Inhibitory interaction networks among coevolved Streptomyces populations from prairie soils

Daniel C. Schlatter, Zewei Song, Patricia Vaz-Jauri, Linda L. Kinkel

Research output: Contribution to journalArticlepeer-review

Abstract

Soil microbes live within highly complex communities, where community composition, function, and evolution are the product of diverse interactions among community members. Analysis of the complex networks of interactions within communities has the potential to shed light on community stability, functioning, and evolution. However, we have little understanding of the variation in interaction networks among coevolved soil populations. We evaluated networks of antibiotic inhibitory interactions among sympatric Streptomyces communities from prairie soil. Inhibition networks differed significantly in key network characteristics from expectations under null models, largely reflecting variation among Streptomyces in the number of sympatric populations that they inhibited. Moreover, networks of inhibitory interactions within Streptomyces communities differed significantly from each other, suggesting unique network structures among soil communities from different locations. Analyses of tri-partite interactions (triads) showed that some triads were significantly over- or under- represented, and that communities differed in ‘preferred’ triads. These results suggest that local processes generate distinct structures among sympatric Streptomyces inhibition networks in soil. Understanding the properties of microbial interaction networks that generate competitive and functional capacities of soil communities will shed light on the ecological and coevolutionary history of sympatric populations, and provide a foundation for more effective management of inhibitory capacities of soil microbial communities.

Original languageEnglish (US)
Article numbere0223779
JournalPloS one
Volume14
Issue number10
DOIs
StatePublished - Oct 2019

Bibliographical note

Funding Information:
This work was supported by the United States Department of Agriculture (U.S.D.A.) Microbial Observatories Grant 2006-35319-17445, NSF Microbial Observatories Program (Grant 9977907), U.S.D.A. NIFA Grant 2011-67019-30330, and NSF Long-Term Ecological Research Program (DEB-0080382) to LLK. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. We gratefully acknowledge Anita Baines, Jen Flor, Dale Johnson, Erica Marti, and Kun Xiao for careful sampling, isolation, and phenotypic analysis of Streptomyces strains used in this work and Lindsey Hanson for continued technical support and critical feedback. This work was supported by the United States Department of Agriculture (U.S.D.A.) Microbial Observatories Grant 2006-35319-17445, NSF Microbial Observatories Program (Grant 9977907), U.S. D.A. NIFA Grant 2011-67019-30330, and NSF Long-Term Ecological Research Program (DEB-0080382) to LLK. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Funding Information:
Funding:ThisworkwassupportedbytheUnited StatesDepartmentofAgriculture(U.S.D.A.) MicrobialObservatoriesGrant2006-35319-17445, NSFMicrobialObservatoriesProgram(Grant 9977907),U.S.D.A.NIFAGrant2011-67019-30330,andNSFLong-TermEcologicalResearch Program(DEB-0080382)toLLK.Thefundershad noroleinthestudydesign,datacollectionand

Publisher Copyright:
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Fingerprint Dive into the research topics of 'Inhibitory interaction networks among coevolved Streptomyces populations from prairie soils'. Together they form a unique fingerprint.

Cite this