Single-Cell Virology: On-Chip Investigation of Viral Infection Dynamics

WNV and SLEV coinfection in avian and mosquito hosts: impact on viremia, antibody responses, and vector competence

West Nile virus (WNV) and St. Louis encephalitis virus (SLEV) are closely related flaviviruses that can cause encephalitis in humans and related diseases in animals. In nature, both are transmitted by Culex, with wild birds, including jays, sparrows, and robins, serving as vertebrate hosts. WNV and SLEV circulate in the same environments and have recently caused concurrent disease outbreaks in humans. The extent that coinfection of mosquitoes or birds may alter transmission dynamics, however, is not well characterized. We therefore sought to determine if coinfection alters infection kinetics and virus levels in birds and infection rates in mosquitoes. Accordingly, American robins (Turdus migratorius), two species of mosquitoes, and vertebrate and invertebrate cells were infected with WNV and/or SLEV to assess how simultaneous exposure may alter infection outcomes. There was variable impact of coinfection in vertebrate cells, with some evidence that SLEV can suppress WNV replication. However, robins had comparable viremia and antibody responses regardless of coinfection. Conversely, in Culex cells and mosquitoes, we saw a minimal impact of simultaneous exposure to both viruses on replication, with comparable infection, dissemination, and transmission rates in singly infected and coinfected mosquitoes. Importantly, while WNV and SLEV levels in coinfected mosquito midguts were positively correlated, we saw no correlation between them in salivary glands and saliva. These results reveal that while coinfection can occur in both avian and mosquito hosts, the viruses minimally impact one another. The potential for coinfection to alter virus population structure or the likelihood of rare genotypes emerging remains unknown.IMPORTANCEWest Nile virus (WNV) and St. Louis encephalitis virus (SLEV) are closely related viruses that are transmitted by the same mosquitoes and infect the same birds in nature. Both viruses circulate in the same regions and have caused concurrent outbreaks in humans. It is possible that mosquitoes, birds, and/or humans could be infected with both WNV and SLEV simultaneously, as has been observed with Zika, chikungunya, and dengue viruses. To study the impact of coinfection, we experimentally infected vertebrate and invertebrate cells, American robins, and two Culex species with WNV and/or SLEV. Robins were efficiently coinfected, with no impact of coinfection on virus levels or immune response. Similarly, in mosquitoes, coinfection did not impact infection rates, and mosquitoes could transmit both WNV and SLEV together. These results reveal that WNV and SLEV coinfection in birds and mosquitoes can occur in nature, which may impact public health and human disease risk.

Non-lytic spread of poliovirus requires the nonstructural protein 3CD

Non-enveloped viruses like poliovirus (PV) have evolved the capacity to spread by non-lytic mechanisms. For PV, this mechanism exploits the host secretory autophagy pathway. Virions are selectively incorporated into autophagosomes, double-membrane vesicles that travel to the plasma membrane, fuse, and release single-membrane vesicles containing virions. Loading of cellular cargo into autophagosomes relies on direct or indirect interactions with microtubule-associated protein 1B-light chain 3 (LC3) that are mediated by motifs referred to as LC3-interaction regions (LIRs). We have identified a PV mutant with a severe defect in non-lytic spread. An F-to-Y substitution in a putative LIR of the nonstructural protein 3CD prevented virion incorporation into LC3-positive autophagosomes and virion trafficking to the plasma membrane for release. Using high-angle annular dark-field scanning transmission electron microscopy to monitor PV-induced autophagosome biogenesis, for the first time, we show that virus-induced autophagic signals yield normal autophagosomes, even in the absence of virions. The F-to-Y derivative of PV 3CD was unable to support normal autophagosome biogenesis. Together, these studies make a compelling case for a direct role of a viral nonstructural protein in the formation and loading of the vesicular carriers used for non-lytic spread that may depend on the proper structure, accessibility, and/or dynamics of its LIR. The studies of PV 3CD protein reported here will hopefully provoke a more deliberate look at the presence and function of LIR motifs in viral proteins of viruses known to use autophagy as the basis for non-lytic spread.

Single-cell virology: On-chip, quantitative characterization of the dynamics of virus spread from one single cell to another

Virus spread at the single-cell level is largely uncharacterized. We have designed and constructed a microfluidic device in which each nanowell contained a single, infected cell (donor) and a single, uninfected cell (recipient). Using a GFP-expressing poliovirus as our model, we observed both lytic and non-lytic spread. Donor cells supporting lytic spread established infection earlier than those supporting non-lytic spread. However, non-lytic spread established infections in recipient cells substantially faster than lytic spread and yielded higher rates of genome replication. While lytic spread was sensitive to the presence of capsid entry/uncoating inhibitors, non-lytic spread was not. Consistent with emerging models for non-lytic spread of enteroviruses using autophagy, reduction of LC3 levels in cells impaired non-lytic spread and elevated the fraction of virus in donor cells spreading lytically. The ability to distinguish lytic and non-lytic spread unambiguously will enable discovery of viral and host factors and host pathways used for non-lytic spread of enteroviruses and other viruses as well.

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.

Single-cell analysis of VACV infection reveals pathogen-driven timing of early and late phases and host-limited dynamics of virus production

The extent and origin of variation in the replication dynamics of complex DNA viruses is not well-defined. Here, we investigate the vaccinia virus (VACV) infection cycle at the single-cell level, quantifying the temporal dynamics of early and post(dna)-replicative phase gene expression across thousands of infections. We found that viral factors determine the initiation time of these phases, and this is influenced by the multiplicity of infection (MOI). In contrast, virus production dynamics are largely constrained by the host cell. Additionally, between-cell variability in infection start time and virus production rate were strongly influenced by MOI, providing evidence for cooperativity between infecting virions. Blocking programmed cell death by pan-caspase inhibition increased infection frequency but not virus production at the population level due to a concurrent attenuation of per-cell virus yield, suggesting a dual role for caspase signaling in VACV infection. Our findings provide key insights into the pivotal factors influencing heterogeneity in the infection cycle of a large DNA virus at the single-cell level.

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.

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.

