What ecologists can tell virologists.

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Review in Advance first posted online on May 16, 2014. (Changes may still occur before final publication online and in print.)

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What Ecologists Can Tell Virologists Annu. Rev. Microbiol. 2014.68. Downloaded from www.annualreviews.org by Universitat Zurich- Hauptbibliothek Irchel on 06/05/14. For personal use only.

John J. Dennehy Biology Department, Queens College and the Graduate Center of the City University of New York, Queens, New York 11367; email: [email protected]

Annu. Rev. Microbiol. 2014. 68:117–35

Keywords

The Annual Review of Microbiology is online at micro.annualreviews.org

biogeography, coevolution, competition, horizontal gene transfer, trade-offs, virus ecology

This article’s doi: 10.1146/annurev-micro-091313-103436 c 2014 by Annual Reviews. Copyright All rights reserved

Abstract I pictured myself as a virus. . .and tried to sense what it would be like. —Jonas Salk Ecology as a science evolved from natural history, the observational study of the interactions of plants and animals with each other and their environments. As natural history matured, it became increasingly quantitative, experimental, and taxonomically broad. Focus diversified beyond the Eukarya to include the hidden world of microbial life. Microbes, particularly viruses, were shown to exist in unfathomable numbers, affecting every living organism. Slowly viruses came to be viewed in an ecological context rather than as abstract, disease-causing agents. This shift is exemplified by an increasing tendency to refer to viruses as living organisms instead of inert particles. In recent years, researchers have recognized the critical contributions of viruses to fundamental ecological processes such as biogeochemical cycling, competition, community structuring, and horizontal gene transfer. This review describes virus ecology from a virus’s perspective. If we are, like Jonas Salk, to imagine ourselves as a virus, what kind of world would we experience?

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Contents

Annu. Rev. Microbiol. 2014.68. Downloaded from www.annualreviews.org by Universitat Zurich- Hauptbibliothek Irchel on 06/05/14. For personal use only.

GETTING BY: SURVIVAL IN THE SUBMICROSCOPIC REALM . . . . . . . . . . . . . . TRADE-OFFS AND COMPROMISES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . GETTING AROUND: HITCHHIKING FOR THE ADVENTUROUS VIRUS . . VIRUS BIOGEOGRAPHY AND BIODIVERSITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . GETTING A LEG UP: VIRUS COMPETITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . GETTING ALONG: INTERACTIONS WITH OTHER SPECIES. . . . . . . . . . . . . . . VIRUS-HOST COEVOLUTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIRUSES AS VEHICLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CONCLUDING REMARKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

118 119 121 123 124 125 126 127 128

GETTING BY: SURVIVAL IN THE SUBMICROSCOPIC REALM

Environment: the physical, chemical, and biological surroundings of an organism at any given time Niche: the ecological role and space that an organism fills in a community Serial passage evolution: a population is allowed to evolve to a new environment by repeatedly transferring a fraction of a growing population to a new container provisioned with fresh resources

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A virus consists of, in essence, a protein shell surrounding a nucleic acid genome. The shell, or capsid, is exquisitely designed to perform several functions: (a) self-assemble, (b) package the genome, (c) protect the genome, and (d ) introduce the genome into a host cell. The genome, in turn, contains all the information required to replicate itself and the capsid inside the host cell. After the virus replicates, multiple copies exit the host and reenter the environment. A virus, thus, straddles two profoundly different worlds, divided by its host’s membrane. Once it leaves the confines of the host, a virus must cope with a highly variable, perilous environment. Its primary objective is to survive until it can locate and infect another host. A major driving force of virus particle design is the need to withstand great physicochemical variations in the environment. These environmental variations, however, are not unpredictable. That is, a virus can be said to reside in a specific ecological niche that consists of its host and the environmental circumstances in which the host lives (92). When a new virus is isolated, one can infer its basic characteristics from its ecological niche. For example, a virus isolated from a hot spring should be high-temperature resistant but perform poorly at low temperatures (such trade-offs are discussed in greater detail below). Because virus proteins are constrained by the environment and by virus functional requirements, it is possible to predict protein structural motifs based on environment of isolation (132). A more subtle point is that one can infer a virus’s ecological niche from its genome sequence. Given that most viruses are currently identified by environmental genomic sampling, efforts to correlate traits such as GC content and amino acid frequency and sequence with ecological niche may be rewarding (44, 94). Environmental hazards, such as high temperatures, desiccation, and radiation exposure, can kill viruses, but work relating virus structure, function, and environmental survival remains nascent (95, 145). Recent studies of bacteriophage thermostability provide excellent examples for future work (39, 40, 86). In one study, Dessau and colleagues (39) challenged phage ϕ6 populations with heat shocks in a serial passage evolution experiment. Mortality among phage populations following heat shocks exceeded 99%; thus strong selection was imposed for phage survival at high temperatures. Following 100 generations of evolution, a single amino acid substitution in the phage’s lysin protein improved the phage’s thermostability and survival 27-fold over the ancestral genotype. Structural studies revealed that the molecular basis of thermostabilization is the filling of a hydrophobic cavity in the lysin protein, which is unoccupied in the wild type (39). Although the mutation improved performance at high temperatures, it caused a 1.5-fold decrease in phage reproduction at standard rearing temperatures. Dennehy


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Heterogeneity of ecological conditions over time and space, and the constraints on virus survival and function, can lead to interesting patterns in the incidence of disease. For example, analysis of influenza sequence data shows unidirectional gene flow from a presumptive source in East Asia to ecological sinks in temperate regions that experience influenza epidemics during winter months (111, 120). These data suggest that influenza virus survival in temperate regions is only possible during winter and that each winter, temperate regions are independently seeded by new strains originating from East Asia. Precisely why East Asia is the ecological source of influenza is not clear, but it may be due to a complex interaction between virus survival, transmissibility, host physiology, and social behavior.


TRADE-OFFS AND COMPROMISES In a deeper sense, habitat specialization in response to an environmental gradient is recognized as a fundamental organizing principle governing organismal evolution (56, 80). Specialization rests on the assumption that natural selection cannot maximize the performance of all traits simultaneously. Increases in the performance of some traits are correlated with decreases in others. Some tradeoffs result from physical constraints or design limitations. For example, many studies point to a trade-off between virus survival and reproduction (31, 39). Capsid assembly kinetics may be such that assembly speed and capsid strength cannot be concurrently optimized (31). In the example given above, phage ϕ6 survival at high temperatures was associated with a loss of reproductive ability at lower temperatures (39). Trade-offs have also been used to explain phenomena such as host specialism and tissue tropism (27, 47, 63). For example, canine distemper virus hemagglutinin proteins bind domestic dog SLAM receptors significantly better than those of other canine species, implying that the virus is a dog specialist (104). Host specialism in such situations is often attributed to strong antagonistic pleiotropy, where mutations improving new functions jeopardize old functions (48). However, numerous cases can be found in the literature of virus performance being simultaneously maximized on multiple host types (115). One feature of some of these studies was that virus generalism was associated with simultaneous or alternating selection on both host regimes. Observations of differences in fitness on different hosts need not imply trade-offs but rather may be evidence of directional selection or mutation accumulation (115). That is, genotypes optimizing performance on multiple hosts may be accessible but may not fix in a population unless specifically selected for. Alternatively, mutations that are neutral in one host may be deleterious in another. The fixation of such mutations will result in fitness differences between host types although no actual trade-off exists. As such, host specialization is caused by the absence of selection in favor of maintaining host generalism. If there are no alternative hosts for a virus in a particular habitat, then the virus will adapt to the currently available host (i.e., specialize). If multiple hosts are available, then a virus may adapt to both hosts simultaneously in the absence of fitness-reducing trade-offs. However, for viruses, there may be an asymmetry in the ease of evolving specialism or generalism. Once the virus is specialized, it may be more difficult for it to reverse gears and recover generalism. The broad reach of trade-off and optimality theory includes virus pathogenicity (3, 30). According to this perspective, natural selection acts to maximize transmission, not to minimize virulence. Harm to the host can be selected for insofar as transmission is simultaneously increased. Conversely, any reduction of transmission due to excess virulence will be disfavored. A frequently cited example of the virulence-transmission trade-off is the attenuation of the rabbit myxoma virus following its introduction in Australia (5). Here rabbit mortality declined from 99% to 50% in a few years and was shown to be at least partially attributable to changes in virus pathogenicity (5). Anderson & May (5) suggested that the introduced strain was overly virulent and killed hosts www.annualreviews.org • What Ecologists Can Tell Virologists


