Extreme heterogeneity of influenza virus infection in single cells

Conformational Dynamics of Influenza A Virus Ribonucleoprotein Complexes during RNA Synthesis

Viral ribonucleoproteins (vRNPs) are the cornerstones of viral proliferation, as they form the macromolecular complexes that are responsible for the transcription and replication of most single-stranded RNA viruses. The influenza A virus (IAV) polymerase catalyzes RNA synthesis within the context of vRNPs where genomic viral RNA (vRNA) is packaged by the viral nucleoprotein (NP). We used high-speed atomic force microscopy and electron microscopy to study the conformational dynamics of individual IAV recombinant RNPs (rRNPs) during RNA synthesis. The rRNPs present an annular organization that allows for the real-time tracking of conformational changes in the NP-vRNA template caused by the advancing polymerase. We demonstrate that the rRNPs undergo a well-defined conformational cycle during RNA synthesis, which can be interpreted in light of previous transcription models. We also present initial estimations of the average RNA synthesis rate in the rRNP and its dependence on the nucleotide concentration and stability of the nascent RNA secondary structures. Furthermore, we provide evidence that rRNPs can perform consecutive cycles of RNA synthesis, accounting for their ability to recycle and generate multiple copies of RNA.

Influenza A defective viral genome production is altered by metabolites, metabolic signaling molecules, and cyanobacteria extracts

RNA virus infections are composed of a diverse mix of viral genomes that arise from low fidelity in replication within cells. The interactions between "defective" and full-length viral genomes have been shown to shape pathogenesis, leading to intense research into employing these to develop novel antivirals. In particular, Influenza A defective viral genomes (DVGs) have been associated with milder clinical outcomes. Yet, the full potential of DVGs as broad-spectrum antivirals remains untapped due to the unknown mechanisms of their de novo production. Much of the research into the factors affecting defective viral genome production has focused on the virus, while the role of the host has been neglected. We recently showed that altering host cell metabolism away from pro-growth pathways using alpelisib increased the production of Influenza A defective viral genomes. To uncover other drugs that could induce infections to create more DVGs, we subjected active influenza infections of the two circulating human subtypes (A/H1N1 & A/H3N2) to a screen of metabolites, metabolic signaling molecules, and cyanobacteria-derived biologics, after which we quantified the defective viral genomes (specifically deletion-containing viral genomes, DelVGs) and total viral genomes using third generation long-read sequencing. Here we show that metabolites and signaling molecules of host cell central carbon metabolism can significantly alter DelVG production early in Influenza A infection. Adenosine, emerged as a potent inducer of defective viral genomes, significantly amplifying DelVG production across both subtypes. Insulin had similar effects, albeit subtype-specific, predominantly enhancing polymerase segment DVGs in TX12 infections. Tricarboxylic Acid (TCA) cycle inhibitors 4-octyl itaconate and UK5099, along with the purine analog favipiravir, increased total viral genome production across subtypes. Cyanobacterial extracts primarily affected DVG and total viral genome production in TX12, with a specific, almost complete shutdown of influenza antigenic segments. These results underscore the influence of host metabolic pathways on DVG production and suggest new avenues for antiviral intervention, including PI3K-AKT and Ras-MAPK signaling pathways, TCA cycle metabolism, purine-pyrimidine metabolism, polymerase inhibition, and cyanotherapeutic approaches. More broadly, our findings suggest that the social interactions observed between defective and full-length viral genomes, depend not only on the viral actors, but can be altered by the stage provided by the host. Our study advances our fundamental understanding of DVG production mechanisms and highlights the potential of targeting host metabolism to develop broad-spectrum influenza therapeutics.

Influenza A defective viral genomes and non-infectious particles are increased by host PI3K inhibition via anti-cancer drug alpelisib

RNA viruses produce abundant defective viral genomes during replication, setting the stage for interactions between viral genomes that alter the course of pathogenesis. Harnessing these interactions to develop antivirals has become a recent goal of intense research focus. Despite decades of research, the mechanisms that regulate the production and interactions of Influenza A defective viral genomes are still unclear. The role of the host is essentially unexplored; specifically, it remains unknown whether host metabolism can influence the formation of defective viral genomes and the particles that house them. To address this question, we manipulated host cell anabolic signaling activity and monitored the production of defective viral genomes and particles by A/H1N1 and A/H3N2 strains, using a combination of single-cell immunofluorescence quantification, third-generation long-read sequencing, and the cluster-forming assay, a method we developed to titer defective and fully-infectious particles simultaneously. Here we show that alpelisib (Piqray), a highly selective inhibitor of mammalian Class 1a phosphoinositide-3 kinase (PI3K) receptors, significantly changed the proportion of defective particles and viral genomes (specifically deletion-containing viral genomes) in a strain-specific manner, under conditions that minimize multiple cycles of replication. Alpelisib pre-treatment of cells led to an increase in defective particles in the A/H3N2 strain, while the A/H1N1 strain showed a decrease in total viral particles. In the same infections, we found that defective viral genomes of polymerase and antigenic segments increased in the A/H1N1 strain, while the total particles decreased suggesting defective interference. We also found that the average deletion size in polymerase complex viral genomes increased in both the A/H3N2 and A/H1N1 strains. The A/H1N1 strain, additionally showed a dose-dependent increase in total number of defective viral genomes. In sum, we provide evidence that host cell metabolism can increase the production of defective viral genomes and particles at an early stage of infection, shifting the makeup of the infection and potential interactions among virions. Given that Influenza A defective viral genomes can inhibit pathogenesis, our study presents a new line of investigation into metabolic states associated with less severe flu infection and the potential induction of these states with metabolic drugs.

