ERBB2 (HER2 or neu ), ERBB3 (HER3), ERBB4 (HER4), MKNK2 (MNK2), ITK, TEC, and DSTYK (RIPK5). Conversely, ERBB1 (EGFR1 or HER1), MKNK1 (MNK1) and FRK (PTK5) were found to promote the maintenance of latency. Mechanistic characterization of ERBB2 pro-lytic functions revealed a signaling connection between ERBB2 and the activation of CREB1, a transcription factor that drives KSHV lytic gene expression. These studies provided a proof-of-principle application of a polypharmacology-based kinome screen for the study of KSHV reactivation and enabled the discovery of both kinase inhibitors and specific kinases that regulate the KSHV latent-to-lytic replication switch.

Author Summary

Kaposi's sarcoma-associated herpesvirus (KSHV) causes Kaposi's sarcoma, a cancer particularly prevalent in Africa. In cancer cells, the virus persists in a quiescent form called latency, in which only a few viral genes are made. Periodically, the virus switches into an active replicative cycle in which most of the viral genes are made and new virus is produced. What controls the switch from latency to active replication is not well understood, but cellular kinases, enzymes that control many cellular processes, have been implicated. Using a cell culture model of KSHV reactivation along with an innovative screening method that probes the effects of many cellular kinases simultaneously, we identified drugs that significantly limit KSHV reactivation, as well as specific kinases that either enhance or restrict KSHV replicative cycle. Among these were the ERBB kinases which are known to regulate growth of cancer cells. Understanding how these and other kinases contribute to the switch leading to production of more infectious virus helps us understand the mediators and mechanisms of KSHV diseases. Additionally, because kinase inhibitors are proving to be effective for treating other diseases including some cancers, identifying ones that restrict KSHV replicative cycle may lead to new approaches to treating KSHV-related diseases.

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

The twenty-first century has seen the emergence of many epidemic and pandemic viruses, with the most recent being the SARS-CoV-2-driven COVID-19 pandemic. As obligate intracellular parasites, viruses rely on host cells to replicate and produce progeny, resulting in complex virus and host dynamics during an infection. Single-cell RNA sequencing (scRNA-seq), by enabling broad and simultaneous profiling of both host and virus transcripts, represents a powerful technology to unravel the delicate balance between host and virus. In this review, we summarize technological and methodological advances in scRNA-seq and their applications to antiviral immunity. We highlight key scRNA-seq applications that have enabled the understanding of viral genomic and host response heterogeneity, differential responses of infected versus bystander cells, and intercellular communication networks. We expect further development of scRNA-seq technologies and analytical methods, combined with measurements of additional multi-omic modalities and increased availability of publicly accessible scRNA-seq datasets, to enable a better understanding of viral pathogenesis and enhance the development of antiviral therapeutics strategies.

Defective Interfering Particles of Influenza Virus and Their Characteristics, Impacts, and Use in Vaccines and Antiviral Strategies: A Systematic Review

Defective interfering particles (DIPs) are particles containing defective viral genomes (DVGs) generated during viral replication. DIPs have been found in various RNA viruses, especially in influenza viruses. Evidence indicates that DIPs interfere with the replication and encapsulation of wild-type viruses, namely standard viruses (STVs) that contain full-length viral genomes. DIPs may also activate the innate immune response by stimulating interferon synthesis. In this review, the underlying generation mechanisms and characteristics of influenza virus DIPs are summarized. We also discuss the potential impact of DIPs on the immunogenicity of live attenuated influenza vaccines (LAIVs) and development of influenza vaccines based on NS1 gene-defective DIPs. Finally, we review the antiviral strategies based on influenza virus DIPs that have been used against both influenza virus and SARS-CoV-2. This review provides systematic insights into the theory and application of influenza virus DIPs.

Levels of Influenza A Virus Defective Viral Genomes Determine Pathogenesis in the BALB/c Mouse Model