Habitat: the area or environment where an organism lives Generalist/Specialist: generalist species thrive in a wide variety of ecological conditions, whereas specialist species persist in a narrow range of conditions Pleiotropy: occurs when a gene influences multiple, seemingly unrelated traits Fitness: a measure of an organism’s reproductive success Directional selection: selection against one extreme of a trait distribution tends to shift a population’s trait distribution to the opposite extreme

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before transmission could be effected. By contrast, attenuated strains allowed hosts to survive long enough to infect new hosts and so came to characterize the population. However, at least virulence was maintained because avirulent strains would fail to transmit the disease at all. In addition to observational studies, experimental evidence for the optimization of virulence by natural selection is available from several studies (32, 41). Doumayrou and colleagues (41) experimentally measured virulence and transmission of nine natural isolates of cauliflower mosaic virus while infecting Brassica rapa. Their results showed a positive correlation between virulence and transmission that was suggestive of an intermediate optimum. Finally, it is apparent that specialism and virulence interact. A virus that has alternative hosts to choose from is less invested in any specific host’s survival (88). Viruses also experience life history trade-offs, stemming from the allocation of limited resources. For example, among the lytic viruses, a trade-off exists between progeny number and generation time. Given that viral progeny are assembled at a linear rate (141), early lysing genotypes will produce, on average, fewer progeny than late lysing genotypes. However, early lysing progeny will have faster access to new host cells. The optimal solution to this trade-off is dictated by the number and quality of hosts available for infection (2, 141). When the number or quality of available hosts is low, natural selection may favor viruses that delay lysis and produce more progeny. In extreme cases, they may forgo lysis altogether and remain latent in the host (further discussion below). By contrast, high host density or quality should select for shorter latent periods and faster lysis. Lysis timing optimality models have been tested experimentally, and the results generally conform to expectations (68). However, some of these studies show that the evolution of optimal phenotypes is always subject to genetic and physical constraints (23, 68). In one case, experimentally evolved ϕX174 phages were unable to access the predicted optimal lysis time. The authors of this study pointed out that ϕX174 lysis gene E overlaps the highly conserved gene D (23). Mutations conferring an optimal lysis time may have been inaccessible because of their concomitant effects on other traits (i.e., antagonistic pleiotropy). Optimality theory provides a starting point to develop hypotheses regarding the evolution of organismal traits, but consideration should be paid to the genetic and physical constraints of the system under study. Related to the lysis timing trade-off is one governing the decision to enter a latent state as a provirus or lysogen. The trade-off here is between reproduction and survival. From the perspective of the virus, the world is sensed only through proxy molecules; thus, decisions must be made on probabilistic bases. A well-studied example comes from the λ phage, which uses bacterially produced RecA to determine host physiology (19). When hosts are metabolically active, RecA is active, which indirectly signals to the phage that the likelihood of finding permissive hosts outside the present host is great. By contrast, metabolically inactive hosts suggest to the phage that additional hosts are wanting. Some eukaryotic viruses engage in similar behaviors by integrating into host genomes as proviruses. These proviruses can remain quiescent for extended periods, a puzzling behavior given that the presumption is that viruses should be selected to maximize their own reproduction. In a larger sense, these behaviors can be viewed as bet-hedging strategies (49). A fraction of viruses sacrifice their reproductive potential to enter a protected state to minimize the risk of environmentally induced population extinction (143). These virus latency behaviors have significant implications for human health. Ho and colleagues (72) found that HIV’s reactivation from dormancy is stochastic, and some proviruses can remain latent despite stimuli to exit the genome. The HIV latent reservoir may be 60-fold greater than anticipated and presents a significant obstacle to a complete cure. The overwhelming evidence of trade-offs leads to the inescapable conclusion that viruses are finely tuned for their ecological circumstances, making it only more remarkable that they are able to do so much with so little. Despite having no sensory apparatus in the usual sense, viruses have an


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amazing ability to locate and infect host cells. One incredible example comes from the cauliflower mosaic virus, which uses aphids as vectors to facilitate their own transmission to new host plants. These viruses induce the formation of transmission bodies in host cells. When aphids feed on an infected leaf, a massive influx of tubulin into the transmission body releases a helper protein, P2, which assists the virus in binding the aphid mouth parts (97). Martinière and colleagues (97) propose to call this phenomenon virus perceptive behavior, as the virus is able to respond nearly instantaneously to changes in the environment. Furthermore, despite lacking any innate means of motility, nearly identical viruses can be found thousands of kilometers apart (17, 123, 134). For example, some Pseudomonas bacteriophages separated by a continent were more closely related than others isolated from the same plant (124). Host motility can explain some distributions (e.g., human viruses), but not others (e.g., phages). Below I discuss the physical forces affecting virus movement from the submicroscopic to megascopic scales.

GETTING AROUND: HITCHHIKING FOR THE ADVENTUROUS VIRUS At the nanoscale, virus movement is largely a product of thermally driven collisions with surrounding molecules, i.e., random diffusion by Brownian motion. Chance collisions may be more unlikely than previously imagined (see sidebar, A Virus’s View of the World). Abedon (1) has estimated that if a virus were the size of the RMS Titanic and its host were a kilometer-wide iceberg, then 1 mL would be equivalent to the volume of Earth. Infections due to diffusion might be improbable if it were not for the vast numbers of host cells and viruses and the mass movement of air and water currents. A virus’s diffusion coefficient depends on the size and shape of the virus, its interactions with the solvent, and the viscosity of the solvent. An underappreciated aspect of viral biology is how viral size and morphology affect the rates of host encounter. With the exception of the bacteriophages, most viruses are either spherical or rod shaped. Recent experiments showed that rod-shaped viruses diffuse in tissues or gels faster than spherical viruses (87). The reverse is true in liquids. Figure 1 shows examples of common virus morphologies. In addition, specific and nonspecific interactions between a virus and its surrounding matrix can strongly affect movement. For example, virus external surface charges may affect virus diffusion in fluids such as mucus. Some viruses easily penetrated mucus, whereas others such as herpes simplex

A VIRUS’S VIEW OF THE WORLD Imagine two cells in a fluid are separated by a modest distance of 1 m. How far is this for a virus? How long would it take to traverse this distance? Assume the average virus is 100 nm in diameter, or 1/10,000,000 of a meter. A virus would need to travel 10,000,000 body lengths to cross the distance between the two cells. In human terms, 10,000,000 body lengths equals 20,000 km or approximately the distance from Shanghai to Buenos Aires. But you can’t swim. You have to float there. Randomly. Virus diffusion is on the order of 4 × 10−10 m/s (86). At this speed, the time to travel 1 m is 2.5 × 109 s, or a little over 79 years. This assumes that the virus is traveling in the right direction. At this rate, the time it would take for a randomly moving virus to reach a fixed target 1 m away is essentially infinite. Imagine that a cell were the size of a human. A virus, then, would be roughly the size of an apple (65). If an apple-sized projectile were fired at a human-sized target located 20,000 km away, what would be the probability of hitting the target? Now imagine the apple’s trajectory randomly changes direction at random intervals. Will it ever strike the target?