Exploiting Sound for Emerging Applications of Extracellular Vesicles

Extracellular vesicles are nano- to microscale, membrane-bound particles released by cells into extracellular space, and act as carriers of biomarkers and therapeutics, holding promising potential in translational medicine. However, the challenges remain in handling and detecting extracellular vesicles for disease diagnosis as well as exploring their therapeutic capability for disease treatment. Here, we review the recent engineering and technology advances by leveraging the power of sound waves to address the challenges in diagnostic and therapeutic applications of extracellular vesicles and biomimetic nanovesicles. We first introduce the fundamental principles of sound waves for understanding different acoustic-assisted extracellular vesicle technologies. We discuss the acoustic-assisted diagnostic methods including the purification, manipulation, biosensing, and bioimaging of extracellular vesicles. Then, we summarize the recent advances in acoustically enhanced therapeutics using extracellular vesicles and biomimetic nanovesicles. Finally, we provide perspectives into current challenges and future clinical applications of the promising extracellular vesicles and biomimetic nanovesicles powered by sound.

Computational Modeling Insights into Extreme Heterogeneity in COVID-19 Nasal Swab Data

Throughout the COVID-19 pandemic, an unprecedented level of clinical nasal swab data from around the globe has been collected and shared. Positive tests have consistently revealed viral titers spanning six orders of magnitude! An open question is whether such extreme population heterogeneity is unique to SARS-CoV-2 or possibly generic to viral respiratory infections. To probe this question, we turn to the computational modeling of nasal tract infections. Employing a physiologically faithful, spatially resolved, stochastic model of respiratory tract infection, we explore the statistical distribution of human nasal infections in the immediate 48 h of infection. The spread, or heterogeneity, of the distribution derives from variations in factors within the model that are unique to the infected host, infectious variant, and timing of the test. Hypothetical factors include: (1) reported physiological differences between infected individuals (nasal mucus thickness and clearance velocity); (2) differences in the kinetics of infection, replication, and shedding of viral RNA copies arising from the unique interactions between the host and viral variant; and (3) differences in the time between initial cell infection and the clinical test. Since positive clinical tests are often pre-symptomatic and independent of prior infection or vaccination status, in the model we assume immune evasion throughout the immediate 48 h of infection. Model simulations generate the mean statistical outcomes of total shed viral load and infected cells throughout 48 h for each "virtual individual", which we define as each fixed set of model parameters (1) and (2) above. The "virtual population" and the statistical distribution of outcomes over the population are defined by collecting clinically and experimentally guided ranges for the full set of model parameters (1) and (2). This establishes a model-generated "virtual population database" of nasal viral titers throughout the initial 48 h of infection of every individual, which we then compare with clinical swab test data. Support for model efficacy comes from the sampling of infection dynamics over the virtual population database, which reproduces the six-order-of-magnitude clinical population heterogeneity. However, the goal of this study is to answer a deeper biological and clinical question. What is the impact on the dynamics of early nasal infection due to each individual physiological feature or virus-cell kinetic mechanism? To answer this question, global data analysis methods are applied to the virtual population database that sample across the entire database and de-correlate (i.e., isolate) the dynamic infection outcome sensitivities of each model parameter. These methods predict the dominant, indeed exponential, driver of population heterogeneity in dynamic infection outcomes is the latency time of infected cells (from the moment of infection until onset of viral RNA shedding). The shedding rate of the viral RNA of infected cells in the shedding phase is a strong, but not exponential, driver of infection. Furthermore, the unknown timing of the nasal swab test relative to the onset of infection is an equally dominant contributor to extreme population heterogeneity in clinical test data since infectious viral loads grow from undetectable levels to more than six orders of magnitude within 48 h.

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.

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.

Modeling suggests that virion production cycles within individual cells is key to understanding acute hepatitis B virus infection kinetics

Hepatitis B virus (HBV) infection kinetics in immunodeficient mice reconstituted with humanized livers from inoculation to steady state is highly dynamic despite the absence of an adaptive immune response. To recapitulate the multiphasic viral kinetic patterns, we developed an agent-based model that includes intracellular virion production cycles reflecting the cyclic nature of each individual virus lifecycle. The model fits the data well predicting an increase in production cycles initially starting with a long production cycle of 1 virion per 20 hours that gradually reaches 1 virion per hour after approximately 3-4 days before virion production increases dramatically to reach to a steady state rate of 4 virions per hour per cell. Together, modeling suggests that it is the cyclic nature of the virus lifecycle combined with an initial slow but increasing rate of HBV production from each cell that plays a role in generating the observed multiphasic HBV kinetic patterns in humanized mice.

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.

Modeling identifies variability in SARS-CoV-2 uptake and eclipse phase by infected cells as principal drivers of extreme variability in nasal viral load in the 48 h post infection

The SARS-CoV-2 coronavirus continues to evolve with scores of mutations of the spike, membrane, envelope, and nucleocapsid structural proteins that impact pathogenesis. Infection data from nasal swabs, nasal PCR assays, upper respiratory samples, ex vivo cell cultures and nasal epithelial organoids reveal extreme variabilities in SARS-CoV-2 RNA titers within and between the variants. Some variabilities are naturally prone to clinical testing protocols and experimental controls. Here we focus on nasal viral load sensitivity arising from the timing of sample collection relative to onset of infection and from heterogeneity in the kinetics of cellular infection, uptake, replication, and shedding of viral RNA copies. The sources of between-variant variability are likely due to SARS-CoV-2 structural protein mutations, whereas within-variant population variability is likely due to heterogeneity in cellular response to that particular variant. With the physiologically faithful, agent-based mechanistic model of inhaled exposure and infection from (Chen et al., 2022), we perform statistical sensitivity analyses of the progression of nasal viral titers in the first 0-48 h post infection, focusing on three kinetic mechanisms. Model simulations reveal shorter latency times of infected cells (including cellular uptake, viral RNA replication, until the onset of viral RNA shedding) exponentially accelerate nasal viral load. Further, the rate of infectious RNA copies shed per day has a proportional influence on nasal viral load. Finally, there is a very weak, negative correlation of viral load with the probability of infection per virus-cell encounter, the model proxy for spike-receptor binding affinity.

