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Potential parasite transmission in multi-host networks based on parasite sharing.

Pilosof S, Morand S, Krasnov BR, Nunn CL - PLoS ONE (2015)

Bottom Line: This suggests that phylogeny affects patterns of parasite sharing, which was confirmed in analyses showing that it predicted affiliation of individuals to modules.The centrality of individuals in these networks differed between multi- and single-species networks, with species identity and individual characteristics influencing their position in the networks.Simulations further revealed that parasite dynamics differed between multi- and single-species networks.

View Article: PubMed Central - PubMed

Affiliation: Mitrani Department of Desert Ecology, Albert Katz International School for Desert Studies, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel.

ABSTRACT
Epidemiological networks are commonly used to explore dynamics of parasite transmission among individuals in a population of a given host species. However, many parasites infect multiple host species, and thus multi-host networks may offer a better framework for investigating parasite dynamics. We investigated the factors that influence parasite sharing--and thus potential transmission pathways--among rodent hosts in Southeast Asia. We focused on differences between networks of a single host species and networks that involve multiple host species. In host-parasite networks, modularity (the extent to which the network is divided into subgroups of rodents that interact with similar parasites) was higher in the multi-species than in the single-species networks. This suggests that phylogeny affects patterns of parasite sharing, which was confirmed in analyses showing that it predicted affiliation of individuals to modules. We then constructed "potential transmission networks" based on the host-parasite networks, in which edges depict the similarity between a pair of individuals in the parasites they share. The centrality of individuals in these networks differed between multi- and single-species networks, with species identity and individual characteristics influencing their position in the networks. Simulations further revealed that parasite dynamics differed between multi- and single-species networks. We conclude that multi-host networks based on parasite sharing can provide new insights into the potential for transmission among hosts in an ecological community. In addition, the factors that determine the nature of parasite sharing (i.e. structure of the host-parasite network) may impact transmission patterns.

No MeSH data available.


Related in: MedlinePlus

Differences between multi- and single-species networks.Differences are in characteristics that determine co-occurrence in modules and centrality of individuals (rows) for three localities (columns). (A-C) The z-score-standardized coefficients of a multiple-regression on matrices procedure. (D-F) The importance of coefficients calculated from a multi-model inference procedure as the sum of model weights across all the models in which the coefficient appears (see S1 Table). In A-C ‘phylogeny’ is the taxonomic distance between two individuals. In D-F ‘species’ is a factor depicting rodent species identity. BM—body mass; RSM—relative spleen mass to body mass. Note that: (i) in Buriram the single-species network was not analyzed because it was not statistically significantly modular; (ii) RSM was not included in the analyses in Mondolkiri due to an excess of missing cases; (iii) Statistical significance is relevant only for A-C.
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pone.0117909.g002: Differences between multi- and single-species networks.Differences are in characteristics that determine co-occurrence in modules and centrality of individuals (rows) for three localities (columns). (A-C) The z-score-standardized coefficients of a multiple-regression on matrices procedure. (D-F) The importance of coefficients calculated from a multi-model inference procedure as the sum of model weights across all the models in which the coefficient appears (see S1 Table). In A-C ‘phylogeny’ is the taxonomic distance between two individuals. In D-F ‘species’ is a factor depicting rodent species identity. BM—body mass; RSM—relative spleen mass to body mass. Note that: (i) in Buriram the single-species network was not analyzed because it was not statistically significantly modular; (ii) RSM was not included in the analyses in Mondolkiri due to an excess of missing cases; (iii) Statistical significance is relevant only for A-C.

Mentions: After determining the modular structure of the networks, we tested the effect of individual- and population-level characteristics on the affiliation of individuals to modules (module composition) with a logistic multiple regression on distance matrices (MRM), following [26] (S1 Methods). The phylogenetic distance between individuals was a significant predictor of affiliation to modules in Buriram and Sihanouk (but not in Mondolkiri): the closer two individuals were phylogenetically, the more likely that they occurred in the same module (Fig. 2A,C). Other characteristics like habitat and body mass were also significant predictors of the affiliation of individuals to modules in the multi-species networks of Buriram (Fig. 2A) and Sihanouk (Fig. 2C). The importance of individual-level characteristics became even more evident when we pre-determined module composition by taxonomy. In that analysis, the value of M was much lower than when obtained through simulated annealing (Table 1).