Defective viral genomes (DVGs), which are generated by the viral polymerase in error during RNA replication, can trigger innate immunity and are implicated in altering the clinical outcome of infection. Here, we investigated the impact of DVGs on innate immunity and pathogenicity in a BALB/c mouse model of influenza virus infection. We generated stocks of influenza viruses containing the internal genes of an H5N1 virus that contained different levels of DVGs (indicated by different genome-to-PFU ratios). In lung epithelial cells, the high-DVG stock was immunostimulatory at early time points postinfection. DVGs were amplified during virus replication in myeloid immune cells and triggered proinflammatory cytokine production. In the mouse model, infection with the different virus stocks produced divergent outcomes. The high-DVG stock induced an early type I interferon (IFN) response that limited viral replication in the lungs, resulting in minimal weight loss. In contrast, the virus stock with low levels of DVGs replicated to high titers and amplified DVGs over time, resulting in elevated levels of proinflammatory cytokines accompanied by rapid weight loss and increased morbidity and mortality. Our results suggest that the timing and levels of immunostimulatory DVGs generated during infection contribute to H5N1 pathogenesis. IMPORTANCE Mammalian infections with highly pathogenic avian influenza viruses (HPAIVs) cause severe disease associated with excessive proinflammatory cytokine production. Aberrant replication products, such as defective viral genomes (DVGs), can stimulate the antiviral response, and cytokine induction is associated with their emergence in vivo. We show that stocks of a recombinant virus containing HPAIV internal genes that differ in their amounts of DVGs have vastly diverse outcomes in a mouse model. The high-DVG stock resulted in extremely mild disease due to suppression of viral replication. Conversely, the stock that contained low DVGs but rapidly accumulated DVGs over the course of infection led to severe disease. Therefore, the timing of DVG amplification and proinflammatory cytokine production impact disease outcome, and these findings demonstrate that not all DVG generation reduces viral virulence. This study also emphasizes the crucial requirement to examine the quality of virus preparations regarding DVG content to ensure reproducible research.

Single-Cell Infection of Influenza A Virus Using Drop-Based Microfluidics

Drop-based microfluidics has revolutionized single-cell studies and can be applied toward analyzing tens of thousands to millions of single cells and their products contained within picoliter-sized drops. Drop-based microfluidics can shed insight into single-cell virology, enabling higher-resolution analysis of cellular and viral heterogeneity during viral infection. In this work, individual A549, MDCK, and siat7e cells were infected with influenza A virus (IAV) and encapsulated into 100-μm-size drops. Initial studies of uninfected cells encapsulated in drops demonstrated high cell viability and drop stability. Cell viability of uninfected cells in the drops remained above 75%, and the average drop radii changed by less than 3% following cell encapsulation and incubation over 24 h. Infection parameters were analyzed over 24 h from individually infected cells in drops. The number of IAV viral genomes and infectious viruses released from A549 and MDCK cells in drops was not significantly different from bulk infection as measured by reverse transcriptase quantitative PCR (RT-qPCR) and plaque assay. The application of drop-based microfluidics in this work expands the capacity to propagate IAV viruses and perform high-throughput analyses of individually infected cells. IMPORTANCE Drop-based microfluidics is a cutting-edge tool in single-cell research. Here, we used drop-based microfluidics to encapsulate thousands of individual cells infected with influenza A virus within picoliter-sized drops. Drop stability, cell loading, and cell viability were quantified from three different cell lines that support influenza A virus propagation. Similar levels of viral progeny as determined by RT-qPCR and plaque assay were observed from encapsulated cells in drops compared to bulk culture. This approach enables the ability to propagate influenza A virus from encapsulated cells, allowing for future high-throughput analysis of single host cell interactions in isolated microenvironments over the course of the viral life cycle.

Influenza A virus NS1 protein represses antiviral immune response by hijacking NF-κB to mediate transcription of type III IFN

Background

Non-structural protein 1 (NS1), one of the viral proteins of influenza A viruses (IAVs), plays a crucial role in evading host antiviral immune response. It is known that the IAV NS1 protein regulates the antiviral genes response mainly through several different molecular mechanisms in cytoplasm. Current evidence suggests that NS1 represses the transcription of IFNB1 gene by inhibiting the recruitment of Pol II to its exons and promoters in infected cells. However, IAV NS1 whether can utilize a common mechanism to antagonize antiviral response by interacting with cellular DNA and immune-related transcription factors in the nucleus, is not yet clear.

Methods

Chromatin immunoprecipitation and sequencing (ChIP-seq) was used to determine genome-wide transcriptional DNA-binding sites for NS1 and NF-κB in viral infection. Next, we used ChIP-reChIP, luciferase reporter assay and secreted embryonic alkaline phosphatase (SEAP) assay to provide information on the dynamic binding of NS1 and NF-κB to chromatin. RNA sequencing (RNA-seq) transcriptomic analyses were used to explore the critical role of NS1 and NF-κB in IAV infection as well as the detailed processes governing host antiviral response.

