Physics

Microbiome

Niche

Inference

Bioinformatics

Evolutionary biology

Biology

Ecological niche

Machine learning

Paleontology

Habitat

Artificial intelligence

Ecology

Data science

Biological network

Context (archaeology)

Modularity (biology)

Computer science

Quantum mechanics

Computational biology

Network analysis

Spurious relationship

FEMS Microbiology Reviews

Microbial networks are an increasingly popular tool to investigate microbial community structure, as they integrate multiple types of information and may represent systems-level behaviour. Interpreting these networks is not straightforward, and the biological implications of network properties are unclear. Analysis of microbial networks allows researchers to predict hub species and species interactions. Additionally, such analyses can help identify alternative community states and niches. Here, we review factors that can result in spurious predictions and address emergent properties that may be meaningful in the context of the microbiome. We also give an overview of studies that analyse microbial networks to identify new hypotheses. Moreover, we show in a simulation how network properties are affected by tool choice and environmental factors. For example, hub species are not consistent across tools, and environmental heterogeneity induces modularity. We highlight the need for robust microbial network inference and suggest strategies to infer networks more reliably.

From hairballs to hypotheses–biological insights from microbial networks