Dataset Information

Scale dependencies and generalism in host use shape virus prevalence.

ABSTRACT: Processes that generate the distribution of pathogens and their interactions with hosts are not insensitive to changes in spatial scale. Spatial scales and species traits are often selected intentionally, based on practical considerations, ignoring biases that the scale and type of observation may introduce. Specifically, these biases might change the interpretation of disease-diversity relationships that are reported as either 'dilution' or 'amplification' effects. Here, we combine field data of a host-pathogen community with empirical models to test the effects that (i) spatial scale and (ii) host range have on the relationship between plant-virus infection prevalence and diversity. We show that prevalence-diversity relationships are scale-dependent and can produce opposite effects associated with different habitats at sub-ecosystem scales. The total number of host species of each virus reflected generalism at the ecosystem scale. However, plasticity in host range resembled habitat-specific specialization and also changed model predictions. We show that habitat heterogeneity, ignored at larger (ecosystem) spatial scales, influences pathogen distributions. Hence, understanding disease distributions and the evolution of pathogens requires reconciling specific hypotheses of the study with an appropriate spatial scale, or scales, and consideration of traits, such as host range, that might strongly contribute to biotic interactions.

SUBMITTER: McLeish M

PROVIDER: S-EPMC5745412 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Scale dependencies and generalism in host use shape virus prevalence.

McLeish Michael M Sacristán Soledad S Fraile Aurora A García-Arenal Fernando F

Proceedings. Biological sciences 20171201 1869

Processes that generate the distribution of pathogens and their interactions with hosts are not insensitive to changes in spatial scale. Spatial scales and species traits are often selected intentionally, based on practical considerations, ignoring biases that the scale and type of observation may introduce. Specifically, these biases might change the interpretation of disease-diversity relationships that are reported as either 'dilution' or 'amplification' effects. Here, we combine field data o ...[more]

PMID: 29263286

Similar Datasets

Project description:Recent functional genomics studies including genome-wide small interfering RNA (siRNA) screens demonstrated that hepatitis C virus (HCV) exploits an extensive network of host factors for productive infection and propagation. How these co-opted host functions interact with various steps of HCV replication cycle and exert pro- or antiviral effects on HCV infection remains largely undefined. Here we present an unbiased and systematic strategy to functionally interrogate HCV host dependencies uncovered from our previous infectious HCV (HCVcc) siRNA screen. Applying functional genomics approaches and various in vitro HCV model systems, including HCV pseudoparticles (HCVpp), single-cycle infectious particles (HCVsc), subgenomic replicons, and HCV cell culture systems (HCVcc), we identified and characterized novel host factors or pathways required for each individual step of the HCV replication cycle. Particularly, we uncovered multiple HCV entry factors, including E-cadherin, choline kinase α, NADPH oxidase CYBA, Rho GTPase RAC1 and SMAD family member 6. We also demonstrated that guanine nucleotide binding protein GNB2L1, E2 ubiquitin-conjugating enzyme UBE2J1, and 39 other host factors are required for HCV RNA replication, while the deubiquitinating enzyme USP11 and multiple other cellular genes are specifically involved in HCV IRES-mediated translation. Families of antiviral factors that target HCV replication or translation were also identified. In addition, various virologic assays validated that 66 host factors are involved in HCV assembly or secretion. These genes included insulin-degrading enzyme (IDE), a proviral factor, and N-Myc down regulated Gene 1 (NDRG1), an antiviral factor. Bioinformatics meta-analyses of our results integrated with literature mining of previously published HCV host factors allows the construction of an extensive roadmap of cellular networks and pathways involved in the complete HCV replication cycle. This comprehensive study of HCV host dependencies yields novel insights into viral infection, pathogenesis and potential therapeutic targets.

Dataset Information

Scale dependencies and generalism in host use shape virus prevalence.

Publications

Scale dependencies and generalism in host use shape virus prevalence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets