Get Our e-AlertsSubmit Manuscript
BioDesign Research / 2022 / Article

Review Article | Open Access

Volume 2022 |Article ID 9819272 |

Ernesto Segredo-Otero, Rafael Sanjuán, "Cooperative Virus-Virus Interactions: An Evolutionary Perspective", BioDesign Research, vol. 2022, Article ID 9819272, 13 pages, 2022.

Cooperative Virus-Virus Interactions: An Evolutionary Perspective

Received16 Feb 2022
Accepted21 May 2022
Published03 Oct 2022


Despite extensive evidence of virus-virus interactions, not much is known about their biological significance. Importantly, virus-virus interactions could have evolved as a form of cooperation or simply be a by-product of other processes. Here, we review and discuss different types of virus-virus interactions from the point of view of social evolution, which provides a well-established framework for interpreting the fitness costs and benefits of such traits. We also classify interactions according to their mechanisms of action and speculate on their evolutionary implications. As in any other biological system, the evolutionary stability of viral cooperation critically requires cheaters to be excluded from cooperative interactions. We discuss how cheater viruses exploit cooperative traits and how viral populations are able to counteract this maladaptive process.

1. Introduction

Viruses exhibit a wide range of direct and host-mediated interactions, some of which have been known for decades. Most of these interactions take place in cells coinfected with different viral variants or species. For instance, genetic complementation occurs when two or more viral mutants carrying deleterious mutations at different loci share their gene products to compensate for these defects, thus restoring normal functions [1, 2]. Another well-known example is pseudotyping, which takes place when two different viruses coinfect a cell and produce virions carrying the genome from one virus but some structural proteins from the other virus [37]. Two additional examples are provided by embedded viruses, which are retroviruses that fully integrate their genome into the genome of another virus [810], and by heterologous transactivation, which occurs when a virus expresses transcription factors that activate promoters of another virus [11, 12]. Negative interactions are also common among coinfecting viruses. In addition to the obvious phenomenon of direct competition for host resources, viruses exhibit mechanisms to inhibit foreign infections, with superinfection exclusion (SIE), a mechanism by which a virus that is infecting a host is able to block other infections, being particularly important [1317]. Some plant viruses are also able to promote host-wide protection, a process called cross-protection [18, 19].

Viruses can also establish more indirect interactions, which are determined by the characteristics of the environment or the host, particularly the immune system. There are many examples of environmental and immunological interactions between different viruses, some of the most important being altering host susceptibility, modifying or suppressing interferon (IFN) response, or altering immune cell activation [20]. For instance, human immunodeficiency virus (HIV) is able to increase human cytomegalovirus (HCMV) replication in various tissues as a result of lymphocyte activation [21], and humans infected with herpes simplex virus (HSV) are more susceptible to HIV infections and more contagious due to an increased expression of the receptor CCR5 [22, 23]. Innate immunity can also promote negative interaction between viruses [24, 25]. Cooperative and competitive interactions mediated by cross-reactive innate immunity appear to be particularly frequent among respiratory viruses [26].

Most of these well-known interactions involve viruses from different species. Cases of embedding, transactivation, or pseudotyping or the interactions between HIV and HSV may occur as a by-product of a normal process in the infection cycle of the other virus. Less attention was traditionally paid to cases of interactions between viruses of the same species (with the exception of genetic complementation), in which the ability of a viral particle to achieve a successful infection is promoted or hampered by the presence of other viral particles. However, several research lines have emerged in recent years showing this kind of viral interactions in various processes including evasion of host immunity [24] and regulation of virulence [27]. Inclusive fitness theory is a well-established theoretical framework for studying these interactions, which was initially developed to explain the evolution of altruism in higher organisms but allows viral interactions to be formally analyzed in terms of fitness costs and benefits. For a trait to be considered social, its evolution should be determined, at least partially, by the effect it produces on individuals different from the actor.

2. Viral Coinfection Mechanisms That Facilitate Interactions

The most common scenario for virus-virus of interactions takes place when multiple infectious particles are present in the same host cell, that is, when there is a high multiplicity of infection (MOI), defined as the number of viral genomes that initiates an infection. Animal viruses typically produce a large number of infectious particles per infected cell, usually ranging from 100 to 1000 [2830]. In the simplest form of viral spread, these particles diffuse in a viscous medium [31] until they reach a neighbor cell, producing infection foci that create a high local MOI. However, the amount of genomes that are actually transmitted from cell to cell is variable and depends, among other factors, on adsorption efficiency. Bacteriophages can exhibit extremely high adsorption efficiencies [32, 33] that, together with their environmental ubiquity, should promote coinfection and, in turn, select for mechanisms that regulate coinfection levels.

A more specialized form of viral spread is cell-to-cell transmission, which should also favor coinfection. Plant viruses can achieve elevated MOIs by delivering multiple viral particles via plasmodesmata [34, 35] (Figure 1). However, the amount of genomes that are transmitted from cell to cell is variable [36, 37]. Animal viruses also exhibit several mechanisms for cell-to-cell transmission such as the formation of actin tails [38], the exploitation of structures like filopodia [39], and tunneling nanotubes [40], as well as the induction of syncytia [4144] or cell synapses [45, 46].

High MOIs can also be achieved when viral spread occurs through collective infectious units (CIUs, Figure 1). This term describes a wide range of virus-promoted structures that allow cotransmission and delivery of multiple viral genomes in a single host cell [47]. CIUs are found in many different types of viruses, although they have been best characterized in animal viruses. For example, some viruses can form “polyploid” virions containing more than one genome copy [4852]. CIUs can also be formed when virions aggregate in the extracellular milieu, as has been shown, for instance, for vesicular stomatitis virus (VSV) in saliva [53, 54] or HIV in semen [55, 56]. Occlusion bodies (OBs) of baculoviruses are composed of polyhedrin protein crystals harboring tens of nucleocapsids [57, 58]. A well-described type of CIUs is extracellular vesicles containing multiple viral particles, which have been described in noroviruses [59]; picornaviruses such as coxsackieviruses [60], polioviruses [61], and hepatitis A virus (HAV) [62]; rotaviruses [59]; and marseilleviruses [63]. Despite the great diversity of structures involved in CIU formation, a common theme is the simultaneous delivery of multiple genomes to the same host or cell. CIU-mediated elevation of MOI can be advantageous in different ways, since it could promote cooperative interactions between potentially identical viral genomes (homotypic) or between different genetic variants of a virus (heterotypic).

2.1. “Mass” Effects

Everything else being equal, if virions infect a single cell instead of different cells, there should be a direct -fold reduction in the amount of viral progeny produced per cell. For mechanisms promoting coinfection to be beneficial in terms of fitness, they must therefore compensate for this cost by increasing the viral progeny per cell by at least the same factor; or promote some other fitness advantage such as faster infection or greater environmental stability (Table 1). This question has been addressed both theoretically and experimentally, and although there are several possible mechanisms that may confer an evolutionary advantage to CIUs, there is no general answer that applies to all viruses [64].