Results

Herein, NS1 was found to co-localize with NF-κB using ChIP-seq. ChIP-reChIP and luciferase reporter assay confirmed the co-localization of NS1 and NF-κB at type III IFN genes, such as IFNL1, IFNL2, and IFNL3. We discovered that NS1 disturbed binding manners of NF-κB to inhibit IFNL1 expression. NS1 hijacked NF-κB from a typical IFNL1 promoter to the exon-intron region of IFNL1 and decreased the enrichment of RNA polymerase II and H3K27ac, a chromatin accessibility marker, in the promoter region of IFNL1 during IAV infection, consequently reducing IFNL1 gene expression. NS1 deletion enhanced the enrichment of RNA polymerase II at the IFNL1 promoter and promoted its expression.

Conclusion

Overall, NS1 hijacked NF-κB to prevent its interaction with the IFNL1 promoter and restricted the open chromatin architecture of the promoter, thereby abating antiviral gene expression.

Practical Considerations for Single-Cell Genomics

The single-cell revolution in the field of genomics is in full bloom, with clever new molecular biology tricks appearing regularly that allow researchers to explore new modalities or scale up their projects to millions of cells and beyond. Techniques abound to measure RNA expression, DNA alterations, protein abundance, chromatin accessibility, and more, all with single-cell resolution and often in combination. Despite such a rapidly changing technology landscape, there are several fundamental principles that are applicable to the majority of experimental workflows to help users avoid pitfalls and exploit the advantages of the chosen platform. In this overview article, we describe a variety of popular single-cell genomics technologies and address some common questions pertaining to study design, sample preparation, quality control, and sequencing strategy. As the majority of relevant publications currently revolve around single-cell RNA-seq, we will prioritize this genomics modality in our discussion. © 2022 Wiley Periodicals LLC.

In Vivo Profiling of Individual Multiciliated Cells during Acute Influenza A Virus Infection

Influenza virus infections are thought to be initiated in a small number of cells; however, the heterogeneity across the cellular responses of the epithelial cells during establishment of disease is incompletely understood. Here, we used an H1N1 influenza virus encoding a fluorescent reporter gene, a cell lineage-labeling transgenic mouse line, and single-cell RNA sequencing to explore the range of responses in a susceptible epithelial cell population during an acute influenza A virus (IAV) infection. Focusing on multiciliated cells, we identified a subpopulation that basally expresses interferon-stimulated genes (ISGs), which we hypothesize may be important for the early response to infection. We subsequently found that a population of infected ciliated cells produce most of the ciliated cell-derived inflammatory cytokines, and nearly all bystander ciliated cells induce a broadly antiviral state. From these data together, we propose that variable preexisting gene expression patterns in the initial cells targeted by the virus may ultimately affect the establishment of viral disease. IMPORTANCE Influenza A virus poses a significant threat to public health, and each year, millions of people in the United States alone are exposed to the virus. We do not currently, however, fully understand why some individuals clear the infection asymptomatically and others become severely ill. Understanding how these divergent phenotypes arise could eventually be leveraged to design therapeutics that prevent severe disease. As a first step toward understanding these different infection states, we used a technology that allowed us to determine how thousands of individual murine lung epithelial cells behaved before and during IAV infection. We found that small subsets of epithelial cells exhibited an antiviral state prior to infection, and similarly, some cells made high levels of inflammatory cytokines during infection. We propose that different ratios of these individual cellular responses may contribute to the broader antiviral state of the lung and may ultimately affect disease severity.

Natural Selection, Intracellular Bottlenecks of Virus Populations, and Viral Superinfection Exclusion

Natural selection acts on cellular organisms by ensuring the genes responsible for an advantageous phenotype consistently reap the phenotypic advantage. This is possible because reproductive cells of these organisms are almost always haploid, separating the beneficial gene from its rival allele at every generation. How natural selection acts on plus-strand RNA viruses is unclear because these viruses frequently load host cells with numerous genome copies and replicate thousands of progeny genomes in each cell. Recent studies suggest that these viruses encode the Bottleneck, Isolate, Amplify, Select (BIAS) mechanism that blocks all but a few viral genome copies from replication, thus creating the environment in which the bottleneck-escaping viral genome copies are isolated from each other, allowing natural selection to reward beneficial mutations and purge lethal errors. This BIAS mechanism also blocks the genomes of highly homologous superinfecting viruses, thus explaining cellular-level superinfection exclusion. Expected final online publication date for the Annual Review of Virology, Volume 9 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Temporal modelling using single-cell transcriptomics

Methods for profiling genes at the single-cell level have revolutionized our ability to study several biological processes and systems including development, differentiation, response programmes and disease progression. In many of these studies, cells are profiled over time in order to infer dynamic changes in cell states and types, sets of expressed genes, active pathways and key regulators. However, time-series single-cell RNA sequencing (scRNA-seq) also raises several new analysis and modelling issues. These issues range from determining when and how deep to profile cells, linking cells within and between time points, learning continuous trajectories, and integrating bulk and single-cell data for reconstructing models of dynamic networks. In this Review, we discuss several approaches for the analysis and modelling of time-series scRNA-seq, highlighting their steps, key assumptions, and the types of data and biological questions they are most appropriate for.