Influenza A viral burst size from thousands of infected single cells using droplet quantitative PCR (dqPCR)

An important aspect of how viruses spread and infect is the viral burst size, or the number of new viruses produced by each infected cell. Surprisingly, this value remains poorly characterized for influenza A virus (IAV), commonly known as the flu. In this study, we screened tens of thousands of cells using a microfluidic method called droplet quantitative PCR (dqPCR). The high-throughput capability of dqPCR enabled the measurement of a large population of infected cells producing progeny virus. By measuring the fully assembled and successfully released viruses from these infected cells, we discover that the viral burst sizes for both the seasonal H3N2 and the 2009 pandemic H1N1 strains vary significantly, with H3N2 ranging from 101 to 104 viruses per cell, and H1N1 ranging from 101 to 103 viruses per cell. Some infected cells produce average numbers of new viruses, while others generate extensive number of viruses. In fact, we find that only 10% of the single-cell infections are responsible for creating a significant portion of all the viruses. This small fraction produced approximately 60% of new viruses for H3N2 and 40% for H1N1. On average, each infected cell of the H3N2 flu strain produced 709 new viruses, whereas for H1N1, each infected cell produced 358 viruses. This novel method reveals insights into the flu virus and can lead to improved strategies for managing and preventing the spread of viruses.

Single-cell transcriptomic reveals a cell atlas and diversity of chicken amygdala responded to social hierarchy

Amygdala serves as a highly cellular, heterogeneous brain region containing excitatory and inhibitory neurons and is involved in the dopamine and serotoninergic neuron systems. An increasing number of studies have revealed the underpinned mechanism mediating social hierarchy in mammal and vertebrate, however, there are rare studies conducted on how amygdala on social hierarchy in poultry. In this study, we conducted food competition tests and determined the social hierarchy of the rooster. We performed cross-species analysis with mammalian amygdala, and found that cell types of human and rhesus monkeys were more closely related and that of chickens were more distant. We identified 26 clusters and divided them into 10 main clusters, of which GABAergic and glutamatergic neurons were associated with social behaviors. In conclusion, our results provide to serve the developmental studies of the amygdala neuron system and new insights into the underpinned mechanism of social hierarchy in roosters.

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.

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.

Epstein-Barr virus reactivation induces divergent abortive, reprogrammed, and host shutoff states by lytic progression

Viral infection leads to heterogeneous cellular outcomes ranging from refractory to abortive and fully productive states. Single cell transcriptomics enables a high resolution view of these distinct post-infection states. Here, we have interrogated the host-pathogen dynamics following reactivation of Epstein-Barr virus (EBV). While benign in most people, EBV is responsible for infectious mononucleosis, up to 2% of human cancers, and is a trigger for the development of multiple sclerosis. Following latency establishment in B cells, EBV reactivates and is shed in saliva to enable infection of new hosts. Beyond its importance for transmission, the lytic cycle is also implicated in EBV-associated oncogenesis. Conversely, induction of lytic reactivation in latent EBV-positive tumors presents a novel therapeutic opportunity. Therefore, defining the dynamics and heterogeneity of EBV lytic reactivation is a high priority to better understand pathogenesis and therapeutic potential. In this study, we applied single-cell techniques to analyze diverse fate trajectories during lytic reactivation in two B cell models. Consistent with prior work, we find that cell cycle and MYC expression correlate with cells refractory to lytic reactivation. We further found that lytic induction yields a continuum from abortive to complete reactivation. Abortive lytic cells upregulate NFκB and IRF3 pathway target genes, while cells that proceed through the full lytic cycle exhibit unexpected expression of genes associated with cellular reprogramming. Distinct subpopulations of lytic cells further displayed variable profiles for transcripts known to escape virus-mediated host shutoff. These data reveal previously unknown and promiscuous outcomes of lytic reactivation with broad implications for viral replication and EBV-associated oncogenesis.

Deciphering bat influenza H18N11 infection dynamics in male Jamaican fruit bats on a single-cell level

Jamaican fruit bats (Artibeus jamaicensis) naturally harbor a wide range of viruses of human relevance. These infections are typically mild in bats, suggesting unique features of their immune system. To better understand the immune response to viral infections in bats, we infected male Jamaican fruit bats with the bat-derived influenza A virus (IAV) H18N11. Using comparative single-cell RNA sequencing, we generated single-cell atlases of the Jamaican fruit bat intestine and mesentery. Gene expression profiling showed that H18N11 infection resulted in a moderate induction of interferon-stimulated genes and transcriptional activation of immune cells. H18N11 infection was predominant in various leukocytes, including macrophages, B cells, and NK/T cells. Confirming these findings, human leukocytes, particularly macrophages, were also susceptible to H18N11, highlighting the zoonotic potential of this bat-derived IAV. Our study provides insight into a natural virus-host relationship and thus serves as a fundamental resource for future in-depth characterization of bat immunology.

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.

Single-cell RNA-seq revealed heterogeneous responses and functional differentiation of hemocytes against white spot syndrome virus infection in Litopenaeus vannamei

Shrimp hemocytes are the vital immune cells participating in innate immune response to defend against viruses. However, the lack of specific molecular markers for shrimp hemocyte hindered the insightful understanding of their functional clusters and differential roles in combating microbial infections. In this study, we used single-cell RNA sequencing to map the transcriptomic landscape of hemocytes from the white spot syndrome virus (WSSV)-infected Litopenaeus vannamei and conjointly analyzed with our previous published single-cell RNA sequencing technology data from the healthy hemocytes. A total of 16 transcriptionally distinct cell clusters were identified, which occupied different proportions in healthy and WSSV-infected hemocytes and exerted differential roles in antiviral immune response. Following mapping of the sequencing data to the WSSV genome, we found that all types of hemocytes could be invaded by WSSV virions, especially the cluster 8, which showed the highest transcriptional levels of WSSV genes and exhibited a cell type-specific antiviral response to the viral infection. Further evaluation of the cell clusters revealed the delicate dynamic balance between hemocyte immune response and viral infestation. Unsupervised pseudo-time analysis of hemocytes showed that the hemocytes in immune-resting state could be significantly activated upon WSSV infection and then functionally differentiated to different hemocyte subsets. Collectively, our results revealed the differential responses of shrimp hemocytes and the process of immune-functional differentiation post-WSSV infection, providing essential resource for the systematic insight into the synergistic immune response mechanism against viral infection among hemocyte subtypes.