Fitness advantageVirusNormalized benefits per capitaReference

Acceleration of the infection cyclePoliovirusYes61
Influenza A virusYes (depending on the MOI and cell type)70-72
Human immunodeficiency virusNo55

Increased per-cell yieldInfluenza A virusYes (depending on the MOI and cell type)69-72
Vaccinia virusYes73
Vesicular stomatitis virusYes68

Increased infectivityInfectious bursal disease virusYes51
Human immunodeficiency virusNo55
Vaccinia virusYes73
Influenza A virusDepends on segment encapsidation70

A general feature of viruses is that there exists a positive feedback between the number of replication templates and the number of virally encoded proteins, since viral genomes code for replication-promoting proteins [65]. Consequently, there should be a disproportionate increase in short-term replication efficiency as the copy number of the viral founder genomes within a cell increases. Several lines of evidence support this idea, such as the fact that increased MOI leads to a direct increase in viral gene expression levels in herpesviruses [66]. In polioviruses, phosphatidylserine vesicles, which promote the en bloc transmission of multiple virions, increase the rate of viral replication [61], and a similar result was described for noroviruses and rotaviruses [59]. Marseillevirus vesicles have also been shown to accelerate the infection cycle [63], but in this case, the authors speculated that the main reason might be a difference in the mechanism of entry, rather than an effect of coinfection per se.

In addition to simply accelerating the release of viral progeny in infected cells with a high MOI, cooperative replication may increase the viral yield per cell. This could take place if viral progeny production is not limited by cellular resource availability, but by the time an infected cell is productive since viral entry (Figure 2). Apoptosis is triggered in infected cells upon recognition of pathogen-associated molecular patterns such as, for instance, double-stranded RNA [67]. This antiviral response imposes a time window for viruses to produce and release progeny. Increased per-cell yield has been demonstrated for VSV [68], influenza A virus (IAV) [6972], infectious bursal disease virus (IBDV) [51], and vaccinia virus [73].

Finally, coinfection could also reduce the fraction of abortive infections. When a single virion initiates infection, nucleic acid or protein degradation (spontaneous or driven by cellular mechanisms) may take place before the key steps of viral gene expression or replication can occur. This stochasticity results in abortive infections and contributes to explain why most viral particles fail to yield productive infections (Figure 2). The ratio of productive infections per particle has been shown to increase with the MOI in vaccinia virus [73] and with cell-to-cell transmission in HIV-1 [74], albeit the latter could be due to the use of a different transmission pathway. Polyploid virions of IBDV also show enhanced infectivity [51], but since this is a segmented virus, such increase could be explained by a higher likelihood of transmission of each genome segment.

Despite the fitness benefit that cotransmission mechanisms may provide (Figure 2), the critical question is whether these advantages increase the per-capita yield of viral genomes, compared to single infections. As argued above, individually infected cells have the potential to yield times more viral progeny than a single cell coinfected with particles. Therefore, viruses in coinfected cells should overcome this -fold cost. To our knowledge, this has only been demonstrated in VSV [68] and vaccinia virus [73]. Coinfection could increase the per-cell viral yield, accelerate the replication cycle [61], or increase infectivity by a factor greater than . In [59], the authors compared infections with equivalent numbers of free virions and vesicle-cloaked virions, but as they performed in vivo infections, it is not easy to determine which cellular-level benefits these vesicles afforded.

There are also connections between the benefits of coinfection and the immune response. IFN is released from infected cells and activates an antiviral state in neighboring cells [75, 76], but the onset of this process takes several hours, at least in cell cultures. Some viruses present specific antiapoptotic proteins that block IFN-activated apoptotic pathways [77, 78], whereas others such as VSV block IFN production [79]. In this context, an increased infection rate or per-cell yield may be critical for infection progression. The fitness advantage of VSV virion aggregates has been shown to correlate with the ability of host cells to mount an effective antiviral innate immune response [68], and similar results have been obtained for IAV [71, 72].

2.2. Diversity-Based Interactions

Viruses are the genetic systems exhibiting the highest mutation rates, particularly RNA viruses [80]. This, together with other mechanisms such as recombination, creates highly diverse and rapidly evolving populations at the cost of frequently suffering detrimental or lethal mutations [81]. Coinfection has been speculated to play an important role in determining viral diversity. Genetic complementation among two coinfecting genomes carrying different deleterious mutations may rescue both and allow them to perform successful infections equivalent to a nonmutated virus (Figure 3). However, buffering deleterious effects implies that such mutations will tend to increase their population frequency. Deterministic [82] and stochastic [83] simulations have shown that genetic complementation transiently alleviates the impact of deleterious mutations but does not change mean population fitness over the long term. This is because, at equilibrium, complementation will reduce the average fitness effect of mutations but will similarly increase the frequency of these mutations in the population.

On the other hand, we can speculate that genetic complementation could promote evolvability by increasing cryptic genetic variation. In a context of high MOI and CIU-mediated transmission, genetic complementation might allow deleterious mutations to be maintained in the population and, potentially, some of these mutations could become advantageous in a different context, such as, for instance, in a new host. This could be the case described in [84], where the authors found Asian-type IAV variants in pigs, suggesting that these variants were deleterious but remained at a certain frequency in the original host, potentially due to complementation, and were subsequently amplified in the alternate host where they provided a fitness advantage to the virus.

A potential direct benefit of transmitting genetically diverse viral populations among hosts could take place when viruses must infect different cell types. An often successful strategy in heterogeneous environments is a generalist phenotype that trades off fitness compared to specialists in every specific environment but increases overall performance [85]. We hypothesize that collective viral dispersal could alleviate such trade-offs by allowing different specialist variants to be jointly transmitted (Figure 3). In baculoviruses, OBs carry multiple infectious particles and are essential for host-to-host transmission, as evidenced by the fact that variants carrying a deletion of the polyhedrin gene are unable to infect new hosts. However, OBs containing a mixture of wild-type and polyhedrin-defective variants are efficiently transmitted and can generate more productive and severe infections than genetically homogeneous OBs [86]. This observation suggests that polyhedrin-defective mutants are better adapted to intrahost dissemination, whereas nonmutated genomes provide interhost transmissibility. Both variants could benefit from this interaction, since the enhanced severity of the infection caused by the polyhedrin-defective mutant could potentially favor transmission. Thus, collective viral transmission via OBs could promote a stable coexistence between complementary specialists. The conditions required for such coexistence include functional complementary, synergistic advantages, and a positive assortment of specialists [87]. Further experiments are required to analyze whether this type of interactions in baculoviruses and potentially other viruses exhibits negative frequency-dependent selection, which is another process promoting stable coexistence.

In a similar vein, it has recently been speculated that high-MOI regimes might be at the origin of segmentation in viruses [88], as each segment functions as a defective genome incapable of performing a successful infection alone. For a set of genomes that are constantly cotransmitted, the selection pressure to keep the entire genome as a unit should be reduced, which may lead to some of them retaining only a subset of all functional genes. Eventually, these genomes might experience long deletions and become segments of the original genome. This was experimentally addressed by passaging foot-and-mouth disease virus (FMDV) at high MOIs for many viral generations, which resulted in the emergence of different mutants that could reciprocally complement their genetic defects [89].