Human placental biology at single-cell resolution: a contemporaneous review

Single-cell technologies capture cellular heterogeneity to focus on previously poorly described subpopulations of cells. Work by our laboratory and many others has metagenomically characterised a low biomass intrauterine microbial community, alongside microbial transcripts, antigens and metabolites, but the functional importance of low biomass microbial communities in placental immuno-microenvironments is still being elucidated. Given their hypothesised role in modulating inflammation and immune ontogeny to enable tolerance of beneficial microbes while warding off pathogens, there is a need for single-cell resolution. Herein, we summarise the potential for mechanistic understanding of these and other key fundamental early developmental processes by applying single-cell approaches.

A spatial and cellular distribution of rabies virus infection in the mouse brain revealed by fMOST and single-cell RNA sequencing

BACKGROUND

Neurotropic virus infection can cause serious damage to the central nervous system (CNS) in both humans and animals. The complexity of the CNS poses unique challenges to investigate the infection of these viruses in the brain using traditional techniques.

METHODS

In this study, we explore the use of fluorescence micro-optical sectioning tomography (fMOST) and single-cell RNA sequencing (scRNA-seq) to map the spatial and cellular distribution of a representative neurotropic virus, rabies virus (RABV), in the whole brain. Mice were inoculated with a lethal dose of a recombinant RABV encoding enhanced green fluorescent protein (EGFP) under different infection routes, and a three-dimensional (3D) view of RABV distribution in the whole mouse brain was obtained using fMOST. Meanwhile, we pinpointed the cellular distribution of RABV by utilizing scRNA-seq.

RESULTS

Our fMOST data provided the 3D view of a neurotropic virus in the whole mouse brain, which indicated that the spatial distribution of RABV in the brain was influenced by the infection route. Interestingly, we provided evidence that RABV could infect multiple nuclei related to fear independent of different infection routes. More surprisingly, our scRNA-seq data revealed that besides neurons RABV could infect macrophages and the infiltrating macrophages played at least three different antiviral roles during RABV infection.

CONCLUSION

This study draws a comprehensively spatial and cellular map of typical neurotropic virus infection in the mouse brain, providing a novel and insightful strategy to investigate the pathogenesis of RABV and other neurotropic viruses.

Elevated temperature inhibits SARS-CoV-2 replication in respiratory epithelium independently of IFN-mediated innate immune defenses

The pandemic spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19), represents an ongoing international health crisis. A key symptom of SARS-CoV-2 infection is the onset of fever, with a hyperthermic temperature range of 38 to 41°C. Fever is an evolutionarily conserved host response to microbial infection that can influence the outcome of viral pathogenicity and regulation of host innate and adaptive immune responses. However, it remains to be determined what effect elevated temperature has on SARS-CoV-2 replication. Utilizing a three-dimensional (3D) air-liquid interface (ALI) model that closely mimics the natural tissue physiology of SARS-CoV-2 infection in the respiratory airway, we identify tissue temperature to play an important role in the regulation of SARS-CoV-2 infection. Respiratory tissue incubated at 40°C remained permissive to SARS-CoV-2 entry but refractory to viral transcription, leading to significantly reduced levels of viral RNA replication and apical shedding of infectious virus. We identify tissue temperature to play an important role in the differential regulation of epithelial host responses to SARS-CoV-2 infection that impact upon multiple pathways, including intracellular immune regulation, without disruption to general transcription or epithelium integrity. We present the first evidence that febrile temperatures associated with COVID-19 inhibit SARS-CoV-2 replication in respiratory epithelia. Our data identify an important role for tissue temperature in the epithelial restriction of SARS-CoV-2 independently of canonical interferon (IFN)-mediated antiviral immune defenses.

