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Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
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Resistant microbial cooccurrence patterns inferred by network topology.

Sari Peura1, Stefan Bertilsson2, Roger I Jones3

  • 1Department of Ecology and Genetics, Limnology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden University of Jyväskylä, Department of Biological and Environmental Science, Jyväskylä, Finland.

Applied and Environmental Microbiology
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Summary
This summary is machine-generated.

Microbial cooccurrence networks reveal system-relevant interdependencies. Network topology, characterized by hubs and bottlenecks, indicates microbial community stability and resistance to disturbances.

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Area of Science:

  • Microbial ecology
  • Ecological network analysis
  • Ecosystem stability

Background:

  • Complex cooccurrence patterns among microbes are known but rarely linked to ecosystem functioning and stability.
  • Understanding these patterns is crucial for predicting ecosystem health.

Purpose of the Study:

  • To construct and analyze microbial cooccurrence networks from aquatic ecosystems.
  • To determine if network topology can serve as an indicator of ecosystem stability.

Main Methods:

  • Species cooccurrence data were extracted from five aquatic time series (dystrophic lake, eutrophic lake, open ocean).
  • Network properties (clustering coefficient, path length, node degree, betweenness) were calculated and compared to random networks.
  • Simulations assessed the impact of removing 'hubs' and 'bottlenecks' on network resistance.

Main Results:

  • Microbial cooccurrence networks exhibited significantly higher clustering coefficients, shorter path lengths, higher average node degrees, and greater betweenness than random networks.
  • Hubs and bottlenecks, identified as taxa with numerous cooccurrences at convergence points, confer resistance to random taxa removal.
  • These network topology features suggest inherent stability in microbial communities.

Conclusions:

  • System-relevant interdependencies, represented by hubs and bottlenecks, are key determinants of microbial cooccurrence network topology.
  • Network topology features indicate that microbial community dynamics are resistant over time.
  • Cooccurrence network analysis can provide valuable indicators for assessing ecosystem stability.