3. Interactions Mediated by Sequential Infections

Superinfection occurs when a given host or cell is sequentially infected with the same virus or different viruses. As mentioned in Introduction, many viruses possess mechanism to avoid superinfection [1317]. Intuitively, SIE can be thought of as a trait that helps viruses avoid competition for cellular resources from other incoming viruses. However, it has also been suggested that SIE may function as a cooperative trait. In vaccinia virus, repulsion of virions from the surface of already infected cells was shown to accelerate the propagation of the infection by helping the excluded virions to reach uninfected susceptible cells in the neighborhood [90]. In other cases, SIE may also simply be a passive process, that is, a by-product of infection progression, as the case of Sonchus yellow web nucleorhabdovirus indicates [91].

A seemingly cooperative interaction mediated by sequential infection was demonstrated in bacteriophages. Some phages inhibit the bacterial CRISPR system using anti-CRISPR proteins (Acr), but Acr function is often not sufficient to ensure successful infection, as the CRISPR system is not fully blocked. Still, infection with Acr-encoding phages can induce a transient “immunosuppressed” state in the bacterial cell, in which CRISPR function is partially disabled. As a result, a second Acr phage infecting the same cell may encounter more permissive conditions for infection [92, 93]. This might not be considered superinfection, since primary infections are unsuccessful. In fact, it has been suggested that the phages performing the first abortive infection function as altruistic cooperators.

4. Interactions Established between Viruses Infecting Different Cells

Recent work has revealed virus-virus interactions mediated by signals released from infected cells, which are sensed by other infected cells and influence infection outcome. The VSV matrix protein (M protein) inhibits overall host gene expression by binding to nuclear pores and blocking the export of mRNA from the nucleus to the cytoplasm [94]. Such blockade is potentially costly for the virus, for instance, by inducing premature apoptosis, but has the obvious benefit of preventing an antiviral innate immune response. However, this benefit is perceived not only by viruses in the infected cell (autocrine effects) but also by viruses infecting neighbor cells (paracrine effects). Thus, IFN blockade can be considered as a social trait, since it modifies the fitness of other members of the viral population. Importantly, a mutant virus that does not block IFN production can take advantage from the blockade exerted by the normal virus without paying the associated costs. Conversely, the IFN-blocking virus could be suppressed by the presence of an IFN-inducing mutant in the neighborhood. Such costly cooperation has been modeled in the classical evolutionary literature using Hamilton’s rule, which states that the cooperative trait will be favored by selection depending on the direct costs/benefits experienced by the actor, the indirect benefits experienced by other members of the population, and the genetic relatedness between the interacting individuals (Box 1) [9597]. It was shown that IFN blockade in VSV obeys these principles and, specifically, that the fitness benefit of this trait correlates with genetic relatedness which, in viruses, depends essentially on the spatial structure of the population [24]. In structured infections where VSV virus spread took place in foci, the wild-type IFN blocking virus was vastly superior to a mutant defective for this trait, whereas this advantage was lost in unstructured infections in which the two virus variants were spatially mixed.

Intercellular virus-virus interactions have also been demonstrated in bacteriophages. In recent years, a regulatory system similar to quorum sensing, called Arbitrium, has been described in some temperate Bacillus phages such as phi3T or SPBeta. Arbitrium controls lysis versus lysogeny decisions, as well lysogen reactivation [98]. The system comprises at least three genes: a signal peptide (aimP), a receptor for that peptide that functions as a transcription factor (aimR), and a regulator (aimX) that inhibits the expression of prolysogenic genes. When the fraction of infected bacterial hosts is low, there is little signal peptide in the medium, since the peptide is produced by lysogens. In this scenario, aimR promotes the expression of aimX, which blocks lysogeny genes. This leads to an acute infection phase, with abundant lysis, therefore promoting the accumulation of infectious particles in the medium and, consequently, increasing the fraction of infected hosts. As the density of lysogens increases, so does the concentration of the signal peptide in the medium, which blocks aimR, promoting lysogeny. In this way, phages display a communication system to regulate virulence and promote prudent exploitation of the host (Figure 4). However, it is possible for more rapacious variants to emerge and outcompete prudent phages by infecting and lysing as many hosts as possible, leading to the dilemma of parasite prudence, which is actually a particular case of a more general dilemma often referred to as yield versus rate. Exploiting resources quickly confers a short-term advantage and prevents others from using them but usually reduces efficiency over the long term by exhausting resources [99, 100]. Further investigation is required to analyze what kind of social games is promoted by the Arbitrium system.

Depolymerases may also mediate intercellular virus-virus interactions in phages. These enzymes are typically located on bacteriophage tails and promote infection by disrupting bacterial exopolysaccharides and exposing phage receptors [101105]. Diffusible depolymerases that are dissociated from tails or remain associated to broken tails could function as classical public goods since they can potentially benefit many members of the local phage population, regardless the specific phage that produced them [104]. It has been suggested that certain synergistic interactions between different phage species at the level of host entry might be mediated by depolymerases [105], although the experimental support for this type of interaction is scarce (Figure 4).

5. Viral Cheating

Just as cooperation is widespread in nature, so are cheaters, defined as individuals that reap the benefits of cooperation without contributing to such benefits. If cooperation entails a cost (for instance, producing a capsid), cheaters may experience higher fitness than cooperators because they do not pay such a cost, potentially jeopardizing the maintenance of cooperative traits in the population (the so-called tragedy of the commons). Box 2 illustrates some well-studied cooperative interactions from a game theory point of view. A classical scenario is the Prisoner’s dilemma (PD), in which (i) cooperative traits bear a cost for the actor () and a greater benefit for the receptor (); (ii) the payoff of interactions between cooperators is the sum of both terms ; (iii) the payoff of cheaters interacting with cooperators is simply the positive effect they receive from cooperators (iv) the payoff of cooperators interacting with cheaters equals the cost of cooperating ; and (v) the payoff of cheaters interacting with cheaters is zero since there is no interaction . Thus, the fitness of cooperators is lower than that of cheaters regardless of the probability of encountering a cooperator or a cheater and . The overall fitness difference between cooperators and cheaters is , which means that cooperation should always go extinct despite the fact that mean population fitness would be maximal if all individuals were cooperators (Box 3).

Viruses and genetic systems in general have to accomplish a balance between two key processes, namely, gene expression and replication. During coinfections, a PD social game may occur if the gene products of one virus can be exploited by the other virus [106, 107]. If this is the case, a virus variant that reduces transcription and prioritizes replication may be capable of producing progeny genomes faster than a counterpart that invests more in transcription. However, a cell coinfected with only such cheaters would produce little progeny [81]. PD is fulfilled in this scenario since infections with only cooperators are the fittest, but coinfections between cooperators and cheaters are always dominated by cheaters.

A different scenario arises when the fitness payoffs of the interaction between cheaters (due to an extremely low propensity for transcription) decrease so much that it is even lower than those of single infections (no interaction). Here, a fundamental modification of the payoff matrix occurs, since now, the interaction between cheaters is no longer neutral . A new social game called Snowdrift (SD) emerges, in which the optimal strategy is no longer to always be a cheater [108]. Since , but , selection is frequency-dependent and a stable equilibrium between cooperators and cheaters is possible (Box 4). This model describes a very well-known type of cheaters, namely, defective interfering particles (DIPs). DIPs are viruses that have lost a large fraction of the viral genome, such that they are unable to complete an infectious cycle except if a normal or “helper” virus is present in the same cell [109111]. It has been shown that a nonlinear trade-off between replication and transcription can also generate a SD game between cheater and cooperator viruses [112].