Single-Cell and Bulk RNA-Sequencing Reveal Differences in Monocyte Susceptibility to Influenza A Virus Infection Between Africans and Europeans

There is considerable inter-individual and inter-population variability in response to viruses. The potential of monocytes to elicit type-I interferon responses has attracted attention to their role in viral infections. Here, we use single-cell RNA-sequencing to characterize the role of cellular heterogeneity in human variation of monocyte responses to influenza A virus (IAV) exposure. We show widespread inter-individual variability in the percentage of IAV-infected monocytes. Notably, individuals with high cellular susceptibility to IAV are characterized by a lower activation at basal state of an IRF/STAT-induced transcriptional network, which includes antiviral genes such as IFITM3, MX1 and OAS3. Upon IAV challenge, we find that cells escaping viral infection display increased mRNA expression of type-I interferon stimulated genes and decreased expression of ribosomal genes, relative to both infected cells and those never exposed to IAV. We also uncover a stronger resistance of CD16⁺ monocytes to IAV infection, together with CD16⁺ -specific mRNA expression of IL6 and TNF in response to IAV. Finally, using flow cytometry and bulk RNA-sequencing across 200 individuals of African and European ancestry, we observe a higher number of CD16 ⁺ monocytes and lower susceptibility to IAV infection among monocytes from individuals of African-descent. Based on these data, we hypothesize that higher basal monocyte activation, driven by environmental factors and/or weak-effect genetic variants, underlies the lower cellular susceptibility to IAV infection of individuals of African ancestry relative to those of European ancestry. Further studies are now required to investigate how such cellular differences in IAV susceptibility translate into population differences in clinical outcomes and susceptibility to severe influenza.

Library-based analysis reveals segment and length dependent characteristics of defective influenza genomes

Found in a diverse set of viral populations, defective interfering particles are parasitic variants that are unable to replicate on their own yet rise to relatively high frequencies. Their presence is associated with a loss of population fitness, both through the depletion of key cellular resources and the stimulation of innate immunity. For influenza A virus, these particles contain large internal deletions in the genomic segments which encode components of the heterotrimeric polymerase. Using a library-based approach, we comprehensively profile the growth and replication of defective influenza species, demonstrating that they possess an advantage during genome replication, and that exclusion during population expansion reshapes population composition in a manner consistent with their final, observed, distribution in natural populations. We find that an innate immune response is not linked to the size of a deletion; however, replication of defective segments can enhance their immunostimulatory properties. Overall, our results address several key questions in defective influenza A virus biology, and the methods we have developed to answer those questions may be broadly applied to other defective viruses.

The evolution of cheating in viruses

The success of many viruses depends upon cooperative interactions between viral genomes. However, whenever cooperation occurs, there is the potential for 'cheats' to exploit that cooperation. We suggest that: (1) the biology of viruses makes viral cooperation particularly susceptible to cheating; (2) cheats are common across a wide range of viruses, including viral entities that are already well studied, such as defective interfering genomes, and satellite viruses. Consequently, the evolutionary theory of cheating could help us understand and manipulate viral dynamics, while viruses also offer new opportunities to study the evolution of cheating.

Single-Cell Genomics: Enabling the Functional Elucidation of Infectious Diseases in Multi-Cell Genomes

Since the time when detection of gene expression in single cells by microarrays to the Next Generation Sequencing (NGS) enabled Single Cell Genomics (SCG), it has played a pivotal role to understand and elucidate the functional role of cellular heterogeneity. Along this journey to becoming a key player in the capture of the individuality of cells, SCG overcame many milestones, including scale, speed, sensitivity and sample costs (4S). There have been many important experimental and computational innovations in the efficient analysis and interpretation of SCG data. The increasing role of AI in SCG data analysis has further enhanced its applicability in building models for clinical intervention. Furthermore, SCG has been instrumental in the delineation of the role of cellular heterogeneity in specific diseases, including cancer and infectious diseases. The understanding of the role of differential immune responses in driving coronavirus disease-2019 (COVID-19) disease severity and clinical outcomes has been greatly aided by SCG. With many variants of concern (VOC) in sight, it would be of great importance to further understand the immune response specificity vis-a-vis the immune cell repertoire, the identification of novel cell types, and antibody response. Given the potential of SCG to play an integral part in the multi-omics approach to the study of the host-pathogen interaction and its outcomes, our review attempts to highlight its strengths, its implications for infectious disease biology, and its current limitations. We conclude that the application of SCG would be a critical step towards future pandemic preparedness.

Presence of defective viral genes in H1N1 live attenuated influenza vaccine strains is not associated with reduced human cell fitness or vaccine effectiveness