Potential parasite transmission in multi-host networks based on parasite sharing.

Pilosof S, Morand S, Krasnov BR, Nunn CL - PLoS ONE (2015)

Differences between multi- and single-species networks.Differences are in characteristics that determine co-occurrence in modules and centrality of individuals (rows) for three localities (columns). (A-C) The z-score-standardized coefficients of a multiple-regression on matrices procedure. (D-F) The importance of coefficients calculated from a multi-model inference procedure as the sum of model weights across all the models in which the coefficient appears (see S1 Table). In A-C ‘phylogeny’ is the taxonomic distance between two individuals. In D-F ‘species’ is a factor depicting rodent species identity. BM—body mass; RSM—relative spleen mass to body mass. Note that: (i) in Buriram the single-species network was not analyzed because it was not statistically significantly modular; (ii) RSM was not included in the analyses in Mondolkiri due to an excess of missing cases; (iii) Statistical significance is relevant only for A-C.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4352066&req=5

pone.0117909.g002: Differences between multi- and single-species networks.Differences are in characteristics that determine co-occurrence in modules and centrality of individuals (rows) for three localities (columns). (A-C) The z-score-standardized coefficients of a multiple-regression on matrices procedure. (D-F) The importance of coefficients calculated from a multi-model inference procedure as the sum of model weights across all the models in which the coefficient appears (see S1 Table). In A-C ‘phylogeny’ is the taxonomic distance between two individuals. In D-F ‘species’ is a factor depicting rodent species identity. BM—body mass; RSM—relative spleen mass to body mass. Note that: (i) in Buriram the single-species network was not analyzed because it was not statistically significantly modular; (ii) RSM was not included in the analyses in Mondolkiri due to an excess of missing cases; (iii) Statistical significance is relevant only for A-C.
Mentions: After determining the modular structure of the networks, we tested the effect of individual- and population-level characteristics on the affiliation of individuals to modules (module composition) with a logistic multiple regression on distance matrices (MRM), following [26] (S1 Methods). The phylogenetic distance between individuals was a significant predictor of affiliation to modules in Buriram and Sihanouk (but not in Mondolkiri): the closer two individuals were phylogenetically, the more likely that they occurred in the same module (Fig. 2A,C). Other characteristics like habitat and body mass were also significant predictors of the affiliation of individuals to modules in the multi-species networks of Buriram (Fig. 2A) and Sihanouk (Fig. 2C). The importance of individual-level characteristics became even more evident when we pre-determined module composition by taxonomy. In that analysis, the value of M was much lower than when obtained through simulated annealing (Table 1).

Bottom Line: This suggests that phylogeny affects patterns of parasite sharing, which was confirmed in analyses showing that it predicted affiliation of individuals to modules.The centrality of individuals in these networks differed between multi- and single-species networks, with species identity and individual characteristics influencing their position in the networks.Simulations further revealed that parasite dynamics differed between multi- and single-species networks.

View Article: PubMed Central - PubMed

Affiliation: Mitrani Department of Desert Ecology, Albert Katz International School for Desert Studies, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel.

ABSTRACT
Epidemiological networks are commonly used to explore dynamics of parasite transmission among individuals in a population of a given host species. However, many parasites infect multiple host species, and thus multi-host networks may offer a better framework for investigating parasite dynamics. We investigated the factors that influence parasite sharing--and thus potential transmission pathways--among rodent hosts in Southeast Asia. We focused on differences between networks of a single host species and networks that involve multiple host species. In host-parasite networks, modularity (the extent to which the network is divided into subgroups of rodents that interact with similar parasites) was higher in the multi-species than in the single-species networks. This suggests that phylogeny affects patterns of parasite sharing, which was confirmed in analyses showing that it predicted affiliation of individuals to modules. We then constructed "potential transmission networks" based on the host-parasite networks, in which edges depict the similarity between a pair of individuals in the parasites they share. The centrality of individuals in these networks differed between multi- and single-species networks, with species identity and individual characteristics influencing their position in the networks. Simulations further revealed that parasite dynamics differed between multi- and single-species networks. We conclude that multi-host networks based on parasite sharing can provide new insights into the potential for transmission among hosts in an ecological community. In addition, the factors that determine the nature of parasite sharing (i.e. structure of the host-parasite network) may impact transmission patterns.

No MeSH data available.


Related in: MedlinePlus