IMPORTANCE

Current knowledge of shrimp hemocyte classification mainly comes from morphology, which hinder in-depth characterization of cell lineage development, functional differentiation, and different immune response of hemocyte types during pathogenic infections. Here, single-cell RNA sequencing was used for mapping hemocytes during white spot syndrome virus (WSSV) infection in Litopenaeus vannamei, identifying 16 cell clusters and evaluating their potential antiviral functional characteristics. We have described the dynamic balance between viral infestation and hemocyte immunity. And the functional differentiation of hemocytes under WSSV stimulation was further characterized. Our results provided a comprehensive transcriptional landscape and revealed the heterogeneous immune response in shrimp hemocytes during WSSV infection.

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 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.

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.

Dissecting viral infections, one cell at a time, by single-cell technologies

The meteoric rise of single-cell genomic technologies, especially of single-cell RNA-sequencing (scRNA-seq), has revolutionized several fields of cellular biology, especially immunology, oncology, neuroscience and developmental biology. While the field of virology has been relatively slow to adopt these technological advances, many works have shed new light on the fascinating interactions of viruses with their hosts using single cell technologies. One clear example is the multitude of studies dissecting viral infections by single-cell sequencing technologies during the recent COVID-19 pandemic. In this review we will detail the advantages of studying viral infections at a single-cell level, how scRNA-seq technologies can be used to achieve this goal and the associated technical limitations, challenges and solutions. We will highlight recent biological discoveries and breakthroughs in virology enabled by single-cell analyses and will end by discussing possible future directions of the field. Given the rate of publications in this exciting new frontier of virology, we have likely missed some important works and we apologize in advance to the researchers whose work we have failed to cite.

Known phyla dominate the Tara Oceans RNA virome

A recent study proposed five new RNA virus phyla, two of which, 'Taraviricota' and 'Arctiviricota', were stated to be 'dominant in the oceans'. However, the study's assignments classify 28,353 putative RdRp-containing contigs to known phyla but only 886 (2.8%) to the five proposed new phyla combined. I re-mapped the reads to the contigs, finding that known phyla also account for a large majority (93.8%) of reads according to the study's classifications, and that contigs originally assigned to 'Arctiviricota' accounted for only a tiny fraction (0.01%) of reads from Arctic Ocean samples. Performing my own virus identification and classifications, I found that 99.95 per cent of reads could be assigned to known phyla. The most abundant species was Beihai picorna-like virus 34 (15% of reads), and the most abundant order-like cluster was classified as Picornavirales (45% of reads). Sequences in the claimed new phylum 'Pomiviricota' were placed inside a phylogenetic tree for established order Durnavirales with 100 per cent confidence. Moreover, two contigs assigned to the proposed phylum 'Taraviricota' were found to have high-identity alignments to dinoflagellate proteins, tentatively identifying this group of RdRp-like sequences as deriving from non-viral transcripts. Together, these results comprehensively contradict the claim that new phyla dominate the data.

Antiviral responses are shaped by heterogeneity in viral replication dynamics

Antiviral signalling, which can be activated in host cells upon virus infection, restricts virus replication and communicates infection status to neighbouring cells. The antiviral response is heterogeneous, both quantitatively (efficiency of response activation) and qualitatively (transcribed antiviral gene set). To investigate the basis of this heterogeneity, we combined Virus Infection Real-time IMaging (VIRIM), a live-cell single-molecule imaging method, with real-time readouts of the dsRNA sensing pathway to analyse the response of human cells to encephalomyocarditis virus (EMCV) infection. We find that cell-to-cell heterogeneity in viral replication rates early in infection affect the efficiency of antiviral response activation, with lower replication rates leading to more antiviral response activation. Furthermore, we show that qualitatively distinct antiviral responses can be linked to the strength of the antiviral signalling pathway. Our analyses identify variation in early viral replication rates as an important parameter contributing to heterogeneity in antiviral response activation.

mSphere of Influence: Virology in the noise-how cell-to-cell variability impacts viral infection outcomes

Nir Drayman works at the intersection of virology and single-cell biology, studying how cellular heterogeneity shapes the outcome of viral infections (and specifically that of HSV-1). In this mSphere of Influence article, he reflects on how two papers, "Remote activation of host cell DNA synthesis in uninfected cells signaled by infected cells in advance of virus transmission" (N. Schmidt, T. Hennig, R. A. Serwa, M. Marchetti, and P. O'Hare, J Virol 89:11107-11115, 2015, https://doi.org/10.1128/jvi.01950-15) and "Extreme heterogeneity of influenza virus infection in single cells" (A. B. Russell, C. Trapnell, and J. D. Bloom, Elife 7:e32303, 2018, https://doi.org/10.7554/eLife.32303), impacted his research by trail blazing the analysis of viral infections in single cells, as well as by illuminating what is yet left to discover.

