Cellular Co-infection Research Articles

Cellular dynamics shape recombination frequency in coronaviruses.

Coronavirus genomes have evolutionary histories shaped extensively by recombination. Yet, how often recombination occurs at a cellular level, or the factors that regulate recombination rates, are poorly understood. Utilizing experimental co-infections with pairs of genetically distinct coronaviruses, we found that recombination is both frequent and rare during coinfection. Recombination occurred in every instance of co-infection yet resulted in relatively few recombinant RNAs. By integrating a discrete-time Susceptible-Infected-Removed (SIR) model, we found that rates of recombination are determined primarily by rates of cellular co-infection, rather than other possible barriers such as RNA compartmentalization. By staggering the order and timing of infection with each virus we also found that rates of co-infection are themselves heavily influenced by genetic and ecological mechanisms, including superinfection exclusion and the relative fitness of competing viruses. Our study highlights recombination as a potent yet regulated force: frequent enough to ensure a steady influx of genetic variation but also infrequent enough to maintain genomic integrity. As recombination is thought to be an important driver of host-switching and disease emergence, our study provides new insights into the factors that regulate coronavirus recombination and evolution more broadly.

The Number and Pattern of Viral Genomic Reassortments are not Necessarily Identifiable from Segment Trees.

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to novel progeny formed from the mixture of parental segments. Since large-scale genome rearrangements have the potential to generate new phenotypes, reassortment is important to both evolutionary biology and public health research. However, statistical inference of the pattern of reassortment events from phylogenetic data is exceptionally difficult, potentially involving inference of general graphs in which individual segment trees are embedded. In this paper, we argue that, in general, the number and pattern of reassortment events are not identifiable from segment trees alone, even with theoretically ideal data. We call this fact the fundamental problem of reassortment, which we illustrate using the concept of the "first-infection tree," a potentially counterfactual genealogy that would have been observed in the segment trees had no reassortment occurred. Further, we illustrate four additional problems that can arise logically in the inference of reassortment events and show, using simulated data, that these problems are not rare and can potentially distort our observation of reassortment even in small data sets. Finally, we discuss how existing methods can be augmented or adapted to account for not only the fundamental problem of reassortment, but also the four additional situations that can complicate the inference of reassortment.

Elevated HIV Viral Load is Associated with Higher Recombination Rate In Vivo.

HIV's exceptionally high recombination rate drives its intrahost diversification, enabling immune escape and multidrug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intrahost populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (recombination analysis via time series linkage decay or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intrahost viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (<26,800 copies/mL), we estimate a recombination rate of 1.5×10-5 events/bp/generation (95% CI: 7×10-6 to 2.9×10-5), similar to existing estimates. However, among samples with the highest viral loads (>82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intrahost viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

HIV-2 inhibits HIV-1 gene expression via two independent mechanisms during cellular co-infection.

Twenty-five years after the first report that HIV-2 infection can reduce HIV-1-associated pathogenesis in dual-infected patients, the mechanisms are still not well understood. We explored these mechanisms in cell culture and showed first that these viruses can co-infect individual cells. Under specific conditions, HIV-2 inhibits HIV-1 through two distinct mechanisms, a broad-spectrum interferon response and an HIV-1-specific inhibition conferred by the HIV-2 TAR. The former could play a prominent role in dually infected individuals, whereas the latter targets HIV-1 promoter activity through competition for HIV-1 Tat binding when the same target cell is dually infected. That mechanism suppresses HIV-1 transcription by stalling RNA polymerase II complexes at the promoter through a minimal inhibitory region within the HIV-2 TAR. This work delineates the sequence of appearance and the modus operandi of each mechanism.

Neuraminidase Activity Modulates Cellular Coinfection during Influenza A Virus Multicycle Growth.