Generally speaking, cooperators can outcompete cheaters if they are more likely to interact with other cooperators than cheaters are (Box 1). Hamilton’s rule states that cooperative traits will be favored by selection if , where is the genetic relatedness between interactors for the relevant trait in question, that is, the probability that the benefits of cooperation are received by individuals who share the cooperative trait [9597]. In the absence of complex phenotype recognition mechanisms such as memory and learning, viruses have to rely on spatial population structure as the main process that promotes genetic relatedness and thus prevents the spread of cheaters.

Viruses exhibit spatial population structure at different levels, ranging from subcellular replication centers to tissues, organs, hosts, or host populations (Figure 5). For instance, infections in solid tissues usually progresses as foci founded by one or a few particles. This creates a region in which each cell is infected by genetically related viruses and where coinfection is likely due to the high local MOI (Figure 5). Concerning CIUs, some allow greater levels of genetic relatedness than others. For instance, extracellular vesicles or occlusion bodies promote the cotransmission of genomes originating from the same infected cell, limiting interactions to “sibling” genomes. Direct cell-to-cell transmission also preserves genetic relatedness in a similar way. In contrast, other CIUs such as virion aggregates generate mixtures of virions from different cells. Increased genetic relatedness should promote the evolution of cooperation between similar variants, but it may also have a negative effect on diversity-driven cooperation.

6. Conclusions

The evolution of cooperation is a widely explored topic in the evolutionary biology literature [113]. In the last two decades, the attention has focused on the social interactions displayed by microorganisms, mainly bacteria but more recently also viruses [114, 115]. Cooperative interactions have been shown to have an important effect on viral evolution, such as, for instance, on the evolution of innate immunity evasion [24], but also on infection outcomes in animal [86] and plant viruses [116, 117]. Moreover, the fact that DIPs are found naturally in human patients [118, 119] provides evidence that cooperative interactions take place in nature and have a practical relevance. Although still poorly explored, social evolution could also offer a new perspective on other important traits such as viral tropism and the regulation of virulence. Concerning collective viral transmission, unresolved questions remain, such as whether there is a general fitness benefit for this transmission mode, which should be associated to elevating the MOI, or whether CIUs have evolved in different viruses in response to specific selective pressures. It is noteworthy that extracellular vesicles, which are a well-studied type of CIU vehicle, are used by different viral families such as Reoviridae [59], Caliciviridae [59], Picornaviridae [60], and Marseilleviridae [63]. Further research from an evolutionary approach is required to shed light on these unresolved questions.

Conflicts of Interest

The authors declare no conflict of interest.


We thank Ivan Andreu-Moreno for helpful discussions. This work has been funded by ERC Consolidator Grant 724519—Vis-a-Vis.