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.

The enterovirus genome can be translated in an IRES-independent manner that requires the initiation factors eIF2A/eIF2D

RNA recombination in positive-strand RNA viruses is a molecular-genetic process, which permits the greatest evolution of the genome and may be essential to stabilizing the genome from the deleterious consequences of accumulated mutations. Enteroviruses represent a useful system to elucidate the details of this process. On the biochemical level, it is known that RNA recombination is catalyzed by the viral RNA-dependent RNA polymerase using a template-switching mechanism. For this mechanism to function in cells, the recombining genomes must be located in the same subcellular compartment. How a viral genome is trafficked to the site of genome replication and recombination, which is membrane associated and isolated from the cytoplasm, is not known. We hypothesized that genome translation was essential for colocalization of genomes for recombination. We show that complete inactivation of internal ribosome entry site (IRES)-mediated translation of a donor enteroviral genome enhanced recombination instead of impairing it. Recombination did not occur by a nonreplicative mechanism. Rather, sufficient translation of the nonstructural region of the genome occurred to support subsequent steps required for recombination. The noncanonical translation initiation factors, eIF2A and eIF2D, were required for IRES-independent translation. Our results support an eIF2A/eIF2D-dependent mechanism under conditions in which the eIF2-dependent mechanism is inactive. Detection of an IRES-independent mechanism for translation of the enterovirus genome provides an explanation for a variety of debated observations, including nonreplicative recombination and persistence of enteroviral RNA lacking an IRES. The existence of an eIF2A/eIF2D-dependent mechanism in enteroviruses predicts the existence of similar mechanisms in other viruses.

Noninvasive prenatal diagnosis targeting fetal nucleated red blood cells

Noninvasive prenatal diagnosis (NIPD) aims to detect fetal-related genetic disorders before birth by detecting markers in the peripheral blood of pregnant women, holding the potential in reducing the risk of fetal birth defects. Fetal-nucleated red blood cells (fNRBCs) can be used as biomarkers for NIPD, given their remarkable nature of carrying the entire genetic information of the fetus. Here, we review recent advances in NIPD technologies based on the isolation and analysis of fNRBCs. Conventional cell separation methods rely primarily on physical properties and surface antigens of fNRBCs, such as density gradient centrifugation, fluorescence-activated cell sorting, and magnetic-activated cell sorting. Due to the limitations of sensitivity and purity in Conventional methods, separation techniques based on micro-/nanomaterials have been developed as novel methods for isolating and enriching fNRBCs. We also discuss emerging methods based on microfluidic chips and nanostructured substrates for static and dynamic isolation of fNRBCs. Additionally, we introduce the identification techniques of fNRBCs and address the potential clinical diagnostic values of fNRBCs. Finally, we highlight the challenges and the future directions of fNRBCs as treatment guidelines in NIPD.

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.

Viro-fluidics: Real-time analysis of virus production kinetics at the single-cell level

Real-time visualization and quantification of viruses released by a cell are crucial to further decipher infection processes. Kinetics studies at the single-cell level will circumvent the limitations of bulk assays with asynchronous virus replication. We have implemented a "viro-fluidic" method, which combines microfluidics and virology at single-cell and single-virus resolutions. As an experimental model, we used standard cell lines producing fluorescent HIV-like particles (VLPs). First, to scale the strategy to the single-cell level, we validated a sensitive flow virometry system to detect VLPs in low concentration samples (≥10⁴ VLPs/mL). Then, this system was coupled to a single-cell trapping device to monitor in real-time the VLPs released, one at a time, from single cells under cell culture conditions. Our results revealed an average production rate of 50 VLPs/h/cell similar to the rate estimated for the same cells grown in population. Thus, the virus-producing capacities of the trapped cells were preserved and its real-time monitoring was accurate. Moreover, single-cell analysis revealed a release of VLPs with stochastic bursts with typical time intervals of few minutes, revealing the existence of limiting step(s) in the virus biogenesis process. Our tools can be applied to other pathogens or to extracellular vesicles to elucidate the dissemination mechanisms of these biological nanoparticles.

Engineering viral genomics and nano-liposomes in microfluidic platforms for patient-specific analysis of SARS-CoV-2 variants

New variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are continuing to spread globally, contributing to the persistence of the COVID-19 pandemic. Increasing resources have been focused on developing vaccines and therapeutics that target the Spike glycoprotein of SARS-CoV-2. Recent advances in microfluidics have the potential to recapitulate viral infection in the organ-specific platforms, known as organ-on-a-chip (OoC), in which binding of SARS-CoV-2 Spike protein to the angiotensin-converting enzyme 2 (ACE2) of the host cells occurs. As the COVID-19 pandemic lingers, there remains an unmet need to screen emerging mutations, to predict viral transmissibility and pathogenicity, and to assess the strength of neutralizing antibodies following vaccination or reinfection. Conventional detection of SARS-CoV-2 variants relies on two-dimensional (2-D) cell culture methods, whereas simulating the micro-environment requires three-dimensional (3-D) systems. To this end, analyzing SARS-CoV-2-mediated pathogenicity via microfluidic platforms minimizes the experimental cost, duration, and optimization needed for animal studies, and obviates the ethical concerns associated with the use of primates. In this context, this review highlights the state-of-the-art strategy to engineer the nano-liposomes that can be conjugated with SARS-CoV-2 Spike mutations or genomic sequences in the microfluidic platforms; thereby, allowing for screening the rising SARS-CoV-2 variants and predicting COVID-19-associated coagulation. Furthermore, introducing viral genomics to the patient-specific blood accelerates the discovery of therapeutic targets in the face of evolving viral variants, including B1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), c.37 (Lambda), and B.1.1.529 (Omicron). Thus, engineering nano-liposomes to encapsulate SARS-CoV-2 viral genomic sequences enables rapid detection of SARS-CoV-2 variants in the long COVID-19 era.

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.