Modulation of Influenza A virus NS1 expression reveals prioritization of host response antagonism at single-cell resolution

Influenza A virus (IAV) is an important human respiratory pathogen that causes significant seasonal epidemics and potential devastating pandemics. As part of its life cycle, IAV encodes the multifunctional protein NS1, that, among many roles, prevents immune detection and limits interferon (IFN) production. As distinct host immune pathways exert different selective pressures against IAV, as replication progresses, we expect a prioritization in the host immune antagonism by NS1. In this work, we profiled bulk transcriptomic differences in a primary bronchial epithelial cell model facing IAV infections at distinct NS1 levels. We further demonstrated that, at single cell level, the intracellular amount of NS1 in-part shapes the heterogeneity of the host response. We found that modulation of NS1 levels reveal a ranking in its inhibitory roles: modest NS1 expression is sufficient to inhibit immune detection, and thus the expression of pro-inflammatory cytokines (including IFNs), but higher levels are required to inhibit IFN signaling and ISG expression. Lastly, inhibition of chaperones related to the unfolded protein response requires the highest amount of NS1, often associated with later stages of viral replication. This work demystifies some of the multiple functions ascribed to IAV NS1, highlighting the prioritization of NS1 in antagonizing the different pathways involved in the host response to IAV infection.

Dissection of key factors correlating with H5N1 avian influenza virus driven inflammatory lung injury of chicken identified by single-cell analysis

Chicken lung is an important target organ of avian influenza virus (AIV) infection, and different pathogenic virus strains lead to opposite prognosis. Using a single-cell RNA sequencing (scRNA-seq) assay, we systematically and sequentially analyzed the transcriptome of 16 cell types (19 clusters) in the lung tissue of chickens infected with H5N1 highly pathogenic avian influenza virus (HPAIV) and H9N2 low pathogenic avian influenza virus (LPAIV), respectively. Notably, we developed a valuable catalog of marker genes for these cell types. Compared to H9N2 AIV infection, H5N1 AIV infection induced extensive virus replication and the immune reaction across most cell types simultaneously. More importantly, we propose that infiltrating inflammatory macrophages (clusters 0, 1, and 14) with massive viral replication, pro-inflammatory cytokines (IFN-β, IL1β, IL6 and IL8), and emerging interaction of various cell populations through CCL4, CCL19 and CXCL13, potentially contributed to the H5N1 AIV driven inflammatory lung injury. Our data revealed complex but distinct immune response landscapes in the lung tissue of chickens after H5N1 and H9N2 AIV infection, and deciphered the potential mechanisms underlying AIV-driven inflammatory reactions in chicken. Furthermore, this article provides a rich database for the molecular basis of different cell-type responses to AIV infection.

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.

Impact of dual-baculovirus infection on the Sf9 insect cell transcriptome during rAAV production using single-cell RNA-seq

The insect cell-baculovirus expression vector system (IC-BEVS) has shown to be a powerful platform to produce complex biopharmaceutical products, such as recombinant proteins and virus-like particles. More recently, IC-BEVS has also been used as an alternative to produce recombinant adeno-associated virus (rAAV). However, little is known about the variability of insect cell populations and the potential effect of heterogeneity (e.g., stochastic infection process and differences in infection kinetics) on product titer and/or quality. In this study, transcriptomics analysis of Sf9 insect cells during the production of rAAV of serotype 2 (rAAV2) using a low multiplicity of infection, dual-baculovirus system was performed via single-cell RNA-sequencing (scRNA-seq). Before infection, the principal source of variability in Sf9 insect cells was associated with the cell cycle. Over the course of infection, an increase in transcriptional heterogeneity was detected, which was linked to the expression of baculovirus genes as well as to differences in rAAV transgenes (rep, cap and gfp) expression. Noteworthy, at 24 h post-infection, only 29.4% of cells enclosed all three necessary rAAV transgenes to produce packed rAAV2 particles, indicating limitations of the dual-baculovirus system. In addition, the trajectory analysis herein performed highlighted that biological processes such as protein folding, metabolic processes, translation, and stress response have been significantly altered upon infection. Overall, this work reports the first application of scRNA-seq to the IC-BEVS and highlights significant variations in individual cells within the population, providing insight into the rational cell and process engineering toward improved rAAV2 production in IC-BEVS.

Comparison of antiviral responses in two bat species reveals conserved and divergent innate immune pathways

Bats host a range of disease-causing viruses without displaying clinical symptoms. The mechanisms behind this are a continuous source of interest. Here, we studied the antiviral response in the Egyptian fruit bat and Kuhl's pipistrelle, representing two subordinal clades. We profiled the antiviral response in fibroblasts using RNA sequencing and compared bat with primate and rodent responses. Both bats upregulate similar genes; however, a subset of these genes is transcriptionally divergent between them. These divergent genes also evolve rapidly in sequence, have specific promoter architectures, and are associated with programs underlying tolerance and resistance. Finally, we characterized antiviral genes that expanded in bats, with duplicates diverging in sequence and expression. Our study reveals a largely conserved antiviral program across bats and points to a set of genes that rapidly evolve through multiple mechanisms. These can contribute to bat adaptation to viral infection and provide directions to understanding the mechanisms behind it.

Single cell susceptibility to SARS-CoV-2 infection is driven by variable cell states

The ability of a virus to infect a cell type is at least in part determined by the presence of host factors required for the viral life cycle. However, even within cell types that express known factors needed for infection, not every cell is equally susceptible, suggesting that our knowledge of the full spectrum of factors that promote infection is incomplete. Profiling the most susceptible subsets of cells within a population may reveal additional factors that promote infection. However, because viral infection dramatically alters the state of the cell, new approaches are needed to reveal the state of these cells prior to infection with virus. Here, we used single-cell clone tracing to retrospectively identify and characterize lung epithelial cells that are highly susceptible to infection with SARS-CoV-2. The transcriptional state of these highly susceptible cells includes markers of retinoic acid signaling and epithelial differentiation. Loss of candidate factors identified by our approach revealed that many of these factors play roles in viral entry. Moreover, a subset of these factors exert control over the infectable cell state itself, regulating the expression of key factors associated with viral infection and entry. Analysis of patient samples revealed the heterogeneous expression of these factors across both cells and patients in vivo. Further, the expression of these factors is upregulated in particular inflammatory pathologies. Altogether, our results show that the variable expression of intrinsic cell states is a major determinant of whether a cell can be infected by SARS-CoV-2.