  1. N. Jorba, R. Coloma, and J. Ortín, “Genetic trans-complementation establishes a new model for influenza virus RNA transcription and replication,” PLoS Pathogens, vol. 5, no. 5, article e1000462, 2009. View at: Publisher Site | Google Scholar
  2. T. Zhou, H. Zhang, T. Lai et al., “Virus-induced gene complementation reveals a transcription factor network in modulation of tomato fruit ripening,” Scientific Reports, vol. 2, no. 1, p. 836, 2012. View at: Publisher Site | Google Scholar
  3. J. Závada, “Viral pseudotypes and phenotypic mixing,” Archives of Virology, vol. 50, no. 1-2, pp. 1–15, 1976. View at: Publisher Site | Google Scholar
  4. J. L. Certo, B. F. Shook, P. D. Yin, J. T. Snider, and W. S. Hu, “Nonreciprocal pseudotyping: murine leukemia virus proteins cannot efficiently package spleen necrosis virus-based vector RNA,” Journal of Virology, vol. 72, no. 7, pp. 5408–5413, 1998. View at: Publisher Site | Google Scholar
  5. S. Funke, I. C. Schneider, S. Glaser et al., “Pseudotyping lentiviral vectors with the wild-type measles virus glycoproteins improves titer and selectivity,” Gene Therapy, vol. 16, no. 5, pp. 700–705, 2009. View at: Publisher Site | Google Scholar
  6. A. Duvergé and M. Negroni, “Pseudotyping lentiviral vectors: when the clothes make the virus,” Viruses, vol. 12, no. 11, p. 1311, 2020. View at: Publisher Site | Google Scholar
  7. Q. Wu, L. Fang, X. Wu et al., “A pseudotype baculovirus-mediated vaccine confers protective immunity against lethal challenge with H5N1 avian influenza virus in mice and chickens,” Molecular Immunology, vol. 46, no. 11-12, pp. 2210–2217, 2009. View at: Publisher Site | Google Scholar
  8. P. D. Friesen and M. S. Nissen, “Gene organization and transcription of TED, a lepidopteran retrotransposon integrated within the baculovirus genome,” Molecular and Cellular Biology, vol. 10, no. 6, pp. 3067–3077, 1990. View at: Google Scholar
  9. C. Hertig, B. E. Coupar, A. R. Gould, and D. B. Boyle, “Field and vaccine strains of fowlpox virus carry integrated sequences from the avian retrovirus, reticuloendotheliosis virus,” Virology, vol. 235, no. 2, pp. 367–376, 1997. View at: Publisher Site | Google Scholar
  10. J. Wang, J. Meers, P. B. Spradbrow, and W. F. Robinson, “Evaluation of immune effects of fowlpox vaccine strains and field isolates,” Veterinary Microbiology, vol. 116, no. 1-3, pp. 106–119, 2006. View at: Publisher Site | Google Scholar
  11. A. D. Yurochko, S. M. Huong, and E. S. Huang, “Identification of human cytomegalovirus target sequences in the human immunodeficiency virus long terminal repeat. Potential role of IE2-86 binding to sequences between -120 and -20 in promoter transactivation,” Journal of Human Virology, vol. 2, pp. 81–90, 1999. View at: Google Scholar
  12. A. H. Lee, K. J. Lee, S. Kim, and Y. C. Sung, “Transactivation of human immunodeficiency virus type 1 long terminal repeat-directed gene expression by the human foamy virus bel1 protein requires a specific DNA sequence,” Journal of Virology, vol. 66, no. 5, pp. 3236–3240, 1992. View at: Publisher Site | Google Scholar
  13. R. H. Adams and D. T. Brown, “BHK cells expressing Sindbis virus-induced homologous interference allow the translation of nonstructural genes of superinfecting virus,” Journal of Virology, vol. 54, no. 2, pp. 351–357, 1985. View at: Publisher Site | Google Scholar
  14. M. Nethe, B. Berkhout, and A. C. van der Kuyl, “Retroviral superinfection resistance,” Retrovirology, vol. 2, no. 1, p. 52, 2005. View at: Publisher Site | Google Scholar
  15. T. Schaller, N. Appel, G. Koutsoudakis et al., “Analysis of hepatitis C virus superinfection exclusion by using novel fluorochrome gene-tagged viral genomes,” Journal of Virology, vol. 81, no. 9, pp. 4591–4603, 2007. View at: Publisher Site | Google Scholar
  16. C. Dietrich and E. Maiss, “Fluorescent labelling reveals spatial separation of potyvirus populations in mixed infected Nicotiana benthamiana plants,” The Journal of General Virology, vol. 84, no. 10, pp. 2871–2876, 2003. View at: Publisher Site | Google Scholar
  17. J. Bondy-Denomy, J. Qian, E. R. Westra et al., “Prophages mediate defense against phage infection through diverse mechanisms,” The ISME Journal, vol. 10, no. 12, pp. 2854–2866, 2016. View at: Publisher Site | Google Scholar
  18. S. Folimonova, “Developing an understanding of cross-protection by Citrus tristeza virus,” Frontiers in Microbiology, vol. 4, 2013. View at: Publisher Site | Google Scholar
  19. X.-F. Zhang, S. Zhang, Q. Guo, R. Sun, T. Wei, and F. Qu, “A new mechanistic model for viral cross protection and superinfection exclusion,” Frontiers in Plant Science, vol. 9, 2018. View at: Publisher Site | Google Scholar
  20. T. DaPalma, B. P. Doonan, N. M. Trager, and L. M. Kasman, “A systematic approach to virus-virus interactions,” Virus Research, vol. 149, no. 1, pp. 1–9, 2010. View at: Publisher Site | Google Scholar
  21. A. Biancotto, S. J. Iglehart, A. Lisco et al., “Upregulation of human cytomegalovirus by HIV type 1 in human lymphoid tissue ex vivo,” AIDS Research and Human Retroviruses, vol. 24, no. 3, pp. 453–462, 2008. View at: Publisher Site | Google Scholar
  22. C. Celum, R. Levine, M. Weaver, and A. Wald, “Genital herpes and human immunodeficiency virus: double trouble,” Bulletin of the World Health Organization, vol. 82, no. 6, pp. 447–453, 2004. View at: Google Scholar
  23. J. S. Sheffield, G. D. Wendel, D. D. McIntire, and M. V. Norgard, “Effect of genital ulcer disease on HIV-1 coreceptor expression in the female genital tract,” The Journal of Infectious Diseases, vol. 196, no. 10, pp. 1509–1516, 2007. View at: Publisher Site | Google Scholar
  24. P. Domingo-Calap, E. Segredo-Otero, M. Durán-Moreno, and R. Sanjuán, “Social evolution of innate immunity evasion in a virus,” Nature Microbiology, vol. 4, no. 6, pp. 1006–1013, 2019. View at: Publisher Site | Google Scholar
  25. K. Dee, D. M. Goldfarb, J. Haney et al., “Human rhinovirus infection blocks severe acute respiratory syndrome coronavirus 2 replication within the respiratory epithelium: implications for COVID-19 epidemiology,” The Journal of Infectious Diseases, vol. 224, no. 1, pp. 31–38, 2021. View at: Publisher Site | Google Scholar
  26. S. Nickbakhsh, C. Mair, L. Matthews et al., “Virus–virus interactions impact the population dynamics of influenza and the common cold,” PNAS, vol. 116, no. 52, pp. 27142–27150, 2019. View at: Publisher Site | Google Scholar
  27. L. Chao, K. A. Hanley, C. L. Burch, C. Dahlberg, and P. E. Turner, “Kin selection and parasite evolution: higher and lower virulence with hard and soft selection,” The Quarterly Review of Biology, vol. 75, no. 3, 2000. View at: Google Scholar
  28. H. Y. Chen, M. Di Mascio, A. S. Perelson, D. D. Ho, and L. Zhang, “Determination of virus burst size in vivo using a single-cycle SIV in rhesus macaques,” PNAS, vol. 104, no. 48, pp. 19079–19084, 2007. View at: Publisher Site | Google Scholar
  29. S. J. Stray and G. M. Air, “Apoptosis by influenza viruses correlates with efficiency of viral mRNA synthesis,” Virus Research, vol. 77, no. 1, pp. 3–17, 2001. View at: Publisher Site | Google Scholar