A microfluidic cell chip for virus isolation via rapid screening for permissive cells

Virus identification is a prerequisite not only for the early diagnosis of viral infectious diseases but also for the effective prevention of epidemics. Successful cultivation is the gold standard for identifying a virus, according to the Koch postulates. However, this requires screening for a permissive cell line, which is traditionally time-, reagent- and labor-intensive. Here, a simple and easy-to-operate microfluidic chip, formed by seeding a variety of cell lines and culturing them in parallel, is reported for use in virus cultivation and virus-permissive host-cell screening. The chip was tested by infection with two known viruses, enterovirus 71 (EV71) and influenza virus H1N1. Infection with EV71 and H1N1 caused significant cytopathic effects (CPE) in RD and MDCK cells, respectively, demonstrating that virus cultivation based on this microfluidic cell chip can be used as a substitute for the traditional plate-based culture method and reproduce the typical CPE caused by virus infection. Using this microfluidic cell chip method for virus cultivation could make it possible to identify an emerging virus in a high-throughput, automatic, and unprecedentedly fast way.

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A simple microfluidic chip for tandem culture of different cell lines is achieved.

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The cell chip has been used for permissive cell screening and culture of viruses.

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The cell chip has advantages of being sample-, reagent-, and time-saving.

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The cell chip system holds potential for high-throughput and automated screening.

Evaluation of cancer immunotherapy using mini-tumor chips

Rationale: Predicting tumor responses to adjuvant therapies can potentially help guide treatment decisions and improve patient survival. Currently, tumor pathology, histology, and molecular profiles are being integrated into personalized profiles to guide therapeutic decisions. However, it remains a grand challenge to evaluate tumor responses to immunotherapy for personalized medicine. Methods: We present a microfluidics-based mini-tumor chip approach to predict tumor responses to cancer immunotherapy in a preclinical model. By uniformly infusing dissociated tumor cells into isolated microfluidic well-arrays, 960 mini-tumors could be uniformly generated on-chip, with each well representing the ex vivo tumor niche that preserves the original tumor cell composition and dynamic cell-cell interactions and autocrine/paracrine cytokines. Results: By incorporating time-lapse live-cell imaging, our mini-tumor chip allows the investigation of dynamic immune-tumor interactions as well as their responses to cancer immunotherapy (e.g., anti-PD1 treatment) in parallel within 36 hours. Additionally, by establishing orthotopic breast tumor models with constitutive differential PD-L1 expression levels, we showed that the on-chip interrogation of the primary tumor's responses to anti-PD1 as early as 10 days post tumor inoculation could predict the in vivo tumors' responses to anti-PD1 at the endpoint of day 24. We also demonstrated the application of this mini-tumor chip to interrogate on-chip responses of primary tumor cells isolated from primary human breast and renal tumor tissues. Conclusions: Our approach provides a simple, quick-turnaround solution to measure tumor responses to cancer immunotherapy.

Recent advances in microfluidic devices for single-cell cultivation: methods and applications

Single-cell analysis is essential to improve our understanding of cell functionality from cellular and subcellular aspects for diagnosis and therapy. Single-cell cultivation is one of the most important processes in single-cell analysis, which allows the monitoring of actual information of individual cells and provides sufficient single-cell clones and cell-derived products for further analysis. The microfluidic device is a fast-rising system that offers efficient, effective, and sensitive single-cell cultivation and real-time single-cell analysis conducted either on-chip or off-chip. Here, we introduce the importance of single-cell cultivation from the aspects of cellular and subcellular studies. We highlight the materials and structures utilized in microfluidic devices for single-cell cultivation. We further discuss biological applications utilizing single-cell cultivation-based microfluidics, such as cellular phenotyping, cell-cell interactions, and omics profiling. Finally, present limitations and future prospects of microfluidics for single-cell cultivation are also discussed.

Individual bacteria in structured environments rely on phenotypic resistance to phage

Bacteriophages represent an avenue to overcome the current antibiotic resistance crisis, but evolution of genetic resistance to phages remains a concern. In vitro, bacteria evolve genetic resistance, preventing phage adsorption or degrading phage DNA. In natural environments, evolved resistance is lower possibly because the spatial heterogeneity within biofilms, microcolonies, or wall populations favours phenotypic survival to lytic phages. However, it is also possible that the persistence of genetically sensitive bacteria is due to less efficient phage amplification in natural environments, the existence of refuges where bacteria can hide, and a reduced spread of resistant genotypes. Here, we monitor the interactions between individual planktonic bacteria in isolation in ephemeral refuges and bacteriophage by tracking the survival of individual cells. We find that in these transient spatial refuges, phenotypic resistance due to reduced expression of the phage receptor is a key determinant of bacterial survival. This survival strategy is in contrast with the emergence of genetic resistance in the absence of ephemeral refuges in well-mixed environments. Predictions generated via a mathematical modelling framework to track bacterial response to phages reveal that the presence of spatial refuges leads to fundamentally different population dynamics that should be considered in order to predict and manipulate the evolutionary and ecological dynamics of bacteria–phage interactions in naturally structured environments.

Bacteriophages represent a promising avenue to overcome the current antibiotic resistance crisis, but evolution of phage resistance remains a concern. This study shows that in the presence of spatial refuges, genetic resistance to phage is less of a problem than commonly assumed, but the persistence of genetically susceptible bacteria suggests that eradicating bacterial pathogens from structured environments may require combined phage-antibiotic therapies.

Dengue virus is sensitive to inhibition prior to productive replication

Uncovering vulnerable steps in the life cycle of viruses supports the rational design of antiviral treatments. However, information on viral replication dynamics obtained from traditional bulk assays with host cell populations is inherently limited as the data represent averages over a multitude of unsynchronized replication cycles. Here, we use time-lapse imaging of virus replication in thousands of single cells, combined with computational inference, to identify rate-limiting steps for dengue virus (DENV), a widespread human pathogen. Comparing wild-type DENV with a vaccine candidate mutant, we show that the viral spread in the mutant is greatly attenuated by delayed onset of productive replication, whereas wild-type and mutant virus have identical replication rates. Single-cell analysis done after applying the broad-spectrum antiviral drug, ribavirin, at clinically relevant concentrations revealed the same mechanism of attenuating viral spread. We conclude that the initial steps of infection, rather than the rate of established replication, are quantitatively limiting DENV spread.

