Statistical structure of host–phage interactions

Flores, Cesar O.; Meyer, Justin R.; Valverde, Sergi; Farr, Lauren; Weitz, Joshua S.

doi:10.1073/pnas.1101595108

Cited by 296 publications

(377 citation statements)

References 103 publications

(88 reference statements)

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“…At small phylogenetic scales, these networks typically show higher than expected nestedness and lower than expected modularity [22]. High nestedness is consistent with an arms race mode of coevolution, where hosts and phages evolve to increase their range of resistance/infectivity.…”

Section: Introductionmentioning

confidence: 64%

Coevolutionary diversification creates nested-modular structure in phage–bacteria interaction networks

Beckett

Williams

2013

Interface Focus.

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One contribution of 11 to a Theme Issue 'Modelling biological evolution: recent progress, current challenges and future direction'. Phage and their bacterial hosts are the most diverse and abundant biological entities in the oceans, where their interactions have a major impact on marine ecology and ecosystem function. The structure of interaction networks for natural phage-bacteria communities offers insight into their coevolutionary origin. At small phylogenetic scales, observed communities typically show a nested structure, in which both hosts and phages can be ranked by their range of resistance and infectivity, respectively. A qualitatively different multi-scale structure is seen at larger phylogenetic scales; a natural assemblage sampled from the Atlantic Ocean displays large-scale modularity and local nestedness within each module. Here, we show that such 'nested-modular' interaction networks can be produced by a simple model of host-phage coevolution in which infection depends on genetic matching. Negative frequencydependent selection causes diversification of hosts (to escape phages) and phages (to track their evolving hosts). This creates a diverse community of bacteria and phage, maintained by kill-the-winner ecological dynamics. When the resulting communities are visualized as bipartite networks of who infects whom, they show the nested-modular structure characteristic of the Atlantic sample. The statistical significance and strength of this observation varies depending on whether the interaction networks take into account the density of the interacting strains, with implications for interpretation of interaction networks constructed by different methods. Our results suggest that the apparently complex community structures associated with marine bacteria and phage may arise from relatively simple coevolutionary origins.

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Section: Introductionmentioning

confidence: 64%

Coevolutionary diversification creates nested-modular structure in phage–bacteria interaction networks

Beckett

Williams

2013

Interface Focus.

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“…However, this effect was rather marginal, and the molecular mechanism of interaction between PVY and plants carrying recessive resistance alleles does not correspond to an elicitor-receptor interaction triggering specific plant defenses, as usually considered in the GFG model (3). It should be noted, however, that nested, but not modular, patterns of interaction were frequently detected in phage-bacteria interactions (29) and could be a rather general pattern of interaction.…”

Section: Discussionmentioning

confidence: 91%

Interaction Patterns betweenPotato Virus Yand eIF4E-Mediated Recessive Resistance in the Solanaceae

Moury¹,

Janzac

Ruellan³

et al. 2014

J Virol

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The structural pattern of infectivity matrices, which contains infection data resulting from inoculations of a set of hosts by a set of parasites, is a key parameter for our understanding of biological interactions and their evolution. This pattern determines the evolution of parasite pathogenicity and host resistance, the spatiotemporal distribution of host and parasite genotypes, and the efficiency of disease control strategies. Two major patterns have been proposed for plant-virus genotype infectivity matrices. In the gene-for-gene model, infectivity matrices show a nested pattern, where the host ranges of specialist virus genotypes are subsets of the host ranges of less specialized viruses. In contrast, in the matching-allele (MA) model, each virus genotype is specialized to infect one (or a small set of) host genotype(s). The corresponding infectivity matrix shows a modular pattern where infection is frequent for plants and viruses belonging to the same module but rare for those belonging to different modules. We analyzed the structure of infectivity matrices between Potato virus Y (PVY) and plant genotypes in the family Solanaceae carrying different eukaryotic initiation factor 4E (eIF4E)-coding alleles conferring recessive resistance. Whereas this system corresponds mechanistically to an MA model, the expected modular pattern was rejected based on our experimental data. This was mostly because PVY mutations involved in adaptation to a particular plant genotype displayed frequent pleiotropic effects, conferring simultaneously an adaptation to additional plant genotypes with different eIF4E alleles. Such effects should be taken into account for the design of strategies of sustainable control of PVY through plant varietal mixtures or rotations. IMPORTANCEThe interaction pattern between host and virus genotypes has important consequences on their respective evolution and on issues regarding the application of disease control strategies. We found that the structure of the interaction between Potato virus Y (PVY) variants and host plants in the family Solanaceae departs significantly from the current model of interaction considered for these organisms because of frequent pleiotropic effects of virus mutations. These mutational effects allow the virus to expand rapidly its range of host plant genotypes, make it very difficult to predict the effects of mutations in PVY infectivity factors, and raise concerns about strategies of sustainable management of plant genetic resistance to viruses. T he interaction pattern between host and parasite genotypes has important consequences on their respective evolution and on issues regarding the application of disease control strategies. This pattern determines to a large extent the maintenance of genetic diversity in host and parasite populations (1), the structure of these populations in space and time (2, 3), and the evolution of parasite pathogenicity and host resistance (4).Different models of host-parasite interaction and coevolution have been proposed (3, 5) (F...

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“…In doing so, we highlight multiple priorities. First, it is essential to extend the current model to link increasingly strain-resolved information on microbial and viral diversity (Breitbart et al, 2002;Edwards and Rohwer, 2005;Allen et al, 2011) and interactions between viruses and their hosts (Flores et al, 2011;Deng et al, 2012;Weitz et al, 2013) the aggregated representation of virus-host interactions and nutrient feedbacks presented here (see the example of a calibrated model for dynamics including viruses of the algae Phaeocystis globosa; Ruardij et al, 2005). Strain-specific interactions also include the change in host physiology that occurs during infection, whether preceding lysis (Lindell et al, 2007;Ankrah et al, 2014) or during long-term associations with hosts, for example, lysogeny (McDaniel et al, 2008).…”

Section: Resultsmentioning

confidence: 99%

A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes

et al. 2015

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Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles.

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Statistical structure of host–phage interactions

Cited by 296 publications

References 103 publications

Coevolutionary diversification creates nested-modular structure in phage–bacteria interaction networks

Coevolutionary diversification creates nested-modular structure in phage–bacteria interaction networks

Interaction Patterns betweenPotato Virus Yand eIF4E-Mediated Recessive Resistance in the Solanaceae

A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes

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