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Figure 1 Representative viruses showing a range of morphologies. (a) Tobacco mosaic virus (Tomas Moravec). (b) G1 cluster mycobacteriophage (Brian Ford). (c) Megavirus (Chantal Abergel). (d ) Maize streak virus (Robert Milne). (e) Halovirus His1 (Mike Dyall-Smith). ( f ) Carnation latent virus (Robert Milne). ( g) Ebolavirus (Frederick Murphy). (h) Poliovirus [Centers for Disease Control and Prevention (CDC)]. (i ) Avian influenza H7N9 (CDC).

virus and HIV were trapped (90, 149). In another example, viruses with hydrophobic capsid surfaces or lipid membranes will accumulate at a droplet’s water-air interface (79). Conceivably this could enhance the transmission of viruses from fomites. It would be interesting to ascertain the degree to which differences in virus morphology derive from habitat differences. Virus movement can be modeled as a random walk until a chance collision with a host cell receptor. Naively, one might expect the virus’s host adsorption rate to be maximized, as this should minimize extracellular search period; however this may not always be the case (26). A classic example of adsorption rate modulation comes from the bacteriophage λ. Wild-type λ have side tail fibers, but initial culturing in the laboratory inadvertently isolated a stf− mutant (70). This mutant shows reduced attachment to Escherichia coli relative to the wild type. In agar, λ stf− produces larger plaques and has greater fitness than wild-type λ (57). Presumably conditions prevalent in laboratory habitats select for λ phage exhibiting reduced attachment rates. In general, selection for maximal reproduction should optimize adsorption rates for any given set of conditions. On one hand, in some situations, such as high densities of stationary phase cells, nonpermissive or trap cells, or cellular debris, high adsorption rates may be deleterious because they may limit the number of hosts encountered and productivity per host (37, 57). On the other hand, low attachment rates can prolong search times and expose phages to increased 122

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risks of environmentally induced inactivation. Mathematically it can be shown that intermediate attachment rates maximize viral fitness, even in liquid cultures, when traps are present (A.S. Singh & J.J. Dennehy, unpublished data). Decreasing virus diffusion rates (as when the viscosity of the culture media is increased) should exacerbate this effect. These predictions are eminently testable and would be a productive direction for future research. Above the nanoscale, virus transport is governed by convection, the concerted movement of particles within fluids (e.g., bodies of water or air). Simply by hitchhiking along aquatic and atmospheric currents, viruses have surprising capacities for host-independent movement. The infinitesimal size of viruses helps explain their extreme dispersal. Particle-settling velocity in any medium is a function of the medium’s viscosity and the particle’s radius and density (i.e., Stokes’ law). In air, 5-μM-diameter particles will fall 3 m in an hour, assuming no turbulence (133). Smaller particles, including nanometer-sized viruses, essentially do not settle. Fluid dynamics are similar in that viruses have a specific gravity only slightly greater than water (121). Locally, travel rates are fairly rapid, and virus particles can disperse within a room or body within minutes (91). Globally, virus dispersal can occur over thousands of kilometers and is likely only limited by virus survival (64, 144). Borne by the jet stream, a virus could feasibly be carried from the Sahara to the Amazon in a day. It might even be possible for a (lucky) virus to circumnavigate the globe in a matter of weeks.

VIRUS BIOGEOGRAPHY AND BIODIVERSITY How organisms are distributed across time and space is the central focus of the field of biogeography. Surprisingly little is known regarding virus biogeography. Only recently has the scientific community come to comprehend the vast size and ubiquity of virus populations. Thirty years ago, it was still believed that viruses in marine habitats were not native but rather were carried there from river and sewerage runoff (62). Given the immense size of the ocean habitat, estimates of the number of viruses in the biosphere have been revised upward to around 1031 , which is seven orders of magnitude greater than the number of stars in the known universe (128). With such numbers, one would expect similar levels of diversity. However, large-scale studies of virus biodiversity were not possible before the development of direct environmental genomic sampling (i.e., metagenomics). Here all nucleic acids from environmental samples (e.g., water, soil, tissue) are extracted, fragmented, and sequenced. Partial genetic fragments obtained from random sequence reads are computationally aligned and assembled into contigs (a consensus region of DNA based on overlapping fragments). Virus abundance, distribution, and diversity can be estimated from contig spectrums by counting the number of sequences that fall into each contig (4). Metagenomic studies have revealed a vast hidden world of virus diversity (118). Approximately 70% of generated sequence data showed no homology to existing sequences (118). It would appear that the bulk of extant virus strains remains unknown. Distinct virus types in the biosphere may number in the millions or more (4). Although provocative, the prevailing evidence is insufficient to evaluate Baas Becking’s (9) famous hypothesis, “Everything is everywhere, but, the environment selects.” If true, this hypothesis would suggest that viruses are spatially limited only by host availability. Depending on their hosts and host habitat preferences, some virus ranges may be fairly circumscribed. Bacterial biogeography, which is somewhat more advanced than viral biogeography, tends to the conclusion that historical events shape species assemblages (60, 98, 103). Some biogeographical studies of viruses support this view (38, 69, 125) whereas others do not (7, 16, 123). Perhaps viruses infecting hosts from rare and patchily distributed environments will show high degrees of spatial population www.annualreviews.org • What Ecologists Can Tell Virologists


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Competition: the simultaneous demand by two or more organisms or species for a limiting resource

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genetic differentiation, whereas more generalist viruses will show little population genetic differentiation. Viral biogeography remains an exciting new field with rich potential for novel insight; however, many difficulties need to be overcome. Especially relevant is how virus distributions will change as the earth’s temperatures rise (58).

GETTING A LEG UP: VIRUS COMPETITION


What shapes virus distributions? The proximate cause is the distribution of hosts, but ultimately all extant viruses are the products of billions of years of competition for hosts. The viruses we observe now are the viruses that are best at converting hosts into viral progeny under existing ecological conditions. Inferior viruses have gone extinct. Understanding competition between organisms is a primary goal of ecology. Because the objects of competition are more likely to be the same, competition is expected to intensify among more similar organisms. Gause’s (59) competitive exclusion principle holds that two species competing for the same resource cannot coexist if all other ecological factors are equal. This principle has been criticized because of its perceived rarity in the natural world and because of the diversity of similar organisms in seemingly identical habitats (i.e., the paradox of the plankton) (35). It is likely that these paradoxical situations violate, in some way, the ecological all-else-equal principle (75, 76, 114, 126). Habitat heterogeneity in time and space, and the ecological effects of this heterogeneity, is probably underestimated. Observations of seemingly similar viruses in the same habitat probably overlook small, but significant, genetic, phenotypic, or microhabitat variations. Whether infecting unicellular or multicellular hosts, viruses with different genotypes can directly compete for host resources. This competition can take place externally (as access for host cells is contested) or internally (within host cells). Externally, there are two main means by which competition is manifested: survival and host attachment. From the time it is released from a host until its entry into another host, a virus must protect its genetic material and maintain the integrity of its structural proteins against a myriad of environmental challenges. In addition, a virus must be able to maximize the introduction of its genome into the host cell despite variation in host physiology and abiotic environmental conditions. Given that virus infection entails the impairment or destruction of the host, there is strong selection on hosts to prevent viral infection. Host counterdefenses include extracellular barriers, receptor loss or alteration, immune activation, and alteration of the environment (e.g., fevers) (12, 28, 77). Multiple virus genotypes infecting the same cell can interact in many ways. At one end of the spectrum, virus genotypes can act mutualistically, increasing pathogenesis or transmission. For example, Lopez-Ferber and colleagues (93) found that some mixed baculovirus infections produced ´ more progeny than single-genotype infections. Coinfection also permits the recombination or reassortment of viral genomes (14, 112). Genome rearrangements allow the generation of novel genotypes from two parental genotypes and thus can be viewed as a form of sex (24, 137). Other interactions are more antagonistic. Coinfection and within-host competition can lead to increased virulence and pathogenicity (101, 105, 139). As discussed previously, viruses evolve to maximize transmission, and harm to the host will be favored insofar as it also increases virus transmission. In this scenario, viruses expressing intermediate levels of virulence should be favored by selection. However, when the virus is confronted by a coinfecting competitor, selection for increased within-host reproduction, with concomitant increases in virulence, will be imposed because the costs of killing the host are minimized (105, 139). Some viruses can parasitize resources from coinfecting helpers (25). This phenomenon is a general problem for organisms that create a valuable product that is made available to all without any guarantee of recompense (18). Viruses are unusual in that the components for creating progeny 124