Single-cell analysis for the study of viral inhibitors

Stochastic outcomes of viral infections are attributed in large part to multiple layers of intrinsic and extrinsic heterogeneity that exist within a population of cells and viruses. Traditional methods in virology often lack the ability to demonstrate cell-to-cell variability in response to the invasion of viruses, and to decipher the sources of heterogeneities that are reflected in the variable infection dynamics. To overcome this challenge, the field of single-cell virology emerged less than a decade ago, enabling researchers to reveal the behavior of single, isolated, infected cells that has been masked in population-based assays. The use of microfluidics in single-cell virology, in particular, has resulted in the development of high-throughput devices that are capable of capturing, isolating, and monitoring single infected cells over the duration of an infection. Results from the studies of viral infection dynamics presented in this chapter indicate how single-cell data provide a more accurate prediction of the start time, replication rate, duration, and yield of infection when compared to population-based data. Additionally, single-cell analysis reveals striking differences between genetically distinct viruses that are almost indistinguishable in population methods. Importantly, both the efficacy and distinct mechanisms of action of antiviral compounds can be elucidated by using single-cell analysis.

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.

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.

Profiling of immune-cancer interactions at the single-cell level using a microfluidic well array

Cancer immunotherapy has achieved great success in hematological cancers. However, immune cells are a highly heterogeneous population and can vary highly in clonal expansion, migration and function status, making it difficult to evaluate and predict patient response to immune therapy. Conventional technologies only yield information on the average population information of the treatment, masking the heterogeneity of the individual T cell activation status, the formation of immune synapse, as well as the efficacy of tumor cell killing at the single-cell level. To fully interrogate these single-cell events in detail, herein, we present a microfluidic microwell array device that enables the massive parallel analysis of the immunocyte's heterogeneity upon its interaction pairs with tumor cells at the single-cell level. By precisely controlling the number and ratio of tumor cells and T cells, our technique can interrogate the dynamics of the CD8+ T cell and leukemia cell interaction inside 6400 microfluidic wells simultaneously. We have demonstrated that by investigating the interactions of T cell and tumor cell pairs at the single-cell level using our microfluidic chip, details hidden in bulk investigations, such as heterogeneity in T cell killing capacity, time-dependent killing dynamics, as well as drug treatment-induced dynamic shifts, can be revealed. This method opens up avenues to investigate the efficacy of cancer immunotherapy and resistance at the single-cell level and can explore our understanding of fundamental cancer immunity as well as determine cancer immunotherapy efficacy for personalized therapy.

Quantitative measurements of early alphaviral replication dynamics in single cells reveals the basis for superinfection exclusion

While decades of research have elucidated many steps of the alphavirus lifecycle, the earliest replication dynamics have remained unclear. This missing time window has obscured early replicase strand-synthesis behavior and prevented elucidation of how the first events of infection might influence subsequent viral competition. Using quantitative live-cell and single-molecule imaging, we observed the initial replicase activity and its strand preferences in situ and measured the trajectory of replication over time. Under this quantitative framework, we investigated viral competition, where one alphavirus is able to exclude superinfection by a second homologous virus. We show that this appears as an indirect phenotypic consequence of a bidirectional competition between the two species, coupled with the rapid onset of viral replication and a limited total cellular carrying capacity. Together, these results emphasize the utility of analyzing viral kinetics within single cells.

Single-Cell Sequencing Applications in the Inner Ear

Genomics studies face specific challenges in the inner ear due to the multiple types and limited amounts of inner ear cells that are arranged in a very delicate structure. However, advances in single-cell sequencing (SCS) technology have made it possible to analyze gene expression variations across different cell types as well as within specific cell groups that were previously considered to be homogeneous. In this review, we summarize recent advances in inner ear research brought about by the use of SCS that have delineated tissue heterogeneity, identified unknown cell subtypes, discovered novel cell markers, and revealed dynamic signaling pathways during development. SCS opens up new avenues for inner ear research, and the potential of the technology is only beginning to be explored.

Mapping of spinal interneurons involved in regulation of the lower urinary tract in juvenile male rats

Coordination between the urinary bladder (BL) and external urethral sphincter (EUS) is necessary for storage and elimination of urine. In rats interneuronal circuits at two levels of the spinal cord (i.e., L6-S1 and L3-L4) play an important role in this coordination. In the present experiments retrograde trans-synaptic transport of pseudorabies virus (PRV) encoding fluorescent markers (GFP and RFP) was used to trace these circuits. To examine the relative localization of EUS-related and BL-related interneuronal populations we injected PRV-GFP into the EUS and PRV-RFP into the BL wall. The PRV infected populations of spinal interneurons were localized primarily in the dorsal commissure (DCM) of L6/S1 and in a hypothesized lumbar spinal coordinating center (LSCC) in L3/L4 above and lateral to central canal (CC). At both sites colocalization of markers occurred in a substantial number of labeled interneurons indicating concomitant involvement of these double-labelled neurons in the EUS- and BL-circuits and suggesting their role in EUS-BL coordination. Intense GFP or RFP fluorescent was detected in a subpopulation of cells at both sites suggesting that they were infected earlier and therefore likely to represent first order, primary interneurons that directly synapse with output neurons. Larger numbers of weakly fluorescent neurons that likely represent second order interneurons were also identified. Within the population of EUS-related first order interneurons only 3-8 % exhibited positive immunoreaction for an early transcription factor Pax2 specific to GABAergic and glycinergic inhibitory neurons suggesting that the majority of interneurons in DCM and LSCC projecting directly to the EUS motoneurons are excitatory.