Airborne fine particles drive H1N1 viruses deep into the lower respiratory tract and distant organs

Mounting data suggest that environmental pollution due to airborne fine particles (AFPs) increases the occurrence and severity of respiratory virus infection in humans. However, it is unclear whether and how interactions with AFPs alter viral infection and distribution. We report synergetic effects between various AFPs and the H1N1 virus, regulated by physicochemical properties of the AFPs. Unlike infection caused by virus alone, AFPs facilitated the internalization of virus through a receptor-independent pathway. Moreover, AFPs promoted the budding and dispersal of progeny virions, likely mediated by lipid rafts in the host plasma membrane. Infected animal models demonstrated that AFPs favored penetration of the H1N1 virus into the distal lung, and its translocation into extrapulmonary organs including the liver, spleen, and kidney, thus causing severe local and systemic disorders. Our findings revealed a key role of AFPs in driving viral infection throughout the respiratory tract and beyond. These insights entail stronger air quality management and air pollution reduction policies.

Mapping interindividual dynamics of innate immune response at single-cell resolution

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.

Intracellular bottlenecking permits no more than three tomato yellow leaf curl virus genomes to initiate replication in a single cell

Viruses are constantly subject to natural selection to enrich beneficial mutations and weed out deleterious ones. However, it remains unresolved as to how the phenotypic gains or losses brought about by these mutations cause the viral genomes carrying the very mutations to become more or less numerous. Previous investigations by us and others suggest that viruses with plus strand (+) RNA genomes may compel such selection by bottlenecking the replicating genome copies in each cell to low single digits. Nevertheless, it is unclear if similarly stringent reproductive bottlenecks also occur in cells invaded by DNA viruses. Here we investigated whether tomato yellow leaf curl virus (TYLCV), a small virus with a single-stranded DNA genome, underwent population bottlenecking in cells of its host plants. We engineered a TYLCV genome to produce two replicons that express green fluorescent protein and mCherry, respectively, in a replication-dependent manner. We found that among the cells entered by both replicons, less than 65% replicated both, whereas at least 35% replicated either of them alone. Further probability computation concluded that replication in an average cell was unlikely to have been initiated with more than three replicon genome copies. Furthermore, sequential inoculations unveiled strong mutual exclusions of these two replicons at the intracellular level. In conclusion, the intracellular population of the small DNA virus TYLCV is actively bottlenecked, and such bottlenecking may be a virus-encoded, evolutionarily conserved trait that assures timely selection of new mutations emerging through error-prone replication.

Antiviral Activity of Cell Membrane-Bound Amphiphilic Polymers

We demonstrate that cholesterol-modified polyethylene glycol has antiviral activity, exerted by anchoring to plasma membranes and sterically inhibiting viruses from entering cells. These polymers distribute sparsely on cell membranes even at binding saturation. However, the polymers have sufficient elastic repulsion energy to repel various kinds of viruses with sizes larger than the mean distances between anchored polymers, including SARS-CoV-2 pseudoparticles. Our strategy can be applied to protect the epithelium from viruses. When these polymers are applied to the epithelium, they localize on the apical surface due to the tight junction barriers, resulting in surface-only coating. Therefore, these polymers can prevent the entry of viruses into cells of the epithelium with minimal disturbance to lateral cell-cell interactions and organizations.

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.

Understanding host response to infectious salmon anaemia virus in an Atlantic salmon cell line using single-cell RNA sequencing

BACKGROUND

Infectious Salmon Anaemia Virus (ISAV) is an Orthomixovirus that represents a large problem for salmonid aquaculture worldwide. Current prevention and treatment methods are only partially effective. Genetic selection and genome engineering have the potential to develop ISAV resistant salmon stocks. Both strategies can benefit from an improved understanding of the genomic regulation of ISAV pathogenesis. Here, we used single-cell RNA sequencing of an Atlantic salmon cell line to provide the first high dimensional insight into the transcriptional landscape that underpins host-virus interaction during early ISAV infection.

RESULTS

Salmon head kidney (SHK-1) cells were single-cell RNA sequenced at 24, 48 and 96 h post-ISAV challenge. At 24 h post infection, cells showed expression signatures consistent with viral entry, with genes such as PI3K, FAK or JNK being upregulated relative to uninfected cells. At 48 and 96 h, infected cells showed a clear anti-viral response, characterised by the expression of IFNA2 or IRF2. Uninfected bystander cells at 48 and 96 h also showed clear transcriptional differences, potentially suggesting paracrine signalling from infected cells. These bystander cells expressed pathways such as mRNA sensing, RNA degradation, ubiquitination or proteasome; and up-regulation of mitochondrial ribosome genes also seemed to play a role in the host response to the infection. Correlation between viral and host genes revealed novel genes potentially key for this fish-virus interaction.

CONCLUSIONS

This study has increased our understanding of the cellular response of Atlantic salmon during ISAV infection and revealed host-virus interactions at the cellular level. Our results highlight various potential key genes in this host-virus interaction, which can be manipulated in future functional studies to increase the resistance of Atlantic salmon to ISAV.

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.