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are released to a common pool within the host cell. This common pool is vulnerable to exploitation by genotypes that did not contribute to the common pool but reap its rewards. For example, phage P4 lacks head, tail, and lysis proteins, but it is able to package its genome into phage P2’s capsid (33). Although P4 is unable to reproduce in the absence of P2, it is presumably able to replicate its genome faster and thus may be packaged in greater numbers than P2. P4 and its allies have been called satellite viruses (33), but because they produce no capsid proteins, they may be better termed plasmids (83). Other viruses or virus-like elements that require helpers to reproduce include viroids, virusoids (130), and defective-interfering particles (74, 119). As a general rule, these parasitic viruses only arise when coinfection is common. As a consequence, there should be strong selection to sequester hosts and limit coinfection. The outcome of intense ecological competition is reflected in the numerous mechanisms of resistance to superinfection (77). For example, some lambdoid phages bind outer membrane protein FhuA to infect E. coli. A competing phage expresses a protein, Cor, that blocks FhuA-mediated ferrichrome uptake and prevents FhuA-mediated phage infection (138). If coinfection cannot be blocked, some viruses can produce intracellular protein products that interfere with their competitor’s reproduction (73). An illustrative case is the coinfection of host cells by influenza A and B viruses. In such situations, the total virus output is reduced relative to single infections of either virus (81). Furthermore, Wainitchang and colleagues (142) reported that influenza B nucleoprotein inhibits influenza A polymerase activity in a dose-dependent manner. Reductions in total virus load during coinfections will reduce each virus’s transmission between hosts; thus, viral interference may be a significant factor in virus ecology. Another consequence of this interference is that reassortment among influenza A and B does not occur (78, 81). Given that reassortment is a major factor in influenza evolution and pathogenicity (42, 102), the consequences of influenza interference are highly relevant to human health. Reassortment between influenza A and B strains could lead to highly pathogenic and transmissible influenza strains infecting humans. Another facet of interference competition that warrants mention is that virus colonization of new geographical areas can be impeded if endemic strains can interfere with the colonizing strain’s reproduction (107, 108). Thus virus interference may be an important factor in virus emergence. Epidemiological theory considers host resistance in models of disease spread, but virus interference could be an important hidden variable thus far overlooked. Competition and cooperation are means to an ultimate goal of persistence and increase of the virus. A popular view of evolution holds that the unit of selection is the gene and that organisms are teams of genes that function well together in the common goal of reproducing additional copies of themselves (29). Teams are able to use division of labor and economy of scale that allow the maximum utility of resources (66). However, among all teams—from viruses to multicellular organisms—there is an inherent tension between cooperation and defection. Cheating will be rewarded, but excessive exploitation will eventually collapse the entire edifice.

GETTING ALONG: INTERACTIONS WITH OTHER SPECIES Although it is common to view viruses as harmful to hosts, there are numerous examples of benefits conferred to hosts by viruses. One of the best-studied examples is E. coli and its phage λ. Several investigators found that λ lysogens have a growth advantage over nonlysogens (45, 46). More convincingly, the λ lom gene increased E. coli adhesion to human buccal epithelial cells by 50% relative to lom− strains (140). Another gene, bor, increased the resistance of E. coli lysogens to animal serum (11). These genes benefit λ because they increase λ survival by allowing it to hitchhike along with a more fit host lineage. Collectively, bacteriophages have an enormous impact on bacterial evolution and ecology and, consequently, on human health (see also Viruses as Vehicles) (15, 21, 67). www.annualreviews.org • What Ecologists Can Tell Virologists


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Mutualism: an ecological relationship where both partners benefit


Coevolution: reciprocal, adaptive genetic changes among two or more species

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Mutualistic interactions among viruses and hosts are not limited to bacteriophage-bacteria systems. Bézier and colleagues (13) reported that the genomes of parasitoid wasps contain polydnavirus genes. Wasps inject polydnavirus particles along with wasp eggs into lepidopteran hosts. The expressed polydnavirus proteins interfere with lepidopteran immune defenses, allowing wasp larvae to survive within hosts (13, 127). To cite another example, coinfection with GB virus C has been shown to reduce mortality among patients infected with HIV-1 (61, 135). The authors speculate that GB virus C interferes with HIV replication. Roossinck and colleagues cite numerous other examples in a pair of reviews of virus mutualisms (10, 117). As mentioned previously (see Trade-Offs and Compromises), natural selection will favor parasites that best enhance their own transmission. Aid or harm to the host is of secondary importance insofar as transmission is increased. Traits that protect the host from harm and/or help it reproduce can be favored as long as they do not reduce parasite transmission. Most examples of virus mutualisms (indeed, all mutualisms) are conditionally dependent (117). Viruses behave mutualistically when a confluence of conditions ensures that virus reproduction is increased relative to a more exploitative strategy. Bao & Roossinck (10) introduce a model wherein viruses will act to benefit hosts when it increases host carrying capacity. By increasing host carrying capacity, viruses can increase their own reproduction and long-term persistence. If the net reproduction of viruses is greater when temperate, and not exploitative, strategies are employed, then these virus traits will be favored by natural selection.

VIRUS-HOST COEVOLUTION Examples of mutualisms aside, viruses have a well-deserved reputation for nastiness. Because of their ability to harm or kill hosts, viruses can have wide-ranging impacts on hosts and host populations. At the most basic level, viruses impose strong selection pressures on hosts to prevent or ameliorate virus infection. Considerable resources are devoted to maintaining immune systems, defensive barriers, and behavioral responses (136, 150). Even the activation of the immune system by nonpathogenic agents is costly (100). Resources devoted to virus defenses could otherwise be devoted to reproduction. In addition, some defensive responses reduce the effectiveness of native physiological mechanisms. For example, E. coli resistance to T4 is effected by defects in the cell wall’s lipopolysaccharides, which increase permeability to hydrophobic compounds (148). Moreover, there is no doubt that many of our traits and characteristics were shaped by viruses. Examples of the signatures of viruses on human evolution include the ABO blood groups, the major histocompatibility complex (MHC), and the endogenous retroviruses. The acquisition of resistance by hosts frequently leads to counterresistance adaptations by viruses (reviewed in 36). It is believed that hosts and viruses can cycle through many rounds of adaptation and counteradaptation, either in the form of arms races or in cyclical Red Queen dynamics (96, 147). A well-studied example of such coevolution comes from the cell-surface transferrin receptor (TfR1), which regulates iron uptake into cells. Because TfR1 is essential for survival and cell replication, it makes a fine target for mammalian viruses. Demogines and colleagues (34) show that substitutions in the TfR1 amino acid sequence corresponding to the virus attachment site block virus entry while simultaneously preserving iron-uptake functionality. TfR1 has evolved so that a small number of amino acid residues can be constantly shuffled to provide virus resistance, and the protein’s key functional role has been preserved. One consequence of coevolution is that host populations will be polymorphic, harboring considerable genetic variation (8). This is significant, as genetic variation is the raw material that enables adaptive evolution. Genetic variation and population differentiation can affect species in

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other ways as well. To judge from the MHC genes as an example, selection imposed by viruses and other parasites can have far-reaching effects on sexual selection and mate choice among vertebrates (109). Animals may seek mates that have MHC genes dissimilar to their own to ensure that their offspring are more resistant to viruses and other parasites. Viruses and hosts have probably coevolved since the very beginnings of life. At each of the major transitions in history, viruses followed hosts as they split into separate lineages. McGeoch and colleagues (99) speculated that the common ancestor of the Herpesvirales first appeared before the emergence of vertebrates in the Cambrian period. Matching phylogenic trees suggest that simian foamy viruses and simian immunodeficiency viruses cospeciated with primates over long periods (122, 129). Although it is unlikely that viruses were the primary driving factor in eukaryotic speciation, it is plausible that they had some influence (54). It is well known that genomes are riddled with endogenous viruses and other elements. These viruses may have carried with them important genes or may have altered the expression of already present genes. As vehicles for genome rearrangements, viruses are a significant ecological and evolutionary force.

Horizontal gene transfer (HGT): the transfer of genes from organism to organism by processes other than reproduction Community: groups of interacting species coexisting in the same habitat

VIRUSES AS VEHICLES Horizontal gene transfer (HGT) is not traditionally considered to be under the purview of ecology, but this is likely to be a relic of the historical macroorganismal focus of ecological thought. Whereas HGT is rare among eukaryotes, it is widespread among microorganisms, particularly viruses. Because HGT significantly affects organismal survival, competition, interspecific interactions, and even community assembly, an ecological perspective of HGT is warranted. Here I discuss viruses as vehicles for HGT, and implications for the study of ecology. Viruses are prolific mediators of HGT, and their genomes often contain an amalgam of genetic information from a variety of sources, termed genomic mosaicism (22). Given that viruses replicate their own genomes in an environment that contains host genomes, coinfecting virus genomes, transposons, plasmids, and even transformed foreign DNA, the accidental integration of genetic material from separate sources is not surprising. As long as capsid space limitations are obeyed, viruses have an unparalleled ability to assimilate foreign genetic material. The statistical probability of such recombination events is low, but the vast number of opportunities for occurrence makes them inevitable. Consequently, nonhomologous recombination may be frequent enough to significantly affect virus evolution and ecology. In fact, the modular architecture of virus genomes may have evolved to allow suites of genes dedicated to a common function to be traded among viruses (19, 71). In other words, the organization and expression of some gene modules may be explicitly shaped to facilitate intergenomic transfer and assimilation into preexisting networks. Lawrence & Roth (85) suggested that the physical proximity of genes provides no physiological benefit to the organism but does benefit coadapted gene complexes. The probability of a successful transfer is enhanced when all the genes encoding a single function move together as a unit. By contrast, a partial cluster will provide no physiological benefit to the host and will be susceptible to deletion. This hypothesis has been criticized on account of the observation of essential genes in modular units. Instead it has been suggested that modularity enhances gene expression (106, 110). More recently evidence for the role of gene expression in genome modularity has been found lacking (84, 89). The prolificity of virus intergenic mobility is reflected in the fact that most organisms contain latent or nonfunctional viruses. This is apparent in bacteria where the majority of all sequenced genomes have been shown to contain prophages, constituting up to 20% of some genomes (20,