  30. I. S. Novella, L. A. Ball, and G. W. Wertz, “Fitness analyses of vesicular stomatitis strains with rearranged genomes reveal replicative disadvantages,” Journal of Virology, vol. 78, no. 18, pp. 9837–9841, 2004. View at: Publisher Site | Google Scholar
  31. T. V. Stirbat, A. Mgharbel, S. Bodennec et al., “Fine tuning of tissues’ viscosity and surface tension through contractility suggests a new role for α-catenin,” PLoS One, vol. 8, no. 2, article e52554, 2013. View at: Publisher Site | Google Scholar
  32. Z. J. Storms, E. Arsenault, D. Sauvageau, and D. G. Cooper, “Bacteriophage adsorption efficiency and its effect on amplification,” Bioprocess and Biosystems Engineering, vol. 33, no. 7, pp. 823–831, 2010. View at: Publisher Site | Google Scholar
  33. Y. Shao and I.-N. Wang, “Bacteriophage adsorption rate and optimal lysis time,” Genetics, vol. 180, no. 1, pp. 471–482, 2008. View at: Publisher Site | Google Scholar
  34. S. Kawakami, Y. Watanabe, and R. N. Beachy, “Tobacco mosaic virus infection spreads cell to cell as intact replication complexes,” PNAS, vol. 101, no. 16, pp. 6291–6296, 2004. View at: Publisher Site | Google Scholar
  35. D. Kumar, R. Kumar, T. K. Hyun, and J.-Y. Kim, “Cell-to-cell movement of viruses via plasmodesmata,” Journal of Plant Research, vol. 128, no. 1, pp. 37–47, 2015. View at: Publisher Site | Google Scholar
  36. S. Gutiérrez, M. Yvon, G. Thébaud, B. Monsion, Y. Michalakis, and S. Blanc, “Dynamics of the multiplicity of cellular infection in a plant virus,” PLoS Pathogens, vol. 6, no. 9, article e1001113, 2010. View at: Publisher Site | Google Scholar
  37. S. Gutiérrez, E. Pirolles, M. Yvon, V. Baecker, Y. Michalakis, and S. Blanc, “The multiplicity of cellular infection changes depending on the route of cell infection in a plant virus,” Journal of Virology, vol. 89, no. 18, pp. 9665–9675, 2015. View at: Publisher Site | Google Scholar
  38. S. Cudmore, P. Cossart, G. Griffiths, and M. Way, “Actin-based motility of vaccinia virus,” Nature, vol. 378, no. 6557, pp. 636–638, 1995. View at: Publisher Site | Google Scholar
  39. M. J. Lehmann, N. M. Sherer, C. B. Marks, M. Pypaert, and W. Mothes, “Actin- and myosin-driven movement of viruses along filopodia precedes their entry into cells,” The Journal of Cell Biology, vol. 170, no. 2, pp. 317–325, 2005. View at: Publisher Site | Google Scholar
  40. S. Sowinski, C. Jolly, O. Berninghausen et al., “Membrane nanotubes physically connect T cells over long distances presenting a novel route for HIV-1 transmission,” Nature Cell Biology, vol. 10, no. 2, pp. 211–219, 2008. View at: Publisher Site | Google Scholar
  41. K. Takeuchi, N. Miyajima, N. Nagata, M. Takeda, and M. Tashiro, “Wild-type measles virus induces large syncytium formation in primary human small airway epithelial cells by a SLAM(CD150)-independent mechanism,” Virus Research, vol. 94, no. 1, pp. 11–16, 2003. View at: Publisher Site | Google Scholar
  42. M.-E. Hamelin, Y. Abed, and G. Boivin, “Human metapneumovirus: a new player among respiratory viruses,” Clinical Infectious Diseases, vol. 38, no. 7, pp. 983–990, 2004. View at: Publisher Site | Google Scholar
  43. N. L. Cole and C. Grose, “Membrane fusion mediated by herpesvirus glycoproteins: the paradigm of varicella-zoster virus,” Reviews in Medical Virology, vol. 13, no. 4, pp. 207–222, 2003. View at: Publisher Site | Google Scholar
  44. R. Nardacci, A. Antinori, L. M. Larocca et al., “Characterization of cell death pathways in human immunodeficiency virus- associated encephalitis,” The American Journal of Pathology, vol. 167, no. 3, pp. 695–704, 2005. View at: Publisher Site | Google Scholar
  45. R. A. Alvarez, M. I. Barría, and B. K. Chen, “Unique features of HIV-1 spread through T cell virological synapses,” PLoS Pathogens, vol. 10, no. 12, article e1004513, 2014. View at: Publisher Site | Google Scholar
  46. M. Dupont and Q. J. Sattentau, “Macrophage cell-cell interactions promoting HIV-1 infection,” Viruses, vol. 12, no. 5, p. 492, 2020. View at: Publisher Site | Google Scholar
  47. R. Sanjuán, “Collective infectious units in viruses,” Trends in Microbiology, vol. 25, no. 5, pp. 402–412, 2017. View at: Publisher Site | Google Scholar
  48. M. J. Iglesias-Sanchez and C. Lopez-Galindez, “Each genomic RNA in HIV-1 heterozygous virus generate new virions,” Virology, vol. 333, no. 2, pp. 316–323, 2005. View at: Publisher Site | Google Scholar
  49. M. Rager, S. Vongpunsawad, W. P. Duprex, and R. Cattaneo, “Polyploid measles virus with hexameric genome length,” The EMBO Journal, vol. 21, no. 10, pp. 2364–2372, 2002. View at: Publisher Site | Google Scholar
  50. D. R. Beniac, P. L. Melito, S. L. deVarennes et al., “The organisation of Ebola virus reveals a capacity for extensive, modular polyploidy,” PLoS One, vol. 7, no. 1, article e29608, 2012. View at: Publisher Site | Google Scholar
  51. D. Luque, G. Rivas, C. Alfonso, J. L. Carrascosa, J. F. Rodríguez, and J. R. Castón, “Infectious bursal disease virus is an icosahedral polyploid dsRNA virus,” PNAS, vol. 106, no. 7, pp. 2148–2152, 2009. View at: Publisher Site | Google Scholar
  52. M. Lago, J. F. Rodríguez, I. Bandín, and C. P. Dopazo, “Aquabirnavirus polyploidy: a new strategy to modulate virulence?” The Journal of General Virology, vol. 97, no. 5, pp. 1168–1177, 2016. View at: Publisher Site | Google Scholar
  53. J. M. Cuevas, M. Durán-Moreno, and R. Sanjuán, “Multi-virion infectious units arise from free viral particles in an enveloped virus,” Nature Microbiology, vol. 2, no. 7, p. 17078, 2017. View at: Publisher Site | Google Scholar
  54. V. Anschau and R. Sanjuán, “Fibrinogen gamma chain promotes aggregation of vesicular stomatitis virus in saliva,” Viruses, vol. 12, no. 3, p. 282, 2020. View at: Publisher Site | Google Scholar
  55. J. Münch, E. Rücker, L. Ständker et al., “Semen-derived amyloid fibrils drastically enhance HIV infection,” Cell, vol. 131, no. 6, pp. 1059–1071, 2007. View at: Publisher Site | Google Scholar
  56. K.-A. Kim, M. Yolamanova, O. Zirafi et al., “Semen-mediated enhancement of HIV infection is donor-dependent and correlates with the levels of SEVI,” Retrovirology, vol. 7, no. 1, p. 55, 2010. View at: Publisher Site | Google Scholar
  57. S. Yang, L. Zhao, R. Ma et al., “Improving baculovirus infectivity by efficiently embedding enhancing factors into occlusion bodies,” Applied and Environmental Microbiology, vol. 83, no. 14, article e00595, 2017. View at: Publisher Site | Google Scholar
  58. D. B. Sajjan and S. B. Hinchigeri, “Structural organization of baculovirus occlusion bodies and protective role of multilayered polyhedron envelope protein,” Food Environ Virol, vol. 8, no. 1, pp. 86–100, 2016. View at: Publisher Site | Google Scholar
  59. M. Santiana, S. Ghosh, B. A. Ho et al., “Vesicle-cloaked virus clusters are optimal units for inter-organismal viral transmission,” Cell Host & Microbe, vol. 24, no. 2, pp. 208–220.e8, 2018. View at: Publisher Site | Google Scholar
  60. J.-V. Bou, R. Geller, and R. Sanjuán, “Membrane-associated enteroviruses undergo intercellular transmission as pools of sibling viral genomes,” Cell Reports, vol. 29, no. 3, pp. 714–723.e4, 2019. View at: Publisher Site | Google Scholar