Infection of individual cells by multiple virions plays critical roles in the replication and spread of many viruses, but mechanisms that control cellular coinfection during multicycle viral growth remain unclear. Here, we investigate virus-intrinsic factors that control cellular coinfection by influenza A virus (IAV). Using quantitative fluorescence to track the spread of virions from single infected cells, we identify the IAV surface protein neuraminidase (NA) as a key determinant of cellular coinfection. We map this effect to NA's ability to deplete viral receptors from both infected and neighboring uninfected cells. In cases in which viral infectious potential is low, genetic or pharmacological inhibition of NA increases the local spread of infection by increasing the viral load received by neighboring cells. These results identify virus-intrinsic factors that contribute to cellular multiplicity of infection and suggest that optimal levels of NA activity depend on the infectious potential of the virus in question. IMPORTANCE Influenza virus populations are comprised of particles that are mostly noninfectious or only partly infectious. As a result, multiple virions are frequently needed for influenza to infect a new cell. Despite its importance in viral spread, mechanisms that control cellular coinfection are not well established. By tracking the local spread of virions from single infected cells, we identify an important role for the viral receptor-destroying enzyme neuraminidase in modulating the degree of coinfection that occurs during multicycle virus growth. We find that decreasing neuraminidase activity facilitates viral attachment to neighboring cells and increases the infectious load that these cells receive. These results identify a genetic mechanism through which the frequency of coinfection may be tuned, with implications for virus evolution.

Modeling cellular co-infection and reassortment of bluetongue virus in Culicoides midges.

When related segmented RNA viruses co-infect a single cell, viral reassortment can occur, potentially leading to new strains with pandemic potential. One virus capable of reassortment is bluetongue virus (BTV), which causes substantial health impacts in ruminants and is transmitted via Culicoides midges. Because midges can become co-infected by feeding on multiple different host species and remain infected for their entire life span, there is a high potential for reassortment to occur. Once a midge is co-infected, additional barriers must be crossed for a reassortant virus to emerge, such as cellular co-infection and dissemination of reassortant viruses to the salivary glands. We developed three mathematical models of within-midge BTV dynamics of increasing complexity, allowing us to explore the conditions leading to the emergence of reassortant viruses. In confronting the simplest model with published data, we estimate that the average life span of a bluetongue virion in the midge midgut is about 6 h, a key determinant of establishing a successful infection. Examination of the full model, which permits cellular co-infection and reassortment, shows that small differences in fitness of the two infecting strains can have a large impact on the frequency with which reassortant virions are observed. This is consistent with experimental co-infection studies with BTV strains with different relative fitnesses that did not produce reassortant progeny. Our models also highlight several gaps in existing data that would allow us to elucidate these dynamics in more detail, in particular the times it takes the virus to disseminate to different tissues, and measurements of viral load and reassortant frequency at different temperatures.

Beneficial effects of cellular coinfection resolve inefficiency in influenza A virus transcription.

For diverse viruses, cellular infection with single vs. multiple virions can yield distinct biological outcomes. We previously found that influenza A/guinea fowl/Hong Kong/WF10/99 (H9N2) virus (GFHK99) displays a particularly high reliance on multiple infection in mammalian cells. Here, we sought to uncover the viral processes underlying this phenotype. We found that the need for multiple infection maps to amino acid 26K of the viral PA protein. PA 26K suppresses endonuclease activity and viral transcription, specifically within cells infected at low multiplicity. In the context of the higher functioning PA 26E, inhibition of PA using baloxavir acid augments reliance on multiple infection. Together, these data suggest a model in which sub-optimal activity of the GFHK99 endonuclease results in inefficient priming of viral transcription, an insufficiency which can be overcome with the introduction of additional viral ribonucleoprotein templates to the cell. More broadly, the finding that deficiency in a core viral function is ameliorated through multiple infection suggests that the fitness effects of many viral mutations are likely to be modulated by multiplicity of infection, such that the shape of fitness landscapes varies with viral densities.

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 the 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.

Spatially Segregated Transmission of Co-Occluded Baculoviruses Limits Virus-Virus Interactions Mediated by Cellular Coinfection during Primary Infection.

The occlusion bodies (OBs) of certain alphabaculoviruses are polyhedrin-rich structures that mediate the collective transmission of tens of viral particles to the same insect host. In addition, in multiple nucleopolyhedroviruses, occlusion-derived virions (ODVs) form nucleocapsid aggregates that are delivered to the same host cell. It has been suggested that, by favoring coinfection, this transmission mode promotes evolutionarily stable interactions between different baculovirus variants. To quantify the joint transmission of different variants, we obtained OBs from cells coinfected with two viral constructs, each encoding a different fluorescent reporter, and used them for inoculating Spodoptera exigua larvae. The microscopy analysis of midguts revealed that the two reporter genes were typically segregated into different infection foci, suggesting that ODVs show limited ability to promote the co-transmission of different virus variants to the same host cell. However, a polyhedrin-deficient mutant underwent inter-host transmission by exploiting the OBs of a fully functional virus and re-acquired the lost gene through recombination, demonstrating cellular coinfection. Our results suggest that viral spatial segregation during transmission and primary infection limits interactions between different baculovirus variants, but that these interactions still occur within the cells of infected insects later in infection.