Cellular co-infection can modulate the efficiency of influenza A virus production and shape the interferon response

During viral infection, the numbers of virions infecting individual cells can vary significantly over time and space. The functional consequences of this variation in cellular multiplicity of infection (MOI) remain poorly understood. Here, we rigorously quantify the phenotypic consequences of cellular MOI during influenza A virus (IAV) infection over a single round of replication in terms of cell death rates, viral output kinetics, interferon and antiviral effector gene transcription, and superinfection potential. By statistically fitting mathematical models to our data, we precisely define specific functional forms that quantitatively describe the modulation of these phenotypes by MOI at the single cell level. To determine the generality of these functional forms, we compare two distinct cell lines (MDCK cells and A549 cells), both infected with the H1N1 strain A/Puerto Rico/8/1934 (PR8). We find that a model assuming that infected cell death rates are independent of cellular MOI best fits the experimental data in both cell lines. We further observe that a model in which the rate and efficiency of virus production increase with cellular co-infection best fits our observations in MDCK cells, but not in A549 cells. In A549 cells, we also find that induction of type III interferon, but not type I interferon, is highly dependent on cellular MOI, especially at early timepoints. This finding identifies a role for cellular co-infection in shaping the innate immune response to IAV infection. Finally, we show that higher cellular MOI is associated with more potent superinfection exclusion, thus limiting the total number of virions capable of infecting a cell. Overall, this study suggests that the extent of cellular co-infection by influenza viruses may be a critical determinant of both viral production kinetics and cellular infection outcomes in a host cell type-dependent manner.

During influenza A virus (IAV) infection, the number of virions to enter individual cells can be highly variable. Cellular co-infection appears to be common and plays an essential role in facilitating reassortment for IAV, yet little is known about how cellular co-infection influences infection outcomes at the cellular level. Here, we combine quantitative in vitro infection experiments with statistical model fitting to precisely define the phenotypic consequences of cellular co-infection in two cell lines. We reveal that cellular co-infection can increase and accelerate the efficiency of IAV production in a cell line-dependent fashion, identifying it as a potential determinant of viral replication kinetics. We also show that induction of type III, but not type I, interferon is highly dependent upon the number of virions that infect a given cell, implicating cellular co-infection as an important determinant of the host innate immune response to infection. Altogether, our findings show that cellular co-infection plays a crucial role in determining infection outcome. The integration of experimental and statistical modeling approaches detailed here represents a significant advance in the quantitative study of influenza virus infection and should aid ongoing efforts focused on the construction of mathematical models of IAV infection.

Acoustofluidic assembly of 3D neurospheroids to model Alzheimer's disease

Neuroinflammation plays a central role in the progression of many neurodegenerative diseases such as Alzheimer's disease, and challenges remain in modeling the complex pathological or physiological processes. Here, we report an acoustofluidic method that can rapidly construct 3D neurospheroids and inflammatory microenvironments for modeling microglia-mediated neuroinflammation in Alzheimer's disease. By incorporating a unique contactless and label-free acoustic assembly, this cell culture platform can assemble dissociated embryonic mouse brain cells into hundreds of uniform 3D neurospheroids with controlled cell numbers, composition (e.g. neurons, astrocytes, and microglia), and environmental components (e.g. amyloid-β aggregates) in hydrogel within minutes. Moreover, this platform can maintain and monitor the interaction among neurons, astrocytes, microglia, and amyloid-β aggregates in real-time for several days to weeks, after the integration of a high-throughput, time-lapse cell imaging approach. We demonstrated that our engineered 3D neurospheroids can represent the amyloid-β neurotoxicity, which is one of the main pathological features of Alzheimer's disease. Using this method, we also investigated the microglia migratory behaviors and activation in the engineered 3D inflammatory microenvironment at a high throughput manner, which is not easy to achieve in 2D neuronal cultures or animal models. Along with the simple fabrication and setup, the acoustofluidic technology is compatible with conventional Petri dishes and well-plates, supports the fine-tuning of the cellular and environmental components of 3D neurospheroids, and enables the high-throughput cellular interaction investigation. We believe our technology may be widely used to facilitate 3D in vitro brain models for modeling neurodegenerative diseases, discovering new drugs, and testing neurotoxicity.

Single cell heterogeneity in influenza A virus gene expression shapes the innate antiviral response to infection

Viral infection outcomes are governed by the complex and dynamic interplay between the infecting virus population and the host response. It is increasingly clear that both viral and host cell populations are highly heterogeneous, but little is known about how this heterogeneity influences infection dynamics or viral pathogenicity. To dissect the interactions between influenza A virus (IAV) and host cell heterogeneity, we examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV virion. We observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at the single cell level. We show that human H1N1 and H3N2 strains differ significantly in patterns of both viral and host anti-viral gene transcriptional heterogeneity at the single cell level. Our analyses also reveal that semi-infectious particles that fail to express the viral NS can play a dominant role in triggering the innate anti-viral response to infection. Altogether, these data reveal how patterns of viral population heterogeneity can serve as a major determinant of antiviral gene activation.

The Role of Single-Cell Technology in the Study and Control of Infectious Diseases

The advent of single-cell research in the recent decade has allowed biological studies at an unprecedented resolution and scale. In particular, single-cell analysis techniques such as Next-Generation Sequencing (NGS) and Fluorescence-Activated Cell Sorting (FACS) have helped show substantial links between cellular heterogeneity and infectious disease progression. The extensive characterization of genomic and phenotypic biomarkers, in addition to host-pathogen interactions at the single-cell level, has resulted in the discovery of previously unknown infection mechanisms as well as potential treatment options. In this article, we review the various single-cell technologies and their applications in the ongoing fight against infectious diseases, as well as discuss the potential opportunities for future development.

Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases

Viral emergence is an unpredictable but obvious event, particularly in the era of climate change and globalization. Efficient management of viral outbreaks depends on pre-existing knowledge and alertness. The potential hotspots of viral emergence often remain neglected and the information related to them is insufficient, particularly for emerging viruses. Viral replication and transmission rely upon usurping the host metabolic machineries. So altered host metabolic pathways can be exploited for containment of these viruses. Metabolomics provides the insight for tracing out such checkpoints. Consequently introspection of metabolic alteration at virus-host interface has evolved as prime area in current virology research. Chromatographic separation followed by mass spectrometry has been used as the predominant analytical platform in bulk of the analyses followed by nuclear magnetic resonance (NMR) and fluorescence based techniques. Although valuable information regarding viral replication and modulation of host metabolic pathways have been extracted but ambiguity often superseded the real events due to population effect over the infected cells. Exploration of cellular heterogeneity and differentiation of infected cells from the nearby healthy ones has become essential. Single cell metabolomics (SCM) emerges as necessity to explore such minute details. Mass spectrometry imaging (MSI) coupled with several soft ionization techniques such as electrospray ionization (ESI), laser ablation electrospray ionization (LAESI), matrix assisted laser desorption/ionization (MALDI), matrix-free laser desorption ionization (LDI) have evolved as the best suited platforms for SCM analyses. The potential of SCM has already been exploited to resolve several biological conundrums. Thus SCM is knocking at the door of virus-host interface.