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82). Mobile genetic elements and endogenous viruses can account for up to 50% of mammalian and 90% of plant genomes (55). Given these numbers, suggestions that a significant portion of all genes in the biosphere are contained by viruses and virus-like elements are plausible (55). Extrapolation of published data suggests that 1024 genes are shuttled from viruses to hosts each year (116). Once integrated into host genomes, viral genes can be recruited for cellular functions to the benefit of the host. As such, viruses may be a major wellspring of genetic creativity (55). Commonly transferred genes include antibiotic resistance, metabolic, and virulence genes, all of which allow recipients to survive new habitats and can be major factors in emerging infectious diseases (82). For example, virulence genes carried by a prophage were implicated in a 2011 outbreak of E. coli O104:H4 that infected thousands in northern Germany. Rasko and colleagues (113) suggested that the epidemic was triggered by the E. coli strain’s acquisition of a Stx-encoding prophage and a plasmid bearing an extended-spectrum β lactamase gene. Viruses, in this sense, can be seen as part of a bacterium’s pangenome (131). In support of this contention, some viruses have evolved gene modules, termed morons, that contain the genes and transcription machinery encoding a specific function directly beneficial to the virus’s host but not to the virus itself (71). Morons consist of a protein-coding region flanked by a putative σ70 promoter and a factor-independent transcription terminator. The nucleotide composition of these regions often differs substantially from surrounding sequences, pointing to their independent origin. Some morons modulate pathogenicity in mammals, such as the superoxide dismutases conferring to Salmonella resistance against reactive oxygen species produced by the mammalian immune system (50). The importance of virus-mediated gene transfers is illustrated by recent theoretical modeling suggesting that viruses can increase the evolvability of their hosts, allowing them to better explore their adaptive landscape (146). Clearly viruses are important components of microbial HGT, resulting in the gain, loss, or reshuffling of host genes (6, 52, 116). Virus-modulated HGT affects eukaryotic organisms as well. Phylogenetic analyses of mitochondrial polymerases and helicases suggest that these critical genes were derived from a provirus infecting protomitochondria (51). In another example, retroviral glycoprotein-encoding env genes have been coopted by mammals to carry out a critical role in placental development (43). The envencoded membrane-fusogenic syncytins contribute to the formation of the syncytiotrophoblast, a fused cell layer at the maternal-fetal interface. In fact, these proteins may be involved in protecting the fetus from the maternal immune system. The retroviral env gene may have played a critical role in the evolutionary transition from egg-laying to placental mammals (43). More speculative hypotheses have implicated viruses in the origins of DNA, the nucleus, cell walls, mRNA capping, and the major domains of cellular life (54). If so, viruses might be the Zelig of the microbial world, present for every major evolutionary transition in the history of life.


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CONCLUDING REMARKS Although we may be loathe to admit it, viruses are an integral part and parcel of life and have accompanied us and our ancestors from the dawn of life on Earth. Although denigrated as parasites or pathogens, viruses work in mysterious ways. It is doubtful that the wondrous diversity we experience would exist if it were not for viruses. They are the dark matter of the biosphere (53), the hidden world that directly or indirectly affects every living organism. Much of the world’s genetic information is contained within them (54). They are masters of shuttling genes, manipulating hosts, creating evolutionary novelty, and fostering biodiversity. They alter biogeographical cycles, communities, and ecosystems and may even influence global climate. Further study of the evolution and ecology of viruses can only increase our appreciation of the rich and wonderful fabric of life. 128

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FUTURE ISSUES 1. How do environmental factors, such as temperature and humidity, shape the epidemiology of viral diseases? 2. How do physical constraints shape virus genome size and architecture? 3. What is the biology of the atmosphere, and how does it affect virus distributions? 4. Are viruses a major force in generating evolutionary novelty and biological diversity? 5. What was the role of viruses in the major transitions in evolutionary history?


6. To what extent do viruses manipulate host behavior, particularly among humans, to facilitate their own transmission?

DISCLOSURE STATEMENT The author is not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS Most, if not all, of the ideas contained in this manuscript are not my own. I apologize to innumerous authors whose work I did not cite because of space limitations. I am indebted to Stephen Abedon, Marko Baloh, James Carpino, Daniel Dykhuizen, Pak-Wing Fok, Brian Ford, Nicholas Friedenberg, Daniel Goldhill, Paul Gottlieb, Al Katz, Gregory Lallos, Abhyudai Singh, Paul Turner, Ing-Nang Wang, and Ry Young for edifying conversations on all things phage. Special thanks to James Carpino for critical suggestions and comments on a prior draft. This work was supported by NSF award #1148879.

LITERATURE CITED 1. Abedon ST. 2011. Envisaging bacteria as phage targets. Bacteriophage 1:228–30 2. Abedon ST, Herschler TD, Stopar D. 2001. Bacteriophage latent-period evolution as a response to resource availability. Appl. Environ. Microbiol. 67:4233–41 3. Alizon S, Hurford A, Mideo N, van Baalen M. 2009. Virulence evolution and the trade-off hypothesis: history, current state of affairs and the future. J. Evol. Biol. 22:245–59 4. Allen HK, Bunge J, Foster JA, Bayles DO, Stanton TB. 2013. Estimation of viral richness from shotgun metagenomes using a frequency count approach. Microbiome 1:5 5. Anderson RM, May RM. 1982. Coevolution of hosts and parasites. Parasitology 85:411–26 6. Andersson JO. 2009. Gene transfer and diversification of microbial eukaryotes. Annu. Rev. Microbiol. 63:177–93 7. Angly FE, Felts B, Breitbart M, Salamon P, Edwards RA, et al. 2006. The marine viromes of four oceanic regions. PLoS Biol. 4:2121–31 8. Apanius V, Penn D, Slev PR, Ruff LR, Potts WK. 1997. The nature of selection on the major histocompatibility complex. Crit. Rev. Immunol. 17:179–224 9. Baas Becking LGM. 1934. Geobiologie of Inleiding Tot de Milieukunde. Hague, Neth.: Van Stockum & Zoon 10. Bao X, Roossinck MJ. 2013. A life history view of mutualistic viral symbioses: quantity or quality for cooperation? Curr. Opin. Microbiol. 16:514–18 www.annualreviews.org • What Ecologists Can Tell Virologists


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13. In a twist, a parasitic wasp hijacks virus genes to silence its lepidopteran host’s immune system.