Generated Randomly and Selected Functionally? The Nature of Enterovirus Recombination.

Genetic recombination in RNA viruses is an important evolutionary mechanism. It contributes to population diversity, host/tissue adaptation, and compromises vaccine efficacy. Both the molecular mechanism and initial products of recombination are relatively poorly understood. We used an established poliovirus-based in vitro recombination assay to investigate the roles of sequence identity and RNA structure, implicated or inferred from an analysis of circulating recombinant viruses, in the process. In addition, we used next-generation sequencing to investigate the early products of recombination after cellular coinfection with different poliovirus serotypes. In independent studies, we find no evidence for a role for RNA identity or structure in determining recombination junctions location. Instead, genome function and fitness are of greater importance in determining the identity of recombinant progeny. These studies provide further insights into this important evolutionary mechanism and emphasize the critical nature of the selection process on a mixed virus population.

The Social Life of Viruses.

Despite their simplicity, viruses exhibit certain types of social interactions. Situations in which a given virus achieves higher fitness in combination with other members of the viral population have been described at the level of transmission, replication, suppression of host immune responses, and host killing, enabling the evolution of viral cooperation. Although cellular coinfection with multiple viral particles is the typical playground for these interactions, cooperation between viruses infecting different cells is also established through cellular and viral-encoded communication systems. In general, the stability of cooperation is compromised by cheater genotypes, as best exemplified by defective interfering particles. As predicted by social evolution theory, cheater invasion can be avoided when cooperators interact preferentially with other cooperators, a situation that is promoted in spatially structured populations. Processes such as transmission bottlenecks, organ compartmentalization, localized spread of infection foci, superinfection exclusion, and even discrete intracellular replication centers promote multilevel spatial structuring in viruses.

Fitness Estimation for Viral Variants in the Context of Cellular Coinfection.

Animal models are frequently used to characterize the within-host dynamics of emerging zoonotic viruses. More recent studies have also deep-sequenced longitudinal viral samples originating from experimental challenges to gain a better understanding of how these viruses may evolve in vivo and between transmission events. These studies have often identified nucleotide variants that can replicate more efficiently within hosts and also transmit more effectively between hosts. Quantifying the degree to which a mutation impacts viral fitness within a host can improve identification of variants that are of particular epidemiological concern and our ability to anticipate viral adaptation at the population level. While methods have been developed to quantify the fitness effects of mutations using observed changes in allele frequencies over the course of a host’s infection, none of the existing methods account for the possibility of cellular coinfection. Here, we develop mathematical models to project variant allele frequency changes in the context of cellular coinfection and, further, integrate these models with statistical inference approaches to demonstrate how variant fitness can be estimated alongside cellular multiplicity of infection. We apply our approaches to empirical longitudinally sampled H5N1 sequence data from ferrets. Our results indicate that previous studies may have significantly underestimated the within-host fitness advantage of viral variants. These findings underscore the importance of considering the process of cellular coinfection when studying within-host viral evolutionary dynamics.

Harmonization of Protocols for Multi-Species Organoid Platforms to Study the Intestinal Biology of Toxoplasma gondii and Other Protozoan Infections.