Microfluidics in Single-Cell Virology: Technologies and Applications

Microfluidics has proven to be a powerful tool for probing biology at the single-cell level. However, it is only in the past 5 years that single-cell microfluidics has been used in the field of virology. An array of strategies based on microwells, microvalves, and droplets is now available for tracking viral infection dynamics, identifying cell subpopulations with particular phenotypes, as well as high-throughput screening. The insights into the virus-host interactions gained at the single-cell level are unprecedented and usually inaccessible by population-based experiments. Therefore, single-cell microfluidics, which opens new avenues for mechanism elucidation and development of antiviral therapeutics, would be a valuable tool for the study of viral pathogenesis.

Immunology in the Era of Single-Cell Technologies

Immune cells are characterized by diversity, specificity, plasticity, and adaptability-properties that enable them to contribute to homeostasis and respond specifically and dynamically to the many threats encountered by the body. Single-cell technologies, including the assessment of transcriptomics, genomics, and proteomics at the level of individual cells, are ideally suited to studying these properties of immune cells. In this review we discuss the benefits of adopting single-cell approaches in studying underappreciated qualities of immune cells and highlight examples where these technologies have been critical to advancing our understanding of the immune system in health and disease.

Progress and applications of single-cell sequencing techniques

Single-cell sequencing (SCS) is a next-generation sequencing method that is mainly used to analyze differences in genetic and protein information between cells, to obtain genetic information on microorganisms that are difficult to cultivate at a single-cell level and to better understand their specific roles in the microenvironment. By sequencing the whole genome, transcriptome and epigenome of a single cell, the complex heterogeneous mechanisms involved in disease occurrence and progression can be revealed, further improving disease diagnosis, prognosis prediction and monitoring of the therapeutic effects of drugs. In this study, we mainly summarized the methods and application fields of SCS, which may provide potential references for its future clinical applications, including the analysis of embryonic and organ development, the immune system, cancer progression, and parasitic and infectious diseases as well as stem cell research, antibody screening, and therapeutic research and development.

Cell-to-Cell Variation in Defective Virus Expression and Effects on Host Responses during Influenza Virus Infection

Defective influenza virus particles generated during viral replication carry incomplete viral genomes and can interfere with the replication of competent viruses. These defective genomes are thought to modulate the disease severity and pathogenicity of an influenza virus infection. Different defective viral genomes also introduce another source of variation across a heterogeneous cell population. Evaluating the impact of defective virus genomes on host cell responses cannot be fully resolved at the population level, requiring single-cell transcriptional profiling. Here, we characterized virus and host transcriptomes in individual influenza virus-infected cells, including those of defective viruses that arise during influenza A virus infection. We established an association between defective virus transcription and host responses and validated interfering and immunostimulatory functions of identified dominant defective viral genome species in vitro. This study demonstrates the intricate effects of defective viral genomes on host transcriptional responses and highlights the importance of capturing host-virus interactions at the single-cell level.

Virus and host factors contribute to cell-to-cell variation in viral infections and determine the outcome of the overall infection. However, the extent of the variability at the single-cell level and how it impacts virus-host interactions at a system level are not well understood. To characterize the dynamics of viral transcription and host responses, we used single-cell RNA sequencing to quantify at multiple time points the host and viral transcriptomes of human A549 cells and primary bronchial epithelial cells infected with influenza A virus. We observed substantial variability in viral transcription between cells, including the accumulation of defective viral genomes (DVGs) that impact viral replication. We show (i) a correlation between DVGs and virus-induced variation of the host transcriptional program and (ii) an association between differential inductions of innate immune response genes and attenuated viral transcription in subpopulations of cells. These observations at the single-cell level improve our understanding of the complex virus-host interplay during influenza virus infection.

Single-Cell Analysis Uncovers a Vast Diversity in Intracellular Viral Defective Interfering RNA Content Affecting the Large Cell-to-Cell Heterogeneity in Influenza A Virus Replication

Virus replication displays a large cell-to-cell heterogeneity; yet, not all sources of this variability are known. Here, we study the effect of defective interfering (DI) particle (DIP) co-infection on cell-to-cell variability in influenza A virus (IAV) replication. DIPs contain a large internal deletion in one of their eight viral RNAs (vRNA) and are, thus, defective in virus replication. Moreover, they interfere with virus replication. Using single-cell isolation and reverse transcription polymerase chain reaction, we uncovered a large between-cell heterogeneity in the DI vRNA content of infected cells, which was confirmed for DI mRNAs by single-cell RNA sequencing. A high load of intracellular DI vRNAs and DI mRNAs was found in low-productive cells, indicating their contribution to the large cell-to-cell variability in virus release. Furthermore, we show that the magnitude of host cell mRNA expression (some factors may inhibit virus replication), but not the ribosome content, may further affect the strength of single-cell virus replication. Finally, we show that the load of viral mRNAs (facilitating viral protein production) and the DI mRNA content are, independently from one another, connected with single-cell virus production. Together, these insights advance single-cell virology research toward the elucidation of the complex multi-parametric origin of the large cell-to-cell heterogeneity in virus infections.

More than efficacy revealed by single-cell analysis of antiviral therapeutics

Because many aspects of viral infection dynamics and inhibition are governed by stochastic processes, single-cell analysis should provide more information than approaches using population averaging. We have developed a microfluidic device composed of ~6000 wells, with each well containing a microstructure to capture single, infected cells replicating an enterovirus expressing a fluorescent reporter protein. We have used this system to characterize enterovirus inhibitors with distinct mechanisms of action. Single-cell analysis reveals that each class of inhibitor interferes with the viral infection cycle in a manner that can be distinguished by principal component analysis. Single-cell analysis of antiviral candidates not only reveals efficacy but also facilitates clustering of drugs with the same mechanism of action and provides some indication of the ease with which resistance will develop.

All Aboard! Enteric Viruses Travel Together

Individual virus particles have long been accepted as the infectious unit during cellular infection and host-to-host transmission. In this issue of Cell Host & Microbe, Santiana et al. (2018) uncover vesicle-cloaked rotavirus and norovirus clusters in feces of infected hosts that are more infectious than free virus particles during fecal-oral transmission.

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

Influenza virus-infected cells vary widely in their expression of viral genes and only occasionally activate innate immunity. Here, we develop a new method to assess how the genetic variation in viral populations contributes to this heterogeneity. We do this by determining the transcriptome and full-length sequences of all viral genes in single cells infected with a nominally "pure" stock of influenza virus. Most cells are infected by virions with defects, some of which increase the frequency of innate-immune activation. These immunostimulatory defects are diverse and include mutations that perturb the function of the viral polymerase protein PB1, large internal deletions in viral genes, and failure to express the virus's interferon antagonist NS1. However, immune activation remains stochastic in cells infected by virions with these defects and occasionally is triggered even by virions that express unmutated copies of all genes. Our work shows that the diverse spectrum of defects in influenza virus populations contributes to-but does not completely explain-the heterogeneity in viral gene expression and immune activation in single infected cells.IMPORTANCE Because influenza virus has a high mutation rate, many cells are infected by mutated virions. But so far, it has been impossible to fully characterize the sequence of the virion infecting any given cell, since conventional techniques such as flow cytometry and single-cell transcriptome sequencing (scRNA-seq) only detect if a protein or transcript is present, not its sequence. Here we develop a new approach that uses long-read PacBio sequencing to determine the sequences of virions infecting single cells. We show that viral genetic variation explains some but not all of the cell-to-cell variability in viral gene expression and innate immune induction. Overall, our study provides the first complete picture of how viral mutations affect the course of infection in single cells.

Uncovering Virus-Virus Interactions by Unifying Approaches and Harnessing High-Throughput Tools

Virus-host interactions have received much attention in virology. Virus-virus interactions can occur when >1 virus infects a host and can be deemed social when one virus affects the fitness of another virus, as in the well-known case of superinfection exclusion. Coinfection and subsequent social interactions can change viral pathogenicity, host range, and genetic composition, with implications for human health and viral evolution. I propose that this field can be advanced by bringing new perspectives into virology (e.g., social evolution theory) and uniting disciplinary divides within virology (classical, host-focused, and ecoevolutionary). The development of novel high-throughput tools that meld molecular and evolutionary approaches can harness viral diversity as an experimental asset to understand complex viral social interactions. A greater knowledge of virus-virus interactions will lead to the reformulation of basic concepts of virology and advances in applied virology, with new treatments that harness interactions between viruses to fight viral and bacterial infections.

HSV-1 single-cell analysis reveals the activation of anti-viral and developmental programs in distinct sub-populations

Viral infection is usually studied at the population level by averaging over millions of cells. However, infection at the single-cell level is highly heterogeneous, with most infected cells giving rise to no or few viral progeny while some cells produce thousands. Analysis of Herpes Simplex virus 1 (HSV-1) infection by population-averaged measurements has taught us a lot about the course of viral infection, but has also produced contradictory results, such as the concurrent activation and inhibition of type I interferon signaling during infection. Here, we combine live-cell imaging and single-cell RNA sequencing to characterize viral and host transcriptional heterogeneity during HSV-1 infection of primary human cells. We find extreme variability in the level of viral gene expression among individually infected cells and show that these cells cluster into transcriptionally distinct sub-populations. We find that anti-viral signaling is initiated in a rare group of abortively infected cells, while highly infected cells undergo cellular reprogramming to an embryonic-like transcriptional state. This reprogramming involves the recruitment of β-catenin to the host nucleus and viral replication compartments, and is required for late viral gene expression and progeny production. These findings uncover the transcriptional differences in cells with variable infection outcomes and shed new light on the manipulation of host pathways by HSV-1.

Unmasking cellular response of a bloom-forming alga to viral infection by resolving expression profiles at a single-cell level

Infection by large dsDNA viruses can lead to a profound alteration of host transcriptome and metabolome in order to provide essential building blocks to support the high metabolic demand for viral assembly and egress. Host response to viral infection can typically lead to diverse phenotypic outcome that include shift in host life cycle and activation of anti-viral defense response. Nevertheless, there is a major bottleneck to discern between viral hijacking strategies and host defense responses when averaging bulk population response. Here we study the interaction between Emiliania huxleyi, a bloom-forming alga, and its specific virus (EhV), an ecologically important host-virus model system in the ocean. We quantified host and virus gene expression on a single-cell resolution during the course of infection, using automatic microfluidic setup that captures individual algal cells and multiplex quantitate PCR. We revealed high heterogeneity in viral gene expression among individual cells. Simultaneous measurements of expression profiles of host and virus genes at a single-cell level allowed mapping of infected cells into newly defined infection states and allowed detection specific host response in a subpopulation of infected cell which otherwise masked by the majority of the infected population. Intriguingly, resistant cells emerged during viral infection, showed unique expression profiles of metabolic genes which can provide the basis for discerning between viral resistant and susceptible cells within heterogeneous populations in the marine environment. We propose that resolving host-virus arms race at a single-cell level will provide important mechanistic insights into viral life cycles and will uncover host defense strategies.

Almost all of our current understanding of the molecular mechanisms that govern host-pathogen interactions in the ocean is derived from experiments carried out at the population level, neglecting any heterogeneity. Here we used a single cell approach to unmask the phenotypic heterogeneity produced within infected populations of the cosmopolitan bloom-forming alga Emiliania huxleyi by its specific lytic virus. We found high variability in expression of viral genes among individual cells. This heterogeneity was used to map cells into their infection state and allowed to uncover a yet unrecognized host response. We also provide evidence that variability in host metabolic states provided a sensitive tool to decipher between susceptible and resistant cells.