In the 2013-2014 and 2015-2016 seasons, quadrivalent live attenuated influenza vaccine (LAIV) showed reduced pandemic 2009 H1N1 (A/H1N1pdm09) vaccine effectiveness (VE) in the U.S. Impaired fitness of A/H1N1pdm09 LAIV strains in primary human nasal epithelial cells (hNEC) was subsequently shown to be associated with reduced VE. As defective viral genes (DVG) have been detected in QLAIV, it was hypothesised that these might play a role in reduced A/H1N1pdm09 fitness. By applying RT-PCR based approaches, DVG for PB2, PB1 and PA segments were detected in all influenza A LAIV strains tested. Absolute quantification of PA vRNA as a biomarker, using a novel digital RT-PCR assay (RT-dPCR), showed that DVG were a minority population (between 10.2 and 27.8 % of PA vRNA) in LAIV, irrespective of subtype or VE. Importantly, no difference was observed between the fitter pre-2009 H1N1 A/New Caledonia/20/1999 (A/NC99) and less fit A/H1N1pdm09 A/Bolivia/509/2013 (A/BOL13), containing medians of 16.0 % and 10.2 % PA DVG, respectively. Manipulating propagation conditions and minimising A/BOL13 PA DVG to 5.2 % failed to improve viral replication in hNEC, suggesting DVG were not limiting A/BOL13 fitness. Conversely, DVG were able to reduce A/NC99 replication in hNEC to A/BOL13-like levels, but only by enrichment of PA DVG to 66.5 % of vRNA. Notably, this required LAIV propagation under conditions markedly different to those used for vaccine production. We conclude from these data that abundance of DVG in QLAIV is not associated with variations in influenza A VE and that the reduced fitness of A/BOL13 previously described was not driven by the presence of DVG.

Constitutive TRIM22 Expression in the Respiratory Tract Confers a Pre-Existing Defence Against Influenza A Virus Infection

The induction of antiviral effector proteins as part of a homeostatically controlled innate immune response to infection plays a critical role in limiting the propagation and transmission of respiratory pathogens. However, the prolonged induction of this immune response can lead to lung hyperinflammation, tissue damage, and respiratory failure. We hypothesized that tissues exposed to the constant threat of infection may constitutively express higher levels of antiviral effector proteins to reduce the need to activate potentially harmful innate immune defences. By analysing transcriptomic data derived from a range of human tissues, we identify lung tissue to express constitutively higher levels of antiviral effector genes relative to that of other mucosal and non-mucosal tissues. By using primary cell lines and the airways of rhesus macaques, we show the interferon-stimulated antiviral effector protein TRIM22 (TRIpartite Motif 22) to be constitutively expressed in the lung independently of viral infection or innate immune stimulation. These findings contrast with previous reports that have shown TRIM22 expression in laboratory-adapted cell lines to require interferon stimulation. We demonstrate that constitutive levels of TRIM22 are sufficient to inhibit the onset of human and avian influenza A virus (IAV) infection by restricting the onset of viral transcription independently of interferon-mediated innate immune defences. Thus, we identify TRIM22 to confer a pre-existing (intrinsic) intracellular defence against IAV infection in cells derived from the respiratory tract. Our data highlight the importance of tissue-specific and cell-type dependent patterns of pre-existing immune gene expression in the intracellular restriction of IAV from the outset of infection.

Single cell sequencing technology and its application in Hypoxic ischemic encephalopathy research

Hypoxic ischemic encephalopathy (HIE) is the common etiology of neonatal morbidity and mortality, which exerts a negative seriously influence for the growth and development of children, and even threatens their life. Therapeutic methods are timely not adopted, it will cause serious irreversible damage to the neonatal nervous system. As no promising therapeutic strategies exist currently, it is important to elucidate the pathological mechanism for HIE, which requires us to explore the nucleic acid molecules, protein, and cell function in HIE patients, and to understand the process of the onset and progression, then research and invent better treatment methods and therapeutic drugs. Single cell sequencing (SCS) exhibits an distinctive advantages in cells research because of the particularity of each cell. This method solves an puzzle about heterogeneit, which could not be solved with multi cell sample research, and provides a new idea and perspective for the un-elucidated and events further analyzed, such as the behaviors, mechanisms and the relationship between single cell and organism in cell population. It also plays an extremely significant role in the basic research and precision medicine. Some studies have suggested that SCS serves a vital function in the study of HIE. Therefore, this review is aim to elaborate SCS and hypoxic-ischemic brain injury, and trace the role of microglia in HIE, and prospect its unknown and undiscovered mechanism by SCS.

Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology

Short-read, high-throughput sequencing (HTS) methods have yielded numerous important insights into microbial ecology and function. Yet, in many instances short-read HTS techniques are suboptimal, for example, by providing insufficient phylogenetic resolution or low integrity of assembled genomes. Single-molecule and synthetic long-read (SLR) HTS methods have successfully ameliorated these limitations. In addition, nanopore sequencing has generated a number of unique analysis opportunities, such as rapid molecular diagnostics and direct RNA sequencing, and both Pacific Biosciences (PacBio) and nanopore sequencing support detection of epigenetic modifications. Although initially suffering from relatively low sequence quality, recent advances have greatly improved the accuracy of long-read sequencing technologies. In spite of great technological progress in recent years, the long-read HTS methods (PacBio and nanopore sequencing) are still relatively costly, require large amounts of high-quality starting material, and commonly need specific solutions in various analysis steps. Despite these challenges, long-read sequencing technologies offer high-quality, cutting-edge alternatives for testing hypotheses about microbiome structure and functioning as well as assembly of eukaryote genomes from complex environmental DNA samples.

