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A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

Association and host selectivity in multi-host pathogens

José M Malpica1, Soledad Sacristán, Aurora Fraile

  • 1Departamento de Biotecnología, Instituto Nacional de Investigación Agraria y Alimentaria, Madrid, Spain.

Plos One
|December 22, 2006
PubMed

Insights

This study introduces new methods to analyze pathogen distribution and co-infection in wild plants. Findings reveal significant host-pathogen associations, indicating host specialization is a successful strategy for multi-host pathogens.

Area of Science:

  • Ecology
  • Pathogen Biology
  • Plant Virology

Background:

  • Pathogen distribution across hosts impacts population dynamics and evolution.
  • Host co-infection can drive host and pathogen evolution, including co-evolution.
  • Understanding non-random pathogen distribution is crucial for ecological and evolutionary studies.

Purpose of the Study:

  • To develop and test indices for analyzing host-pathogen infection and co-infection patterns.
  • To determine if observed pathogen distributions are random or indicative of specific associations.
  • To investigate host-virus associations and the prevalence of host specialization in multi-host pathogens.

Main Methods:

  • Proposed novel indices to quantify host infection and co-infection patterns.
  • Developed statistical tests to assess deviations from random distribution.
  • Applied methods to analyze the prevalence of five plant viruses across 21 wild plant species.

Main Results:

  • Evidence of significant host-virus associations, with hosts and viruses showing selectivity.
  • More host-selective viruses were found to be more prevalent.
  • Observed a positive association between viruses in co-infected hosts.

Conclusions:

  • Host specialization appears to be a successful strategy for multi-host plant pathogens.
  • Developed tools can analyze pathogen associations across diverse host-pathogen systems.
  • Findings aid in understanding and modeling the population biology of multi-host pathogens.

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