  61. Y.-H. Chen, W. L. du, M. C. Hagemeijer et al., “Phosphatidylserine vesicles enable efficient en bloc transmission of enteroviruses,” Cell, vol. 160, no. 4, pp. 619–630, 2015. View at: Publisher Site | Google Scholar
  62. V. Ramakrishnaiah and L. J. W. van der Laan, “Hepatitis virus hijacks shuttle: exosome-like vesicles provide protection against neutralizing antibodies,” Hepatology, vol. 59, no. 6, pp. 2416–2418, 2014. View at: Publisher Site | Google Scholar
  63. T. S. Arantes, R. A. L. Rodrigues, L. K. dos Santos Silva et al., “The large Marseillevirus explores different entry pathways by forming giant infectious vesicles,” Journal of Virology, vol. 90, no. 11, pp. 5246–5255, 2016. View at: Publisher Site | Google Scholar
  64. R. Sanjuán and M.-I. Thoulouze, “Why viruses sometimes disperse in groups?†,” Virus Evol, vol. 5, no. 1, p. vez014, 2019. View at: Publisher Site | Google Scholar
  65. I. Andreu-Moreno, J.-V. Bou, and R. Sanjuán, “Cooperative nature of viral replication,” Science Advances, vol. 6, no. 49, p. eabd4942, 2020. View at: Publisher Site | Google Scholar
  66. E. M. Cohen and O. Kobiler, “Gene expression correlates with the number of herpes viral genomes initiating infection in single cells,” PLoS Pathogens, vol. 12, no. 12, article e1006082, 2016. View at: Publisher Site | Google Scholar
  67. H. Kumar, T. Kawai, and S. Akira, “Pathogen recognition by the innate immune system,” International Reviews of Immunology, vol. 30, no. 1, pp. 16–34, 2011. View at: Publisher Site | Google Scholar
  68. I. Andreu-Moreno and R. Sanjuán, “Collective infection of cells by viral aggregates promotes early viral proliferation and reveals a cellular-level Allee effect,” Current Biology, vol. 28, no. 20, pp. 3212–3219.e4, 2018. View at: Publisher Site | Google Scholar
  69. F. S. Heldt, S. Y. Kupke, S. Dorl, U. Reichl, and T. Frensing, “Single-cell analysis and stochastic modelling unveil large cell-to-cell variability in influenza A virus infection,” Nature Communications, vol. 6, no. 1, p. 8938, 2015. View at: Publisher Site | Google Scholar
  70. N. T. Jacobs, N. O. Onuoha, A. Antia, J. Steel, R. Antia, and A. C. Lowen, “Incomplete influenza A virus genomes occur frequently but are readily complemented during localized viral spread,” Nature Communications, vol. 10, no. 1, p. 3526, 2019. View at: Publisher Site | Google Scholar
  71. B. E. Martin, J. D. Harris, J. Sun, K. Koelle, and C. B. Brooke, “Cellular co-infection can modulate the efficiency of influenza A virus production and shape the interferon response,” PLoS Pathogens, vol. 16, no. 10, article e1008974, 2020. View at: Publisher Site | Google Scholar
  72. K. L. Phipps, K. Ganti, N. T. Jacobs et al., “Collective interactions augment influenza A virus replication in a host- dependent manner,” Nature Microbiology, vol. 5, no. 9, pp. 1158–1169, 2020. View at: Publisher Site | Google Scholar
  73. P. Stiefel, F. I. Schmidt, P. Dörig et al., “Cooperative vaccinia infection demonstrated at the single-cell level using FluidFM,” Nano Letters, vol. 12, no. 8, pp. 4219–4227, 2012. View at: Publisher Site | Google Scholar
  74. L. M. Agosto, P. D. Uchil, and W. Mothes, “HIV cell-to-cell transmission: effects on pathogenesis and antiretroviral therapy,” Trends in Microbiology, vol. 23, no. 5, pp. 289–295, 2015. View at: Publisher Site | Google Scholar
  75. M. G. Katze, Y. He, and M. Gale, “Viruses and interferon: a fight for supremacy,” Nature Reviews. Immunology, vol. 2, no. 9, pp. 675–687, 2002. View at: Publisher Site | Google Scholar
  76. C. E. Samuel, “Antiviral actions of interferons,” Clinical microbiology reviews, vol. 14, pp. 778–809, 2001. View at: Google Scholar
  77. M. H. Orzalli and J. C. Kagan, “Apoptosis and necroptosis as host defense strategies to prevent viral infection,” Trends in Cell Biology, vol. 27, no. 11, pp. 800–809, 2017. View at: Publisher Site | Google Scholar
  78. F. Nainu, A. Shiratsuchi, and Y. Nakanishi, “Induction of apoptosis and subsequent phagocytosis of virus-infected cells as an antiviral mechanism,” Frontiers in Immunology, vol. 8, p. 1220, 2017. View at: Publisher Site | Google Scholar
  79. E. A. Voigt, A. Swick, and J. Yin, “Rapid induction and persistence of paracrine-induced cellular antiviral states arrest viral infection spread in A549 cells,” Virology, vol. 496, pp. 59–66, 2016. View at: Publisher Site | Google Scholar
  80. R. Sanjuán and P. Domingo-Calap, “Mechanisms of viral mutation,” Cellular and Molecular Life Sciences, vol. 73, no. 23, pp. 4433–4448, 2016. View at: Publisher Site | Google Scholar
  81. R. Sanjuán, “Mutational fitness effects in RNA and single-stranded DNA viruses: common patterns revealed by site-directed mutagenesis studies,” Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, vol. 365, no. 1548, pp. 1975–1982, 2010. View at: Publisher Site | Google Scholar
  82. H. Gao and M. W. Feldman, “Complementation and epistasis in viral coinfection dynamics,” Genetics, vol. 182, no. 1, pp. 251–263, 2009. View at: Publisher Site | Google Scholar
  83. E. Segredo-Otero and R. Sanjuán, “The effect of genetic complementation on the fitness and diversity of viruses spreading as collective infectious units,” Virus Research, vol. 267, pp. 41–48, 2019. View at: Publisher Site | Google Scholar
  84. P. R. Murcia, J. Hughes, P. Battista et al., “Evolution of an Eurasian avian-like influenza virus in naïve and vaccinated pigs,” PLoS Pathogens, vol. 8, no. 5, article e1002730, 2012. View at: Publisher Site | Google Scholar
  85. V. J. Morley, M. Sistrom, J. A. Usme-Ciro, S. K. Remold, and P. E. Turner, “Evolution in spatially mixed host environments increases divergence for evolved fitness and intrapopulation genetic diversity in RNA viruses,” Virus Evol, vol. 2, no. 1, p. vev022, 2016. View at: Publisher Site | Google Scholar
  86. O. Simón, T. Williams, P. Caballero, and M. López-Ferber, “Dynamics of deletion genotypes in an experimental insect virus population,” Proceedings of the Biological Sciences, vol. 273, no. 1588, pp. 783–790, 2006. View at: Publisher Site | Google Scholar
  87. S. Giri, S. Waschina, C. Kaleta, and C. Kost, “Defining division of labor in microbial communities,” Journal of Molecular Biology, vol. 431, no. 23, pp. 4712–4731, 2019. View at: Publisher Site | Google Scholar
  88. S. F. Elena, “Evolutionary transitions during RNA virus experimental evolution,” Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, vol. 371, no. 1701, p. 20150441, 2016. View at: Publisher Site | Google Scholar
  89. J. García-Arriaza, S. C. Manrubia, M. Toja, E. Domingo, and C. Escarmís, “Evolutionary transition toward defective RNAs that are infectious by complementation,” Journal of Virology, vol. 78, no. 21, pp. 11678–11685, 2004. View at: Publisher Site | Google Scholar
  90. V. Doceul, M. Hollinshead, L. van der Linden, and G. L. Smith, “Repulsion of superinfecting virions: a mechanism for rapid virus spread,” Science, vol. 327, no. 5967, pp. 873–876, 2010. View at: Publisher Site | Google Scholar