The small intestinal epithelium is the primary route of infection for many protozoan parasites. Understanding the mechanisms of infection, however, has been hindered due to the lack of appropriate models that recapitulate the complexity of the intestinal epithelium. Here, we describe an in vitro platform using stem cell-derived intestinal organoids established for four species that are important hosts of Apicomplexa and other protozoa in a zoonotic context: human, mouse, pig and chicken. The focus was set to create organoid-derived monolayers (ODMs) using the transwell system amenable for infection studies, and we provide straightforward guidelines for their generation and differentiation from organ-derived intestinal crypts. To this end, we reduced medium variations to an absolute minimum, allowing generation and differentiation of three-dimensional organoids for all four species and the subsequent generation of ODMs. Quantitative RT-PCR, immunolabeling with antibodies against marker proteins as well as transepithelial-electrical resistance (TEER) measurements were used to characterize ODM’s integrity and functional state. These experiments show an overall uniform generation of monolayers suitable for Toxoplasma gondii infection, although robustness in terms of generation of stable TEER levels and cell differentiation status varies from species to species. Murine duodenal ODMs were then infected with T. gondii and/or Giardia duodenalis, two parasites that temporarily co-inhabit the intestinal niche but have not been studied previously in cellular co-infection models. T. gondii alone did not alter TEER values, integrity and transcriptional abundance of tight junction components. In contrast, in G. duodenalis-infected ODMs all these parameters were altered and T. gondii had no apparent influence on the G. duodenalis-triggered phenotype. In conclusion, we provide robust protocols for the generation, differentiation and characterization of intestinal organoids and ODMs from four species. We show their applications for comparative studies on parasite-host interactions during the early phase of a T. gondii infection but also its use for co-infections with other relevant intestinal protozoans.

Drivers of within-host genetic diversity in acute infections of viruses.

Genetic diversity is the fuel of evolution and facilitates adaptation to novel environments. However, our understanding of what drives differences in the genetic diversity during the early stages of viral infection is somewhat limited. Here, we use ultra-deep sequencing to interrogate 43 clinical samples taken from early infections of the human-infecting viruses HIV, RSV and CMV. Hundreds to thousands of virus templates were sequenced per sample, allowing us to reveal dramatic differences in within-host genetic diversity among virus populations. We found that increased diversity was mostly driven by presence of multiple divergent genotypes in HIV and CMV samples, which we suggest reflect multiple transmitted/founder viruses. Conversely, we detected an abundance of low frequency hyper-edited genomes in RSV samples, presumably reflecting defective virus genomes (DVGs). We suggest that RSV is characterized by higher levels of cellular co-infection, which allow for complementation and hence elevated levels of DVGs.

Non-SARS-CoV-2 genome sequences identified in clinical samples from COVID-19 infected patients: Evidence for co-infections.

BackgroundIn December 2019, an ongoing outbreak of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/ 2019-nCoV) infection was initially reported in Wuhan, Hubei Province, China. Early in 2020, the World Health Organization (WHO) announced a new name for the 2019-nCoV-caused disease: coronavirus disease 2019 (COVID-19) and declared COVID-19 to be a Public Health Emergency of International Concern (PHEIC). Cellular co-infection is a critical determinant of viral fitness and infection outcomes and plays a crucial role in shaping the host immune response to infections.MethodsIn this study, 68 public next-generation sequencing data from SARS-CoV-2 infected patients were retrieved from the NCBI Sequence Read Archive database using SRA-Toolkit. Data screening was performed using an alignment-free method based on k-mer mapping and extension, fastv. Taxonomic classification was performed using Kraken 2 on all reads containing one or more virus sequences other than SARS-CoV-2.ResultsSARS-CoV-2 was identified in all except three patients. Influenza type A (H7N9) virus, human immunodeficiency virus, rhabdovirus, human metapneumovirus, Human adenovirus, Human herpesvirus 1, coronavirus NL63, parvovirus, simian virus 40, and hepatitis virus genomes sequences were detected in SARS-CoV-2 infected patients. Besides, a very diverse group of bacterial populations were observed in the samples.

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.

Within-host infectious disease models accommodating cellular coinfection, with an application to influenza.

Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (e.g. cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological ‘macroparasite’ models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as ‘hosts’ and viral particles as ‘macroparasites’, and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cell’s multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, and demonstrate using model selection approaches that they have the ability to outperform traditional within-host viral dynamic models. Important in vivo quantities such as the mean multiplicity of cellular infection and time-evolving reassortant frequencies can also be quantified in a straightforward manner once these macroparasite models have been parameterized. The within-host model structure we develop here provides a mathematical way forward to address questions related to the roles of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