Virus Infection Variability by Single-Cell Profiling

Cell-to-cell variability of infection has long been known, yet it has remained one of the least understood phenomena in infection research. It impacts on disease onset and development, yet only recently underlying mechanisms have been studied in clonal cell cultures by single-virion immunofluorescence microscopy and flow cytometry. In this review, we showcase how single-cell RNA sequencing (scRNA-seq), single-molecule RNA-fluorescence in situ hybridization (FISH), and copper(I)-catalyzed azide-alkyne cycloaddition (click) with alkynyl-tagged viral genomes dissect infection variability in human and mouse cells. We show how the combined use of scRNA-FISH and click-chemistry reveals highly variable onsets of adenoviral gene expression, and how single live cell plaques reveal lytic and nonlytic adenovirus transmissions. The review highlights how scRNA-seq profiling and scRNA-FISH of coxsackie, influenza, dengue, zika, and herpes simplex virus infections uncover transcriptional variability, and how the host interferon response tunes influenza and sendai virus infections. We introduce the concept of "cell state" in infection variability, and conclude with advances by single-cell simultaneous measurements of chromatin accessibility and mRNA counts at high-throughput. Such technology will further dissect the sequence of events in virus infection and pathology, and better characterize the genetic and genomic stability of viruses, cell autonomous innate immune responses, and mechanisms of tissue injury.

Single-cell RNA-seq landscape midbrain cell responses to red spotted grouper nervous necrosis virus infection

Viral nervous necrosis (VNN) is an acute and serious fish disease caused by nervous necrosis virus (NNV) which has been reported massive mortality in more than fifty teleost species worldwide. VNN causes damage of necrosis and vacuolation to central nervous system (CNS) cells in fish. It is difficult to identify the specific type of cell targeted by NNV, and to decipher the host immune response because of the functional diversity and highly complex anatomical and cellular composition of the CNS. In this study, we found that the red spotted grouper NNV (RGNNV) mainly attacked the midbrain of orange-spotted grouper (Epinephelus coioides). We conducted single-cell RNA-seq analysis of the midbrain of healthy and RGNNV-infected fish and identified 35 transcriptionally distinct cell subtypes, including 28 neuronal and 7 non-neuronal cell types. An evaluation of the subpopulations of immune cells revealed that macrophages were enriched in RGNNV-infected fish, and the transcriptional profiles of macrophages indicated an acute cytokine and inflammatory response. Unsupervised pseudotime analysis of immune cells showed that microglia transformed into M1-type activated macrophages to produce cytokines to reduce the damage to nerve tissue caused by the virus. We also found that RGNNV targeted neuronal cell types was GLU1 and GLU3, and we found that the key genes and pathways by which causes cell cytoplasmic vacuoles and autophagy significant enrichment, this may be the major route viruses cause cell death. These data provided a comprehensive transcriptional perspective of the grouper midbrain and the basis for further research on how viruses infect the teleost CNS.

Modeling poliovirus replication dynamics from live time-lapse single-cell imaging data

Viruses experience selective pressure on the timing and order of events during infection to maximize the number of viable offspring they produce. Additionally, they may experience variability in cellular environments encountered, as individual eukaryotic cells can display variation in gene expression among cells. This leads to a dynamic phenotypic landscape that viruses must face to replicate. To examine replication dynamics displayed by viruses faced with this variable landscape, we have developed a method for fitting a stochastic mechanistic model of viral infection to time-lapse imaging data from high-throughput single-cell poliovirus infection experiments. The model's mechanistic parameters provide estimates of several aspects associated with the virus's intracellular dynamics. We examine distributions of parameter estimates and assess their variability to gain insight into the root causes of variability in viral growth dynamics. We also fit our model to experiments performed under various drug treatments and examine which parameters differ under these conditions. We find that parameters associated with translation and early stage viral replication processes are essential for the model to capture experimentally observed dynamics. In aggregate, our results suggest that differences in viral growth data generated under different treatments can largely be captured by steps that occur early in the replication process.