34. TfR1 iron transporter sequence highly conserved except at two regions associated with virus binding.

130

16:34

11. Barondess JJ, Beckwith J. 1995. bor gene of phage λ, involved in serum resistance, encodes a widely conserved outer-membrane lipoprotein. J. Bact. 177:1247–53 12. Beutler B, Eidenschenk C, Crozat K, Imler J-L, Takeuchi O, et al. 2007. Genetic analysis of resistance to viral infection. Nat. Rev. Immunol. 7:753–66 13. Bezier A, Annaheim M, Herbiniere J, Wetterwald C, Gyapay G, et al. 2009. Polydnaviruses of ´ Braconid wasps derive from an ancestral nudivirus. Science 323:926–30 14. Blackard JT, Cohen DE, Mayer KH. 2002. Human immunodeficiency virus superinfection and recombination: current state of knowledge and potential clinical consequences. Clin. Infect. Dis. 34:1108–14 15. Boyd EF. 2012. Bacteriophage-encoded bacterial virulence factors and phage-pathogenicity island interactions. Adv. Virus Res. 82:91–118 16. Breitbart M, Miyake JH, Rohwer F. 2004. Global distribution of nearly identical phage-encoded DNA sequences. FEMS Microbiol. Lett. 236:249–56 17. Breitbart M, Rohwer F. 2005. Here a virus, there a virus, everywhere the same virus? Trends Microbiol. 13:278–84 18. Bronstein JL. 2001. The exploitation of mutualisms. Ecol. Lett. 4:277–87 19. Campbell A, Botstein D. 1983. Evolution of the lambdoid phages. In Lambda II, ed. RW Hendrix, pp. 365–80. Cold Spring Harbor: Cold Spring Harbor Laboratory Press 20. Canchaya C, Proux C, Fournous G, Bruttin A, Brussow H. 2003. Prophage genomics. Microbiol. Mol. Biol. Rev. 67:238–76 21. Casas V, Maloy S. 2011. Role of bacteriophage-encoded exotoxins in the evolution of bacterial pathogens. Future Microbiol. 6:1461–73 22. Casjens SR, Thuman-Commike PA. 2011. Evolution of mosaically related tailed bacteriophage genomes seen through the lens of phage P22 virion assembly. Virol 411:393–415 23. Chantranupong L, Heineman RH. 2012. A common, non-optimal phenotypic endpoint in experimental adaptations of bacteriophage lysis time. BMC Evol. Biol. 12:37 24. Chao L. 1992. Evolution of sex in RNA viruses. Trends Ecol. Evol. 7:147–51 25. Christie GE, Dokland T. 2012. Pirates of the Caudovirales. Virol 434:210–21 26. Conley MP, Wood WB. 1975. Bacteriophage T4 whiskers: a rudimentary environment-sensing device. Proc. Natl. Acad. Sci. USA 72:3701–5 27. Crill WD, Wichman HA, Bull JJ. 2000. Evolutionary reversals during viral adaptation to alternating hosts. Genetics 154:27–37 28. Damania B, Blackbourn DJ. 2012. Innate barriers to viral infection. Future Microbiol. 7:815–22 29. Dawkins R. 1976. The Selfish Gene. Oxford: Oxford Univ. Press 30. Day T. 2003. Virulence evolution and the timing of disease life-history events. Trends Ecol. Evol. 18:113– 18 31. De Paepe M, Taddei F. 2006. Viruses’ life history: towards a mechanistic basis of a trade-off between survival and reproduction among phages. PLoS Biol. 4:e193 32. de Roode JC, Yates AJ, Altizer S. 2008. Virulence-transmission trade-offs and population divergence in virulence in a naturally occurring butterfly parasite. Proc. Natl. Acad. Sci. USA 105:7489–94 33. Deho G, Ghisotti D. 2006. The satellite phage P4. In The Bacteriophages, ed. RL Calendar, ST Abedon, pp. 391–408. Oxford: Oxford Univ. Press 34. Demogines A, Abraham J, Choe H, Farzan M, Sawyer SL. 2013. Dual host-virus arms races shape an essential housekeeping protein. PLoS Biol. 11:e1001571 35. den Boer PJ. 1986. The present status of the competitive exclusion principle. Trends Ecol. Evol. 1:25–28 36. Dennehy JJ. 2012. What can phages tell us about host-pathogen coevolution? Int. J. Evol. Biol. 2012:396165 37. Dennehy JJ, Friedenberg NA, Yang YW, Turner PE. 2007. Virus population extinction via ecological traps. Ecol. Lett. 10:230–40 38. Desnues C, Rodriguez-Brito B, Rayhawk S, Kelley S, Tran T, et al. 2008. Biodiversity and biogeography of phages in modern stromatolites and thrombolites. Nature 452:340–43 Dennehy



MI68CH07-Dennehy

ARI

8 May 2014

16:34

39. Dessau M, Goldhill D, McBride RL, Turner PE, Modis Y. 2012. Selective pressure causes an RNA virus to trade reproductive fitness for increased structural and thermal stability of a viral enzyme. PLoS Genet. 8:e1003102 40. Domingo-Calap P, Pereira-Gomez M, Sanjuán R. 2010. Selection for thermostability can lead to the ´ emergence of mutational robustness in an RNA virus. J. Evol. Biol. 23:2453–60 41. Doumayrou J, Avellan A, Froissart R, Michalakis Y. 2013. An experimental test of the transmissionvirulence trade-off hypothesis in a plant virus. Evolution 67:477–86 42. Ducatez MF, Hause B, Stigger-Rosser E, Darnell D, Corzo C, et al. 2011. Multiple reassortment between pandemic (H1N1) 2009 and endemic influenza viruses in pigs: United States. Emerg. Infect. Dis. 17:1624– 29 43. Dupressoir A, Lavialle C, Heidmann T. 2012. From ancestral infectious retroviruses to bona fide cellular genes: role of the captured syncytins in placentation. Placenta 33:663–71 44. Dutta C, Paul S. 2012. Microbial lifestyle and genome signatures. Curr. Genomics 13:153–62 45. Dykhuizen D, Campbell JH, Rolfe BG. 1978. Influences of a lambda prophage on the growth rate of Escherichia coli. Microbios 23:99–113 46. Edlin G, Lin L, Kudrna R. 1975. Lambda lysogens of Escherichia coli reproduce more rapidly than non-lysogens. Nature 255:735–37 47. Elena SF, Agudelo-Romero P, Carrasco P, Codoner ˜ FM, Mart´ın S, et al. 2008. Experimental evolution of plant RNA viruses. Heredity 100:478–83 48. Elena SF, Agudelo-Romero P, Lalić J. 2009. The evolution of viruses in multi-host fitness landscapes. Open Virol. J. 3:1–6 49. Evans MEK, Dennehy JJ. 2005. Germ banking: bet-hedging and variable release from egg and seed dormancy. Q. Rev. Biol. 80:431–51 50. Figueroa-Bossi N, Bossi L. 1999. Inducible prophages contribute to Salmonella virulence in mice. Mol. Microbiol. 33:167–76 51. Filée J, Forterre P. 2005. Viral proteins functioning in organelles: a cryptic origin? Trends Microbiol. 13:510–13 52. Filée J, Forterre P, Sen-Lin T, Laurent J. 2002. Evolution of DNA polymerase families: evidences for multiple gene exchange between cellular and viral proteins. J. Mol. Evol. 54:763–73 53. Filée J, Tetart F, Suttle CA, Krisch HM. 2005. Marine T4-type bacteriophages, a ubiquitous component of the dark matter of the biosphere. Proc. Natl. Acad. Sci. USA 102:12471–76 54. Forterre P, Prangishvili D. 2009. The great billion-year war between ribosome- and capsid-encoding organisms (cells and viruses) as the major source of evolutionary novelties. In Natural Genetic Engineering and Natural Genome Editing, ed. G Witzany, pp. 65–77. Boston: Blackwell 55. Forterre P, Prangishvili D. 2013. The major role of viruses in cellular evolution: facts and hypotheses. Curr. Opin. Virol. 3:558–65 56. Futuyma DJ, Moreno G. 1988. The evolution of ecological specialization. Annu. Rev. Ecol. Syst. 19:207– 33 57. Gallet R, Shao Y, Wang I-N. 2009. High adsorption rate is detrimental to bacteriophage fitness in a biofilm-like environment. BMC Evol. Biol. 9:241 58. Garcia-Pichel F, Loza V, Marusenko Y, Mateo P, Potrafka RM. 2013. Temperature drives the continental-scale distribution of key microbes in topsoil communities. Science 340:1574–77 59. Gause GF. 1934. The Struggle for Existence. Baltimore, MD: Williams & Wilkins 60. Ghiglione J-F, Galand PE, Pommier T, Pedros-Ali o´ C, Maas EW, et al. 2012. Pole-to-pole biogeography ´ of surface and deep marine bacterial communities. Proc. Natl. Acad. Sci. USA 109:17633–38 61. Giret MTM, Kallas EG. 2012. GBV-C: state of the art and future prospects. Curr. HIV/AIDS RepP.9:26– 33 62. Goyal SM, Gerba CP, Bitton G. 1987. Phage Ecology. Boca Raton, FL: CRC 63. Greene IP, Wang EY, Deardorff ER, Milleron R, Domingo E, Weaver SC. 2005. Effect of alternating passage on adaptation of Sindbis virus to vertebrate and invertebrate cells. J. Virol. 79:14253–60 64. Griffin DW. 2007. Atmospheric movement of microorganisms in clouds of desert dust and implications for human health. Clin. Microbiol. Rev. 20:459–77 www.annualreviews.org • What Ecologists Can Tell Virologists