Worldwide circulation of HSV-2\u2009\xd7\u2009HSV-1 recombinant strains

Homo sapiens harbor two distinct, medically significant species of simplexviruses, herpes simplex virus (HSV)-1 and HSV-2, with estimated divergence 6–8 million years ago (MYA). Unexpectedly, we found that circulating HSV-2 strains can contain HSV-1 DNA segments in three distinct genes. Using over 150 genital swabs from North and South America and Africa, we detected recombinants worldwide. Common, widely distributed gene UL39 genotypes are parsimoniously explained by an initial >457 basepair (bp) HSV-1 × HSV-2 crossover followed by back-recombination to HSV-2. Blocks of >244 and >539 bp of HSV-1 DNA within genes UL29 and UL30, respectively, have reached near fixation, with a minority of strains retaining sequences we posit as ancestral HSV-2. Our data add to previous in vitro and animal work, implying that in vivo cellular co-infection with HSV-1 and HSV-2 yields viable interspecies recombinants in the natural human host.

Repeatable Population Dynamics among Vesicular Stomatitis Virus Lineages Evolved under High Co-infection.

Parasites and hosts can experience oscillatory cycles, where the densities of these interacting species dynamically fluctuate through time. Viruses with different replication strategies can also interact to produce cyclical dynamics. Frequent cellular co-infection can select for defective-interfering particles (DIPs): “cheater” viruses with shortened genomes that interfere with intracellular replication of full-length (ordinary) viruses. DIPs are positively selected when rare because they out-replicate ordinary viruses during co-infection, but DIPs are negatively selected when common because ordinary viruses become unavailable for intracellular exploitation via cheating. Here, we tested whether oscillatory dynamics of ordinary viruses were similar across independently evolved populations of vesicular stomatitis virus (VSV). Results showed identical cyclical dynamics across populations in the first 10 experimental passages, which transitioned to repeatable dampened oscillations by passage 20. Genomic analyses revealed parallel molecular substitutions across populations, particularly novel mutations that became dominant by passage 10. Our study showed that oscillatory dynamics and molecular evolution of interacting viruses were highly repeatable in VSV populations passaged under frequent co-infection. Furthermore, our data suggested that frequent co-infection with DIPs caused lowered performance of full-length viruses, by reducing their population densities by orders of magnitude compared to reproduction of ordinary viruses during strictly clonal infections.

A viral protein mediates superinfection exclusion at the whole-organism level but is not required for exclusion at the cellular level.

Superinfection exclusion (SIE), the ability of an established virus infection to interfere with a secondary infection by the same or a closely related virus, has been described for different viruses, including important pathogens of humans, animals, and plants. Citrus tristeza virus (CTV), a positive-sense RNA virus, represents a valuable model system for studying SIE due to the existence of several phylogenetically distinct strains. Furthermore, CTV allows SIE to be examined at the whole-organism level. Previously, we demonstrated that SIE by CTV is a virus-controlled function that requires the viral protein p33. In this study, we show that p33 mediates SIE at the whole-organism level, while it is not required for exclusion at the cellular level. Primary infection of a host with a fluorescent protein-tagged CTV variant lacking p33 did not interfere with the establishment of a secondary infection by the same virus labeled with a different fluorescent protein. However, cellular coinfection by both viruses was rare. The obtained observations, along with estimates of the cellular multiplicity of infection (MOI) and MOI model selection, suggested that low levels of cellular coinfection appear to be best explained by exclusion at the cellular level. Based on these results, we propose that SIE by CTV is operated at two levels--the cellular and the whole-organism levels--by two distinct mechanisms that could function independently. This novel aspect of viral SIE highlights the intriguing complexity of this phenomenon, further understanding of which may open up new avenues to manage virus diseases. Many viruses exhibit superinfection exclusion (SIE), the ability of an established virus infection to interfere with a secondary infection by related viruses. SIE plays an important role in the pathogenesis and evolution of virus populations. The observations described here suggest that SIE could be controlled independently at different levels of the host: the whole-organism level or the level of individual cells. The p33 protein of citrus tristeza virus (CTV), an RNA virus, was shown to mediate SIE at the whole-organism level, while it appeared not to be required for exclusion at the cellular level. SIE by CTV is, therefore, highly complex and appears to use mechanisms different from those proposed for other viruses. A better understanding of this phenomenon may lead to the development of new strategies for controlling viral diseases in human populations and agroecosystems.