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Environmental sensing capacity predicts bacterial ecological strategies and environmental preferences

Created on 04 Sep 2026

Authors

Altxu, R. S., Shankar, G., Comas-Pujol, A., Francesch-Vazquez, A., Pascual-Garcia, A., Krell, T., Ramoneda, J.

Abstract

The ability to sense environmental variation is a prerequisite for ecological success. Sensor domains enable bacteria to detect nutrients, neighboring organisms, and physicochemical conditions, but whether variation in these sensing systems reflects ecological specialization remains unresolved. Here, we analyzed sensor domains across 51,343 bacterial genomes and 255 soil metagenomes spanning a climatic gradient to determine whether sensory repertoires encode bacterial ecological strategies and environmental preferences. Sensory repertoires exhibited strong phylogenetic conservatism and revealed signatures of genome streamlining, indicating that environmental sensing reflects trade-offs associated with maintaining sensory complexity. Taxa occupying environmentally heterogeneous habitats, particularly free-living aerobic generalists, encoded the largest sensory repertoires, consistent with selection for expanded environmental information processing. To link sensory function with ecological adaptation, we mapped experimentally-characterized ligand-binding motifs (LBMs) across genomes and metagenomes. Distinct LBM profiles discriminated host-associated and free-living taxa, aerobic and anaerobic lineages, and generalists and non-generalists, revealing a tight coupling between sensory capacity and ecological strategy. Across soil communities, motifs associated with osmoprotection and oxygen sensing were consistently enriched under increasing aridity, linking sensory function to environmental filtering in natural ecosystems. These findings identify environmental sensing as an important organizational axis of bacterial trait-based ecology that integrates evolutionary history, ecological lifestyle, and adaptation to local conditions. Environmental sensing should be considered for predicting microbial niches and responses to environmental change.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 04 Sep 2026.

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