39. Study determines molecular basis of virus thermal stability and capsid assembly trade-off.

131


MI68CH07-Dennehy

ARI

8 May 2014

72. The noninduced provirus fraction of the latent HIV reservoir is found to be reproductively viable.

132

16:34

65. Hagens S, Loessner MJ. 2010. Bacteriophage for biocontrol of foodborne pathogens: calculations and considerations. Curr. Pharm. Biotechnol. 11:58–68 66. Haig D. 1997. The social gene. In Behavioural Ecology: An Evolutionary Approach, ed. JR Krebs, NB Davies, pp. 284–304. Malden, MA: Blackwell Science. 4th ed. 67. Hartley M-A, Ronet C, Fasel N. 2012. Backseat drivers: the hidden influence of microbial viruses on disease. Curr. Opin. Microbiol. 15:538–45 68. Heineman RH, Bull JJ. 2007. Testing optimality with experimental evolution: lysis time in a bacteriophage. Evolution 61:1695–709 69. Held NL, Whitaker RJ. 2009. Viral biogeography revealed by signatures in Sulfolobus islandicus genomes. Environ. Microbiol. 11:457–66 70. Hendrix RW, Duda RL. 1992. Bacteriophage lambda PaPa: not the mother of all lambda phages. Science 258:1145–48 71. Hendrix RW, Lawrence JG, Hatfull GF, Casjens S. 2000. The origins and ongoing evolution of viruses. Trends Microbiol. 8:504–8 72. Ho Y-C, Shan L, Hosmane NN, Wang J, Laskey SB, et al. 2013. Replication-competent noninduced proviruses in the latent reservoir increase barrier to HIV-1 cure. Cell 155:540–51 73. Hobson-Peters J, Yam AWY, Lu JWF, Setoh YX, May FJ, et al. 2013. A new insect-specific flavivirus from northern Australia suppresses replication of West Nile virus and Murray Valley encephalitis virus in co-infected mosquito cells. PLoS ONE 8:e56534 74. Huang AS. 1973. Defective interfering viruses. Annu. Rev. Microbiol. 27:101–17 75. Huisman J, Weissing FJ. 1999. Biodiversity of plankton by species oscillations and chaos. Nature 402:407– 10 76. Hutchinson GE. 1961. Paradox of the plankton. Am. Nat. 95:137–45 77. Hyman P, Abedon ST. 2010. Bacteriophage host range and bacterial resistance. In Advances in Applied Microbiology, ed. AI Laskin, S Sariaslani, GM Gadd. pp. 217–48. Vol. 70. Waltham, MA: Academic 78. Iwatsuki-Horimoto K, Hatta Y, Hatta M, Muramoto Y, Chen H, et al. 2008. Limited compatibility between the RNA polymerase components of influenza virus type A and B. Virus Res. 135:161–65 79. Johnson RP, Gregory DW. 1993. Viruses accumulate spontaneously near droplet surfaces: a method to concentrate viruses for electron microscopy. J. Microsc. 171:125–36 80. Kassen R. 2002. The experimental evolution of specialists, generalists, and the maintenance of diversity. J. Evol. Biol. 15:173–90 81. Kaverin NV, Varich NL, Sklyanskaya EI, Amvrosieva TV, Petrik J, Vovk TC. 1983. Studies on heterotypic interference between influenza-A and influenza-B viruses: a differential inhibition of the synthesis of viral proteins and RNAs. J. Gen. Virol. 64:2139–46 82. Klumpp J, Fouts DE, Sozhamannan S. 2013. Bacteriophage functional genomics and its role in bacterial pathogen detection. Brief Funct. Genomics 12:354–65 83. Krupovic M, Ravantti JJ, Bamford DH. 2009. Geminiviruses: a tale of a plasmid becoming a virus. BMC Evol. Biol. 9:112 84. Lang GI, Botstein D. 2011. A test of the coordinated expression hypothesis for the origin and maintenance of the GAL cluster in yeast. PLoS ONE 6:e25290 85. Lawrence JG, Roth JR. 1996. Selfish operons: Horizontal transfer may drive the evolution of gene clusters. Genetics 143:1843–60 86. Lee KH, Miller CR, Nagel AC, Wichman HA, Joyce P, Ytreberg FM. 2011. First-step mutations for adaptation at elevated temperature increase capsid stability in a virus. PLoS ONE 6:e25640 87. Lee KL, Hubbard LC, Hern S, Yildiz I, Gratzl M, Steinmetz NF. 2013. Shape matters: The diffusion rates of TMV rods and CPMV icosahedrons in a spheroid model of extracellular matrix are distinct. Biomater. Sci. 1:581–88 88. Leggett HC, Buckling A, Long GH, Boots M. 2013. Generalism and the evolution of parasite virulence. Trends Ecol. Evol. 28:592–96 89. Liang LW, Hussein R, Block DHS, Lim HN. 2013. Minimal effect of gene clustering on expression in Escherichia coli. Genetics 193:453–65 90. Lieleg O, Lieleg C, Bloom J, Buck CB, Ribbeck K. 2012. Mucin biopolymers as broad-spectrum antiviral agents. Biomacromolecules 13:1724–32 Dennehy



MI68CH07-Dennehy

ARI

8 May 2014

16:34

91. Lindsley WG, King WP, Thewlis RE, Reynolds JS, Panday K, et al. 2012. Dispersion and exposure to a cough-generated aerosol in a simulated medical examination room. J. Occup. Environ. Hyg. 9:681–90 92. Lloyd-Smith JO. 2013. Vacated niches, competitive release and the community ecology of pathogen eradication. Philos. Trans. R. Soc. Lond. B 368:20120150 93. Lopez-Ferber M, Simon ´ ´ O, Williams T, Caballero P. 2003. Defective or effective? Mutualistic interactions between virus genotypes. Proc. R. Soc. B 270:2249–55 94. Mann S, Chen Y-PP. 2010. Bacterial genomic G + C composition-eliciting environmental adaptation. Genomics 95:7–15 95. Mannige RV, Brooks CL III. 2010. Periodic table of virus capsids: implications for natural selection and design. PLoS ONE 5:e9423 96. Marston MF, Pierciey FJ Jr, Shepard A, Gearin G, Qi J, et al. 2012. Rapid diversification of coevolving marine Synechococcus and a virus. Proc. Natl. Acad. Sci. USA 109:4544–49 97. Martiniere ` A, Bak A, Macia J-L, Lautredou N, Gargani D, et al. 2013. A virus responds instantly to the presence of the vector on the host and forms transmission morphs. eLife 2:e00183 98. Martiny JBH, Bohannan BJM, Brown JH, Colwell RK, Fuhrman JA, et al. 2006. Microbial biogeography: putting microorganisms on the map. Nat. Rev. Microbiol. 4:102–12 99. McGeoch DJ, Rixon FJ, Davison AJ. 2006. Topics in herpesvirus genomics and evolution. Virus Res. 117:90–104 100. Moret Y, Schmid-Hempel P. 2000. Survival for immunity: the price of immune system activation for bumblebee workers. Science 290:1166–68 101. Mosquera J, Adler FR. 1998. Evolution of virulence: a unified framework for coinfection and superinfection. J. Theor. Biol. 195:293–313 102. Nelson MI, Viboud C, Simonsen L, Bennett RT, Griesemer SB, et al. 2008. Multiple reassortment events in the evolutionary history of H1N1 influenza A virus since 1918. PLoS Pathog. 4:e1000012 103. Nemergut DR, Costello EK, Hamady M, Lozupone C, Jiang L, et al. 2011. Global patterns in the biogeography of bacterial taxa. Environ. Microbiol. 13:135–44 104. Nikolin VM, Osterrieder K, von Messling V, Hofer H, Anderson D, et al. 2012. Antagonistic pleiotropy and fitness trade-offs reveal specialist and generalist traits in strains of canine distemper virus. PLoS ONE 7:e50955 105. Nowak MA, May RM. 1994. Superinfection and the evolution of parasite virulence. Proc. R. Soc. B 255:81–89 106. Pal C, Hurst LD. 2004. Evidence against the selfish operon theory. Trends Genet. 20:232–34 107. Pepin KM, Hanley KA. 2008. Density-dependent competitive suppression of sylvatic dengue virus by endemic dengue virus in cultured mosquito cells. Vector Borne Zoonotic Dis. 8:821–28 108. Pepin KM, Lambeth K, Hanley KA. 2008. Asymmetric competitive suppression between strains of dengue virus. BMC Microbiol. 8:28 109. Piertney SB, Oliver MK. 2006. The evolutionary ecology of the major histocompatibility complex. Heredity 96:7–21 110. Price MN, Huang KH, Arkin AP, Alm EJ. 2005. Operon formation is driven by co-regulation and not by horizontal gene transfer. Genome Res. 15:809–19 111. Rambaut A, Pybus OG, Nelson MI, Viboud C, Taubenberger JK, Holmes EC. 2008. The genomic and epidemiological dynamics of human influenza A virus. Nature 453:615–19 112. Ramig RF, Ward RL. 1991. Genomic segment reassortment in rotaviruses and other reoviridae. Adv. Virus Res. 39:163–207 113. Rasko DA, Webster DR, Sahl JW, Bashir A, Boisen N, et al. 2011. Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany. N. Engl. J. Med. 365:709–17 114. Record NR, Pershing AJ, Maps F. 2014. The paradox of the “paradox of the plankton”. ICES J. Mar. Sci. 71:236–40 115. Remold S. 2012. Understanding specialism when the jack of all trades can be the master of all. Proc. R. Soc. B 279:4861–69 116. Rohwer F, Thurber RV. 2009. Viruses manipulate the marine environment. Nature 459:207–12 117. Roossinck MJ. 2011. The good viruses: viral mutualistic symbioses. Nat. Rev. Microbiol. 9:99–108 www.annualreviews.org • What Ecologists Can Tell Virologists


