Cross-kingdom co-occurrence networks in the plant microbiome: Importance and ecological interpretations

Microbial co-occurrence network analysis is being widely used for data exploration in plant microbiome research. Still, challenges lie in how well these microbial networks represent natural microbial communities and how well we can interpret and extract eco-evolutionary insights from the networks. Although many technical solutions have been proposed, in this perspective, we touch on the grave problem of kingdom-level bias in network representation and interpretation. We underscore the eco-evolutionary significance of using cross-kingdom (bacterial-fungal) co-occurrence networks to increase the network's representability of natural communities. To do so, we demonstrate how ecosystem-level interpretation of plant microbiome evolution changes with and without multi-kingdom analysis. Then, to overcome oversimplified interpretation of the networks stemming from the stereotypical dichotomy between bacteria and fungi, we recommend three avenues for ecological interpretation: (1) understanding dynamics and mechanisms of co-occurrence networks through generalized Lotka-Volterra and consumer-resource models, (2) finding alternative ecological explanations for individual negative and positive fungal-bacterial edges, and (3) connecting cross-kingdom networks to abiotic and biotic (host) environments.

Automated summary

Microbial co-occurrence network analysis is widely used in plant microbiome research, but challenges remain in representing natural microbial communities and extracting ecological and evolutionary insights from the networks. This perspective highlights the kingdom-level bias in network representation and interpretation, and suggests using cross-kingdom co-occurrence networks to increase representability. The paper also recommends three approaches for ecological interpretation to overcome oversimplified interpretation of the networks.