Single-Cell Approach Reveals Intercellular Heterogeneity in Phage-Producing Capacities

Bacteriophage burst size is the average number of phage virions released from infected bacterial cells, and its magnitude depends on the duration of an intracellular progeny accumulation phase. Burst size is often measured at the population level, not the single-cell level, and consequently, statistical moments are not commonly available. In this study, we estimated the bacteriophage lambda (λ) single-cell burst size mean and variance following different intracellular accumulation period durations by employing Escherichia coli lysogens bearing lysis-deficient λ prophages. Single lysogens can be isolated and chemically lysed at desired times following prophage induction to quantify progeny intracellular accumulation within individual cells. Our data showed that λ phage burst size initially increased exponentially with increased lysis time (i.e., period between induction and chemical lysis) and then saturated at longer lysis times. We also demonstrated that cell-to-cell variation, or "noise," in lysis timing did not contribute significantly to burst size noise. The burst size noise remained constant with increasing mean burst size. The most likely explanation for the experimentally observed constant burst size noise was that cell-to-cell differences in burst size originated from intercellular heterogeneity in cellular capacities to produce phages. The mean burst size measured at different lysis times was positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicated that there are other factors in addition to cell size that determine this cellular capacity. IMPORTANCE Phages produce offspring by hijacking a cell's replicative machinery. Previously, it was noted that the variation in the number of phages produced by single infected cells far exceeded cell size variation. It was hypothesized that this variation is a consequence of variation in the timing of host cell lysis. Here, we show that cell-to-cell variation in lysis timing does not significantly contribute to the burst size variation. We suggest that the constant burst size variation across different host lysis times results from cell-to-cell differences in capacity to produce phages. We found that the mean burst size measured at different lysis times was positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicated that there are other factors in addition to cell size that determine this cellular capacity.

High-throughput droplet-based analysis of influenza A virus genetic reassortment by single-virus RNA sequencing

The segmented RNA genome of influenza A viruses (IAVs) enables viral evolution through genetic reassortment after multiple IAVs coinfect the same cell, leading to viruses harboring combinations of eight genomic segments from distinct parental viruses. Existing data indicate that reassortant genotypes are not equiprobable; however, the low throughput of available virology techniques does not allow quantitative analysis. Here, we have developed a high-throughput single-cell droplet microfluidic system allowing encapsulation of IAV-infected cells, each cell being infected by a single progeny virion resulting from a coinfection process. Customized barcoded primers for targeted viral RNA sequencing enabled the analysis of 18,422 viral genotypes resulting from coinfection with two circulating human H1N1pdm09 and H3N2 IAVs. Results were highly reproducible, confirmed that genetic reassortment is far from random, and allowed accurate quantification of reassortants including rare events. In total, 159 out of the 254 possible reassortant genotypes were observed but with widely varied prevalence (from 0.038 to 8.45%). In cells where eight segments were detected, all 112 possible pairwise combinations of segments were observed. The inclusion of data from single cells where less than eight segments were detected allowed analysis of pairwise cosegregation between segments with very high confidence. Direct coupling analysis accurately predicted the fraction of pairwise segments and full genotypes. Overall, our results indicate that a large proportion of reassortant genotypes can emerge upon coinfection and be detected over a wide range of frequencies, highlighting the power of our tool for systematic and exhaustive monitoring of the reassortment potential of IAVs.

Nonproductive Hepatitis B Virus Covalently Closed Circular DNA Generates HBx-Related Transcripts from the HBx/Enhancer I Region and Acquires Reactivation by Superinfection in Single Cells

Hepatitis B virus (HBV) infection remains a public health problem worldwide. Persistent HBV infection relies on active transcription of the covalently closed circular DNA (cccDNA) in hepatocytes, which is less understood at the single-cell level. In this study, we isolated primary human hepatocytes from liver-humanized FRG mice infected with HBV and examined cccDNA transcripts in single cells based on 5' end sequencing. Our 5' transcriptome sequencing (RNA-seq) analysis unambiguously assigns different viral transcripts with overlapping 3' sequences and quantitatively measures viral transcripts for structural genes (3.5 kb, 2.4 kb, and 2.1 kb) and the nonstructural X gene (0.7 kb and related) in single cells. We found that an infected cell either can generate all viral transcripts, signifying active transcription, or presents only transcripts from the X gene and its associated enhancer I domain and no structural gene transcripts. Results from cell infection assays with recombinant HBV show that nonproductive transcription of cccDNA can be activated by incoming virus through superinfection. Moreover, upon HBV infection, cccDNA apparently can be transcribed in the absence of HBx and produces HBx, needed for productive transcription of other viral genes. These results shed new light on cccDNA transcription at the single-cell level and provide insights useful for improving the treatment strategy against chronic HBV infection. IMPORTANCE Hepatitis B virus (HBV) infection can be effectively suppressed but rarely cured by available drugs. Chronic HBV infection is based on persistence of covalently closed circular DNA (cccDNA) and continuous infection and reinfection with HBV in the liver. Understanding transcriptional regulation of cccDNA will help to achieve permanent transcriptional silencing, i.e., functional cure of HBV. In our study, we found that an infected cell either can generate all viral transcripts, signifying active transcription, or presents only transcripts from the X gene and its associated enhancer I domain and no structural gene transcripts. The nonproductive transcription of cccDNA can be activated by incoming virus through superinfection. Upon an infection, cccDNA apparently can be transcribed in the absence of HBx to produce HBx, necessary for subsequent transcription of other HBV genes. Our studies shed new light on the mechanism of HBV infection and may have implications for a functional cure regimen for HBV.

Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics

The insect cell-baculovirus expression vector system (IC-BEVS) has been widely used to produce recombinant protein at high titers, including complex virus-like particles (VPLs). However, cell-to-cell variability upon infection is yet one of the least understood phenomena in virology, and little is known about its impact on production of therapeutic proteins. This study aimed at dissecting insect cell population heterogeneity during production of influenza VLPs in IC-BEVS using single-cell RNA-seq (scRNA-seq). High Five cell population was shown to be heterogeneous even before infection, with cell cycle being one of the factors contributing for this variation. In addition, infected insect cells were clustered according to the timing and level of baculovirus genes expression, with each cluster reporting similar influenza VLPs transgenes (i.e., hemagglutinin and M1) transcript counts. Trajectory analysis enabled to track infection progression throughout pseudotime. Specific pathways such as translation machinery, protein folding, sorting and degradation, endocytosis and energy metabolism were identified as being those which vary the most during insect cell infection and production of Influenza VLPs. Overall, this study lays the ground for the application of scRNA-seq in IC-BEVS processes to isolate relevant biological mechanisms during recombinant protein expression towards its further optimization.