96. Antagonistic coevolution with a virus leads to diversification of an important marine cyanobacterium.

97. Virus perceives aphid vectors via host cell responses and behaves to increase its own transmission.

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8 May 2014


122. Annual seasonal epidemics of influenza A are independently seeded by populations from East Asia.

142. Influenza B nucleoprotein inhibits influenza A polymerase activity in a dosedependent manner, suggesting an interference mechanism.

134

16:34

118. Rosario K, Breitbart M. 2011. Exploring the viral world through metagenomics. Curr. Opin. Virol. 1:289–97 119. Roux L, Simon AE, Holland JJ. 1991. Effects of defective interfering viruses on virus replication and pathogenesis in vitro and in vivo. Adv. Virus Res. 40:181–211 120. Russell CA, Jones TC, Barr IG, Cox NJ, Garten RJ, et al. 2008. The global circulation of seasonal influenza A (H3N2) viruses. Science 320:340–46 121. Sehgal OP, Jean J, Bhalla RB, Soong MM, Krause GF. 1970. Correlation between buoyant density and ribonucleic acid content in viruses. Phytopathology 60:1778–84 122. Sharp PM, Hahn BH. 2011. Origins of HIV and the AIDS pandemic. Cold Spring Harb. Perspect. Med. 1:a006841 123. Short CM, Suttle CA. 2005. Nearly identical bacteriophage structural gene sequences are widely distributed in both marine and freshwater environments. Appl. Environ. Microbiol. 71:480–86 124. Silander OK, Weinreich DM, Wright KM, O’Keefe KJ, Rang CU, et al. 2005. Widespread genetic exchange among terrestrial bacteriophages. Proc. Natl. Acad. Sci. USA 102:19009–14 125. Snyder JC, Wiedenheft B, Lavin M, Roberto FF, Spuhler J, et al. 2007. Virus movement maintains local virus population diversity. Proc. Natl. Acad. Sci. USA 104:19102–7 126. Sommer U, Padisak J, Reynolds CS, Juhasznagy P. 1993. Hutchinson heritage: the diversity-disturbance relationship in phytoplankton. Hydrobiologia 249:1–7 127. Strand MR, Burke GR. 2013. Polydnavirus-wasp associations: evolution, genome organization, and function. Curr. Opin. Virol. 3:587–94 128. Suttle CA. 2005. Viruses in the sea. Nature 437:356–61 129. Switzer WM, Salemi M, Shanmugam V, Gao F, Cong ME, et al. 2005. Ancient co-speciation of simian foamy viruses and primates. Nature 434:376–80 130. Symons RH. 1991. The intriguing viroids and virusoids: What is their information content and how did they evolve? Mol. Plant Microbe Interact. 4:111–21 131. Syvanen M. 2012. Evolutionary implications of horizontal gene transfer. Annu. Rev. Genet. 46:341–58 132. Szilagyi A, Zavodszky P. 2000. Structural differences between mesophilic, moderately thermophilic and extremely thermophilic protein subunits: results of a comprehensive survey. Structure 8:493–504 133. Tellier R. 2009. Aerosol transmission of influenza A virus: a review of new studies. J. R. Soc. Interface 6:S783–90 134. Thurber RV. 2009. Current insights into phage biodiversity and biogeography. Curr. Opin. Microbiol. 12:582–87 135. Tillmann HL, Heiken H, Knapik-Botor A, Heringlake S, Ockenga J, et al. 2001. Infection with GB virus C and reduced mortality among HIV-infected patients. N. Engl. J. Med. 345:715–24 136. Tortorella D, Gewurz BE, Furman MH, Schust DJ, Ploegh HL. 2000. Viral subversion of the immune system. Annu. Rev. Immunol. 18:861–926 137. Turner PE, Chao L. 1998. Sex and the evolution of intrahost competition in RNA virus ϕ6. Genetics 150:523–32 138. Uc-Mass A, Loeza Jacinto E, de la Garza M, Guarneros G, Hernández-Sánchez J, Kameyama L. 2004. An orthologue of the cor gene is involved in the exclusion of temperate lambdoid phages. Evidence that Cor inactivates FhuA receptor functions. Virology 329:425–33 139. van Baalen M, Sabelis MW. 1995. The dynamics of multiple infection and the evolution of virulence. Am. Nat. 146:881–910 140. Vica Pacheco S, Garc´ıa González O, Paniagua Contreras GL. 1997. The lom gene of bacteriophage λ is involved in Escherichia coli K12 adhesion to human buccal epithelial cells. FEMS Microbiol. Lett. 156:129–32 141. Wang I-N. 2006. Lysis timing and bacteriophage fitness. Genetics 172:17–26 142. Wanitchang A, Narkpuk J, Jaru-ampornpan P, Jengarn J, Jongkaewwattana A. 2012. Inhibition of influenza A virus replication by influenza B virus nucleoprotein: an insight into interference between influenza A and B viruses. Virology 432:194–203 143. Weinberger AD, Weinberger LS. 2013. Stochastic fate selection in HIV-infected patients. Cell 155:497– 99 Dennehy


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8 May 2014

16:34

144. Atmospheric virus diversity is inversely correlated with temperature and humidity and increases in winter.


144. Whon TW, Kim M-S, Roh SW, Shin N-R, Lee H-W, Bae J-W. 2012. Metagenomic characterization of airborne viral DNA diversity in the near-surface atmosphere. J. Virol. 86:8221–31 145. Wigginton KR, Kohn T. 2012. Virus disinfection mechanisms: the role of virus composition, structure, and function. Curr. Opin. Virol. 2:84–89 146. Williams HTP. 2013. Phage-induced diversification improves host evolvability. BMC Evol. Biol. 13:17 147. Woolhouse MEJ, Webster JP, Domingo E, Charlesworth B, Levin BR. 2002. Biological and biomedical implications of the co-evolution of pathogens and their hosts. Nat. Genet. 32:569–77 148. Wright A, McConnell M, Kanegasakai S. 1980. Lipopolysaccharide as a bacteriophage receptor. In Bacterial Viruses, ed. LL Randall, L Phillipson, pp. 27–57. London: Chapman Hall 149. Yang X, Forier K, Steukers L, van Vlierberghe S, Dubruel P, et al. 2012. Immobilization of pseudorabies virus in porcine tracheal respiratory mucus revealed by single particle tracking. PLoS ONE 7:e51054 150. Zinkernagel RM, Bachmann MF, Kundig TM, Oehen S, Pirchet H, Hengartner H. 1996. On immunological memory. Annu. Rev. Immunol. 14:333–67



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