  91. X. Zhou, K. Sun, X. Zhou, A. O. Jackson, and Z. Li, “The matrix protein of a plant rhabdovirus mediates superinfection exclusion by inhibiting viral transcription,” Journal of Virology, vol. 93, no. 20, article e00680, 2019. View at: Publisher Site | Google Scholar
  92. M. Landsberger, S. Gandon, S. Meaden et al., “Anti-CRISPR phages cooperate to overcome CRISPR-Cas immunity,” Cell, vol. 174, no. 4, pp. 908–916.e12, 2018. View at: Publisher Site | Google Scholar
  93. A. L. Borges, J. Y. Zhang, M. C. F. Rollins, B. A. Osuna, B. Wiedenheft, and J. Bondy-Denomy, “Bacteriophage cooperation suppresses CRISPR-Cas3 and Cas9 immunity,” Cell, vol. 174, no. 4, pp. 917–925.e10, 2018. View at: Publisher Site | Google Scholar
  94. J. M. Petersen, L. S. Her, V. Varvel, E. Lund, and J. E. Dahlberg, “The matrix protein of vesicular stomatitis virus inhibits nucleocytoplasmic transport when it is in the nucleus and associated with nuclear pore complexes,” Molecular and Cellular Biology, vol. 20, no. 22, pp. 8590–8601, 2000. View at: Publisher Site | Google Scholar
  95. J. Smith, J. D. Van Dyken, and P. Zee, “A generalization of Hamilton’s rule for the evolution of microbial cooperation,” Science, vol. 328, no. 5986, pp. 1700–1703, 2010. View at: Publisher Site | Google Scholar
  96. A. F. G. Bourke, “Hamilton’s rule and the causes of social evolution,” Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, vol. 369, no. 1642, p. 20130362, 2014. View at: Publisher Site | Google Scholar
  97. S. A. West, A. S. Griffin, and A. Gardner, “Evolutionary explanations for cooperation,” Current Biology, vol. 17, no. 16, pp. R661–R672, 2007. View at: Publisher Site | Google Scholar
  98. Z. Erez, I. Steinberger-Levy, M. Shamir et al., “Communication between viruses guides lysis-lysogeny decisions,” Nature, vol. 541, no. 7638, pp. 488–493, 2017. View at: Publisher Site | Google Scholar
  99. M. Boots and M. Mealor, “Local interactions select for lower pathogen infectivity,” Science, vol. 315, no. 5816, pp. 1284–1286, 2007. View at: Publisher Site | Google Scholar
  100. A. Buckling and M. A. Brockhurst, “Kin selection and the evolution of virulence,” Heredity, vol. 100, no. 5, pp. 484–488, 2008. View at: Publisher Site | Google Scholar
  101. A. C. Hernandez-Morales, L. L. Lessor, T. L. Wood et al., “Genomic and biochemical characterization of Acinetobacter podophage petty reveals a novel lysis mechanism and tail-associated depolymerase activity,” Journal of Virology, vol. 92, no. 6, article e01064, 2018. View at: Publisher Site | Google Scholar
  102. L. Mi, Y. Liu, C. Wang et al., “Identification of a lytic Pseudomonas aeruginosa phage depolymerase and its anti-biofilm effect and bactericidal contribution to serum,” Virus Genes, vol. 55, no. 3, pp. 394–405, 2019. View at: Publisher Site | Google Scholar
  103. Z. Guo, J. Huang, G. Yan et al., “Identification and characterization of Dpo42, a novel depolymerase derived from the Escherichia coli phage vB_EcoM_ECOO78,” Frontiers in Microbiology, vol. 8, p. 1460, 2017. View at: Publisher Site | Google Scholar
  104. A. Latka, B. Maciejewska, G. Majkowska-Skrobek, Y. Briers, and Z. Drulis-Kawa, “Bacteriophage-encoded virion-associated enzymes to overcome the carbohydrate barriers during the infection process,” Applied Microbiology and Biotechnology, vol. 101, no. 8, pp. 3103–3119, 2017. View at: Publisher Site | Google Scholar
  105. M. Schmerer, I. J. Molineux, and J. J. Bull, “Synergy as a rationale for phage therapy using phage cocktails,” PeerJ, vol. 2, article e590, 2014. View at: Publisher Site | Google Scholar
  106. H. C. Gelderblom, D. N. Vatakis, S. A. Burke, S. D. Lawrie, G. C. Bristol, and D. N. Levy, “Viral complementation allows HIV-1 replication without integration,” Retrovirology, vol. 5, no. 1, p. 60, 2008. View at: Publisher Site | Google Scholar
  107. N. Appel, U. Herian, and R. Bartenschlager, “Efficient rescue of hepatitis C virus RNA replication by trans-complementation with nonstructural protein 5A,” Journal of Virology, vol. 79, no. 2, pp. 896–909, 2005. View at: Publisher Site | Google Scholar
  108. M. Doebeli and C. Hauert, “Models of cooperation based on the Prisoner’s Dilemma and the snowdrift game: Prisoner’s Dilemma and the Snowdrift game,” Ecology letters, vol. 8, pp. 748–766, 2005. View at: Google Scholar
  109. E. Szathmáry, “Natural selection and dynamical coexistence of defective and complementing virus segments,” Journal of Theoretical Biology, vol. 157, no. 3, pp. 383–406, 1992. View at: Publisher Site | Google Scholar
  110. T. B. Kirkwood and C. R. Bangham, “Cycles, chaos, and evolution in virus cultures: a model of defective interfering particles,” PNAS, vol. 91, no. 18, pp. 8685–8689, 1994. View at: Publisher Site | Google Scholar
  111. C. R. Bangham and T. B. Kirkwood, “Defective interfering particles: effects in modulating virus growth and persistence,” Virology, vol. 179, no. 2, pp. 821–826, 1990. View at: Publisher Site | Google Scholar
  112. L. Chao and S. F. Elena, “Nonlinear trade-offs allow the cooperation game to evolve from Prisoner’s Dilemma to Snowdrift,” Proceedings of the Royal Society B: Biological Sciences, vol. 284, no. 1854, p. 20170228, 2017. View at: Publisher Site | Google Scholar
  113. S. A. Frank, “Natural selection. VII. History and interpretation of kin selection theory,” Journal of Evolutionary Biology, vol. 26, no. 6, pp. 1151–1184, 2013. View at: Publisher Site | Google Scholar
  114. S. A. West, A. S. Griffin, A. Gardner, and S. P. Diggle, “Social evolution theory for microorganisms,” Nature Reviews. Microbiology, vol. 4, no. 8, pp. 597–607, 2006. View at: Publisher Site | Google Scholar
  115. R. Sanjuán, “The social life of viruses,” Annu Rev Virol, vol. 8, no. 1, pp. 183–199, 2021. View at: Publisher Site | Google Scholar
  116. S. Martín and S. F. Elena, “Application of game theory to the interaction between plant viruses during mixed infections,” The Journal of General Virology, vol. 90, no. 11, pp. 2815–2820, 2009. View at: Publisher Site | Google Scholar
  117. W. M. Wintermantel, A. A. Cortez, A. G. Anchieta, A. Gulati-Sakhuja, and L. L. Hladky, “Co-infection by two criniviruses alters accumulation of each virus in a host-specific manner and influences efficiency of virus transmission,” Phytopathology, vol. 98, no. 12, pp. 1340–1345, 2008. View at: Publisher Site | Google Scholar
  118. S. A. Felt, Y. Sun, A. Jozwik et al., “Detection of respiratory syncytial virus defective genomes in nasal secretions is associated with distinct clinical outcomes,” Nature Microbiology, vol. 6, no. 5, pp. 672–681, 2021. View at: Publisher Site | Google Scholar
  119. J. Vasilijevic, N. Zamarreño, J. C. Oliveros et al., “Reduced accumulation of defective viral genomes contributes to severe outcome in influenza virus infected patients,” PLoS Pathogens, vol. 13, no. 10, article e1006650, 2017. View at: Publisher Site | Google Scholar

Copyright © 2022 Ernesto Segredo-Otero and Rafael Sanjuán. Exclusive Licensee Nanjing Agricultural University. Distributed under a Creative Commons Attribution License (CC BY 4.0).

 PDF Download Citation Citation
Altmetric Score