Single-cell RNA-sequencing data analysis reveals a highly correlated triphasic transcriptional response to SARS-CoV-2 infection

Single-cell RNA sequencing (scRNA-seq) is currently one of the most powerful techniques available to study the transcriptional response of thousands of cells to an external perturbation. Here, we perform a pseudotime analysis of SARS-CoV-2 infection using publicly available scRNA-seq data from human bronchial epithelial cells and colon and ileum organoids. Our results reveal that, for most genes, the transcriptional response to SARS-CoV-2 infection follows a non-linear pattern characterized by an initial and a final down-regulatory phase separated by an intermediate up-regulatory stage. A correlation analysis of transcriptional profiles suggests a common mechanism regulating the mRNA levels of most genes. Interestingly, genes encoded in the mitochondria or involved in translation exhibited distinct pseudotime profiles. To explain our results, we propose a simple model where nuclear export inhibition of nsp1-sensitive transcripts will be sufficient to explain the transcriptional shutdown of SARS-CoV-2 infected cells.

Incomplete bunyavirus particles can cooperatively support virus infection and spread

Bunyaviruses lack a specific mechanism to ensure the incorporation of a complete set of genome segments into each virion, explaining the generation of incomplete virus particles lacking one or more genome segments. Such incomplete virus particles, which may represent the majority of particles produced, are generally considered to interfere with virus infection and spread. Using the three-segmented arthropod-borne Rift Valley fever virus as a model bunyavirus, we here show that two distinct incomplete virus particle populations unable to spread autonomously are able to efficiently complement each other in both mammalian and insect cells following co-infection. We further show that complementing incomplete virus particles can co-infect mosquitoes, resulting in the reconstitution of infectious virus that is able to disseminate to the mosquito salivary glands. Computational models of infection dynamics predict that incomplete virus particles can positively impact virus spread over a wide range of conditions, with the strongest effect at intermediate multiplicities of infection. Our findings suggest that incomplete particles may play a significant role in within-host spread and between-host transmission, reminiscent of the infection cycle of multipartite viruses.

Single-cell genome-wide association reveals that a nonsynonymous variant in ERAP1 confers increased susceptibility to influenza virus

During pandemics, individuals exhibit differences in risk and clinical outcomes. Here, we developed single-cell high-throughput human in vitro susceptibility testing (scHi-HOST), a method for rapidly identifying genetic variants that confer resistance and susceptibility. We applied this method to influenza A virus (IAV), the cause of four pandemics since the start of the 20th century. scHi-HOST leverages single-cell RNA sequencing (scRNA-seq) to simultaneously assign genetic identity to cells in mixed infections of cell lines of European, African, and Asian origin, reveal associated genetic variants for viral burden, and identify expression quantitative trait loci. Integration of scHi-HOST with human challenge and experimental validation demonstrated that a missense variant in endoplasmic reticulum aminopeptidase 1 (ERAP1; rs27895) increased IAV burden in cells and human volunteers. rs27895 exhibits population differentiation, likely contributing to greater permissivity of cells from African populations to IAV. scHi-HOST is a broadly applicable method and resource for decoding infectious-disease genetics.

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.

An anti-influenza combined therapy assessed by single cell RNA-sequencing

Influenza makes millions of people ill every year, placing a large burden on the healthcare system and the economy. To develop a treatment against influenza, we combined virucidal sialylated cyclodextrins with interferon lambda and demonstrated, in human airway epithelia, that the two compounds inhibit the replication of a clinical H1N1 strain more efficiently when administered together rather than alone. We investigated the mechanism of action of the combined treatment by single cell RNA-sequencing analysis and found that both the single and combined treatments impair viral replication to different extents across distinct epithelial cell types. We showed that each cell type comprises multiple sub-types, whose proportions are altered by H1N1 infection, and assessed the ability of the treatments to restore them. To the best of our knowledge this is the first study investigating the effectiveness of an antiviral therapy against influenza virus by single cell transcriptomic studies.

When combined with interferon lambda, virucidal sialylated cyclodextrins inhibit the replication of a clinical H1N1 influenza strain in ex vivo human airway epithelia more efficiently than when delivered alone.

Comprehensive single cell analysis of pandemic influenza A virus infection in the human airways uncovers cell-type specific host transcriptional signatures relevant for disease progression and pathogenesis

The respiratory epithelium constitutes the first line of defense against invading respiratory pathogens, such as the 2009 pandemic strain of influenza A virus (IAV, H1N1pdm09), and plays a crucial role in the host antiviral response to infection. Despite its importance, however, it remains unknown how individual cell types within the respiratory epithelium respond to IAV infection or how the latter may influence IAV disease progression and pathogenesis. Here, we used single cell RNA sequencing (scRNA-seq) to dissect the host response to IAV infection in its natural target cells. scRNA-seq was performed on human airway epithelial cell (hAEC) cultures infected with either wild-type pandemic IAV (WT) or with a mutant version of IAV (NS1_R38A) that induced a robust innate immune response. We then characterized both the host and viral transcriptomes of more than 19,000 single cells across the 5 major cell types populating the human respiratory epithelium. For all cell types, we observed a wide spectrum of viral burden among single infected cells and a disparate host response between infected and bystander populations. Interestingly, we also identified multiple key differences in the host response to IAV among individual cell types, including high levels of pro-inflammatory cytokines and chemokines in secretory and basal cells and an important role for luminal cells in sensing and restricting incoming virus. Multiple infected cell types were shown to upregulate interferons (IFN), with type III IFNs clearly dominating the antiviral response. Transcriptional changes in genes related to cell differentiation, cell migration, and tissue repair were also identified. Strikingly, we also detected a shift in viral host cell tropism from non-ciliated cells to ciliated cells at later stages of infection and observed major changes in the cellular composition. Microscopic analysis of both WT and NS1_R38A virus-infected hAECs at various stages of IAV infection revealed that the transcriptional changes we observed at 18 hpi were likely driving the downstream histopathological alterations in the airway epithelium. To our knowledge, this is the first study to provide a comprehensive analysis of the cell type-specific host antiviral response to influenza virus infection in its natural target cells – namely, the human respiratory epithelium.

