Trait-based meta-analysis of microbial guilds in the iron redox cycle

Iron redox reactions shape nutrient turnover, contaminant mobility, and primary productivity, yet the microbes driving these processes are often studied in isolation. By integrating decades of data into a trait-based guild framework, we reveal the ecophysiological diversity and niche differentiation of microbial iron redox cycling taxa across environments. Our synthesis exposes major gaps, such as limited trait data for >80% of dual-capacity Fe oxidizing/reducing species and highlights the need for functional trait surveys to complement metagenomics and cultivation efforts. The guild framework presented here advances predictive microbial ecology by linking metabolic traits with environmental gradients, offering a robust foundation for incorporating iron cycling into ecosystem models and biogeochemical forecasts.

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Publication Details

Journal
mSystems
Published
2026-01-26
DOI
https://doi.org/10.1128/msystems.01488-25
Primary Topic
Microbial Fuel Cells and Bioremediation
Type
article
Field-Weighted Citation Impact
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article

Trait-based meta-analysis of microbial guilds in the iron redox cycle

Sabrina Hedrich, Fernando Díaz-González, Francisco Issotta, Pedro Temporetti et al.
mSystems
Microbial Fuel Cells and Bioremediation
article

Trait-based meta-analysis of microbial guilds in the iron redox cycle

Sabrina Hedrich, Fernando Díaz-González, Francisco Issotta, Pedro Temporetti, Sofia Reyes-Impellizzeri, C Camila Rojas-Villalobos, D. Barrie Johnson
article en

Abstract

Iron redox reactions shape nutrient turnover, contaminant mobility, and primary productivity, yet the microbes driving these processes are often studied in isolation. By integrating decades of data into a trait-based guild framework, we reveal the ecophysiological diversity and niche differentiation of microbial iron redox cycling taxa across environments. Our synthesis exposes major gaps, such as limited trait data for >80% of dual-capacity Fe oxidizing/reducing species and highlights the need for functional trait surveys to complement metagenomics and cultivation efforts. The guild framework presented here advances predictive microbial ecology by linking metabolic traits with environmental gradients, offering a robust foundation for incorporating iron cycling into ecosystem models and biogeochemical forecasts.

mSystemsVol. 11(2)
Universidad Mayor (CL), Natural History Museum (GB), Bangor University (GB), San Sebastián University (CL), Centro Científico Tecnológico - Patagonia Norte (AR), TU Bergakademie Freiberg (DE), Coventry University (GB)
Life in Land
Openalex Percentile: Top 80%
Microbial Fuel Cells and Bioremediation
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