Influenza Virus RNA Synthesis and the Innate Immune Response

Infection with influenza A and B viruses results in a mild to severe respiratory tract infection. It is widely accepted that many factors affect the severity of influenza disease, including viral replication, host adaptation, innate immune signalling, pre-existing immunity, and secondary infections. In this review, we will focus on the interplay between influenza virus RNA synthesis and the detection of influenza virus RNA by our innate immune system. Specifically, we will discuss the generation of various RNA species, host pathogen receptors, and host shut-off. In addition, we will also address outstanding questions that currently limit our knowledge of influenza virus replication and host adaption. Understanding the molecular mechanisms underlying these factors is essential for assessing the pandemic potential of future influenza virus outbreaks.

The transcriptional landscape of Venezuelan equine encephalitis virus (TC-83) infection

Venezuelan Equine Encephalitis Virus (VEEV) is a major biothreat agent that naturally causes outbreaks in humans and horses particularly in tropical areas of the western hemisphere, for which no antiviral therapy is currently available. The host response to VEEV and the cellular factors this alphavirus hijacks to support its effective replication or evade cellular immune responses are largely uncharacterized. We have previously demonstrated tremendous cell-to-cell heterogeneity in viral RNA (vRNA) and cellular transcript levels during flaviviral infection using a novel virus-inclusive single-cell RNA-Seq approach. Here, we used this unbiased, genome-wide approach to simultaneously profile the host transcriptome and vRNA in thousands of single cells during infection of human astrocytes with the live-attenuated vaccine strain of VEEV (TC-83). Host transcription was profoundly suppressed, yet “superproducer cells” with extremely high vRNA abundance emerged during the first viral life cycle and demonstrated an altered transcriptome relative to both uninfected cells and cells with high vRNA abundance harvested at later time points. Additionally, cells with increased structural-to-nonstructural transcript ratio exhibited upregulation of intracellular membrane trafficking genes at later time points. Loss- and gain-of-function experiments confirmed pro- and antiviral activities in both vaccine and virulent VEEV infections among the products of transcripts that positively or negatively correlated with vRNA abundance, respectively. Lastly, comparison with single cell transcriptomic data from other viruses highlighted common and unique pathways perturbed by infection across evolutionary scales. This study provides a high-resolution characterization of the VEEV (TC-83)-host interplay, identifies candidate targets for antivirals, and establishes a comparative single-cell approach to study the evolution of virus-host interactions.

Little is known about the host response to Venezuelan Equine Encephalitis Virus (VEEV) and the cellular factors this alphavirus hijacks to support effective replication or evade cellular immune responses. Monitoring dynamics of host and viral RNA (vRNA) during viral infection at a single-cell level can provide insight into the virus-host interplay at a high resolution. Here, a single-cell RNA sequencing technology that detects host and viral RNA was used to investigate the interactions between TC-83, the vaccine strain of VEEV, and the human host during the course of infection of U-87 MG cells (human astrocytoma). Virus abundance and host transcriptome were heterogeneous across cells from the same culture. Subsets of differentially expressed genes, positively or negatively correlating with vRNA abundance, were identified and subsequently in vitro validated as candidate proviral and antiviral factors, respectively, in TC-83 and/or virulent VEEV infections. In the first replication cycle, “superproducer” cells exhibited rapid increase in vRNA abundance and unique gene expression patterns. At later time points, cells with increased structural-to-nonstructural transcript ratio demonstrated upregulation of intracellular membrane trafficking genes. Lastly, comparing the VEEV dataset with published datasets on other RNA viruses revealed unique and overlapping responses across viral clades. Overall, this study improves the understanding of VEEV-host interactions, reveals candidate targets for antiviral approaches, and establishes a comparative single-cell approach to study the evolution of virus-host interactions.

Norovirus evolution in immunodeficient mice reveals potentiated pathogenicity via a single nucleotide change in the viral capsid

Interferons (IFNs) are key controllers of viral replication, with intact IFN responses suppressing virus growth and spread. Using the murine norovirus (MNoV) system, we show that IFNs exert selective pressure to limit the pathogenic evolutionary potential of this enteric virus. In animals lacking type I IFN signaling, the nonlethal MNoV strain CR6 rapidly acquired enhanced virulence via conversion of a single nucleotide. This nucleotide change resulted in amino acid substitution F514I in the viral capsid, which led to >10,000-fold higher replication in systemic organs including the brain. Pathogenicity was mediated by enhanced recruitment and infection of intestinal myeloid cells and increased extraintestinal dissemination of virus. Interestingly, the trade-off for this mutation was reduced fitness in an IFN-competent host, in which CR6 bearing F514I exhibited decreased intestinal replication and shedding. In an immunodeficient context, a spontaneous amino acid change can thus convert a relatively avirulent viral strain into a lethal pathogen.