Human alveolar progenitors generate dual lineage bronchioalveolar organoids

Mechanisms of epithelial renewal in the alveolar compartment remain incompletely understood. To this end, we aimed to characterize alveolar progenitors. Single-cell RNA-sequencing (scRNA-seq) analysis of the HTII-280⁺/EpCAM⁺ population from adult human lung revealed subclusters enriched for adult stem cell signature (ASCS) genes. We found that alveolar progenitors in organoid culture in vitro show phenotypic lineage plasticity as they can yield alveolar or bronchial cell-type progeny. The direction of the differentiation is dependent on the presence of the GSK-3β inhibitor, CHIR99021. By RNA-seq profiling of GSK-3β knockdown organoids we identified additional candidate target genes of the inhibitor, among others FOXM1 and EGF. This gives evidence of Wnt pathway independent regulatory mechanisms of alveolar specification. Following influenza A virus (IAV) infection organoids showed a similar response as lung tissue explants which confirms their suitability for studies of sequelae of pathogen-host interaction.

Heterogeneity in viral populations increases the rate of deleterious mutation accumulation

RNA viruses have high mutation rates, with the majority of mutations being deleterious. We examine patterns of deleterious mutation accumulation over multiple rounds of viral replication, with a focus on how cellular coinfection and heterogeneity in viral output affect these patterns. Specifically, using agent-based intercellular simulations we find, in agreement with previous studies, that coinfection of cells by viruses relaxes the strength of purifying selection, and thereby increases the rate of deleterious mutation accumulation. We further find that cellular heterogeneity in viral output exacerbates the rate of deleterious mutation accumulation, regardless of whether this heterogeneity in viral output is stochastic or is due to variation in cellular multiplicity of infection. These results highlight the need to consider the unique life histories of viruses and their population structure to better understand observed patterns of viral evolution.

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.

A Virus Is a Community: Diversity within Negative-Sense RNA Virus Populations

Negative-sense RNA virus populations are composed of diverse viral components that interact to form a community and shape the outcome of virus infections. At the genomic level, RNA virus populations consist not only of a homogeneous population of standard viral genomes but also of an extremely large number of genome variants, termed viral quasispecies, and nonstandard viral genomes, which include copy-back viral genomes, deletion viral genomes, mini viral RNAs, and hypermutated RNAs. At the particle level, RNA virus populations are composed of pleomorphic particles, particles missing or having additional genomes, and single particles or particle aggregates. As we continue discovering more about the components of negative-sense RNA virus populations and their crucial functions during virus infection, it will become more important to study RNA virus populations as a whole rather than their individual parts. In this review, we will discuss what is known about the components of negative-sense RNA virus communities, speculate how the components of the virus community interact, and summarize what vaccines and antiviral therapies are being currently developed to target or harness these components.

Droplet Microfluidics for High-Resolution Virology

Microfluidics has enabled a new era of cellular and molecular assays due to the small length scales, parallelization, and the modularity of various analysis and actuation functions. Droplet microfluidics, in particular, has been instrumental in providing new tools for biology with its ability to quickly and reproducibly generate drops that act as individual reactors. A notable beneficiary of this technology has been single-cell RNA sequencing, which has revealed new heterogeneities and interactions for the fundamental unit of life. However, viruses far surpass the diversity of cellular life, affect the dynamics of all ecosystems, and are a chronic source of global health crises. Despite their impact on the world, high-throughput and high-resolution viral profiling has been difficult, with conventional methods being limited to population-level averaging, large sample volumes, and few cultivable hosts. Consequently, most viruses have not been identified and studied. Droplet microfluidics holds the potential to address many of these limitations and offers new levels of sensitivity and throughput for virology. This Feature highlights recent efforts that have applied droplet microfluidics to the detection and study of viruses, including for diagnostics, virus-host interactions, and cell-independent virus assays. In combination with traditional virology methods, droplet microfluidics should prove a potent tool toward achieving a better understanding of the most abundant biological species on Earth.

Functional single-cell genomics of human cytomegalovirus infection

Understanding how viral and host factors interact and how perturbations impact infection is the basis for designing antiviral interventions. Here we define the functional contribution of each viral and host factor involved in human cytomegalovirus infection in primary human fibroblasts through pooled CRISPR interference and nuclease screening. To determine how genetic perturbation of critical host and viral factors alters the timing, course and progression of infection, we applied Perturb-seq to record the transcriptomes of tens of thousands of CRISPR-modified single cells and found that, normally, most cells follow a stereotypical transcriptional trajectory. Perturbing critical host factors does not change the stereotypical transcriptional trajectory per se but can stall, delay or accelerate progression along the trajectory, allowing one to pinpoint the stage of infection at which host factors act. Conversely, perturbation of viral factors can create distinct, abortive trajectories. Our results reveal the roles of host and viral factors and provide a roadmap for the dissection of host-pathogen interactions.