Microbiome networks: A systems framework for identifying candidate microbial assemblages for disease management

R. Poudel, A. Jumpponen, D. C. Schlatter, T. C. Paulitz, B. B. McSpadden Gardener, L. L. Kinkel, K. A. Garrett

Research output: Contribution to journalArticlepeer-review

219 Scopus citations


Network models of soil and plant microbiomes provide new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how observed network structures can be used to generate testable hypotheses about candidate microbes affecting plant health. The framework includes four types of network analyses. "General network analysis" identifies candidate taxa for maintaining an existing microbial community. "Host-focused analysis" includes a node representing a plant response such as yield, identifying taxa with direct or indirect associations with that node. "Pathogenfocused analysis" identifies taxa with direct or indirect associations with taxa known a priori as pathogens. "Disease-focused analysis" identifies taxa associated with disease. Positive direct or indirect associations with desirable outcomes, or negative associations with undesirable outcomes, indicate candidate taxa. Network analysis provides characterization not only of taxa with direct associations with important outcomes such as disease suppression, biofertilization, or expression of plant host resistance, but also taxa with indirect associations via their association with other key taxa. We illustrate the interpretation of network structure with analyses of microbiomes in the oak phyllosphere, and in wheat rhizosphere and bulk soil associated with the presence or absence of infection by Rhizoctonia solani.

Original languageEnglish (US)
Pages (from-to)1083-1096
Number of pages14
Issue number10
StatePublished - Oct 2016

Bibliographical note

Publisher Copyright:
© 2016 The American Phytopathological Society.


  • Biocontrol
  • Networks
  • Phytobiome
  • Quercus macrocarpa
  • Triticum aestivum

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.


Dive into the research topics of 'Microbiome networks: A systems framework for identifying candidate microbial assemblages for disease management'. Together they form a unique fingerprint.

Cite this