Structure and co-occurrence patterns in microbial communities under acute environmental stress reveal ecological factors fostering resilience.
Dinka MandakovicClaudia RojasJonathan MaldonadoMauricio LatorreDante TravisanyErwan DelageAudrey BihouéeGéraldine JeanFrancisca P DíazBeatriz Fernández-GómezPablo CabreraAlexis GaeteClaudio LatorreRodrigo A GutiérrezAlejandro MaassVerónica CambiazoSergio A NavarreteDamien EveillardMauricio GonzálezPublished in: Scientific reports (2018)
Understanding the factors that modulate bacterial community assembly in natural soils is a longstanding challenge in microbial community ecology. In this work, we compared two microbial co-occurrence networks representing bacterial soil communities from two different sections of a pH, temperature and humidity gradient occurring along a western slope of the Andes in the Atacama Desert. In doing so, a topological graph alignment of co-occurrence networks was used to determine the impact of a shift in environmental variables on OTUs taxonomic composition and their relationships. We observed that a fraction of association patterns identified in the co-occurrence networks are persistent despite large environmental variation. This apparent resilience seems to be due to: (1) a proportion of OTUs that persist across the gradient and maintain similar association patterns within the community and (2) bacterial community ecological rearrangements, where an important fraction of the OTUs come to fill the ecological roles of other OTUs in the other network. Actually, potential functional features suggest a fundamental role of persistent OTUs along the soil gradient involving nitrogen fixation. Our results allow identifying factors that induce changes in microbial assemblage configuration, altering specific bacterial soil functions and interactions within the microbial communities in natural environments.
Keyphrases
- human health
- microbial community
- climate change
- risk assessment
- antibiotic resistance genes
- social support
- mental health
- heavy metals
- liver failure
- minimally invasive
- dna methylation
- magnetic resonance imaging
- depressive symptoms
- genome wide
- deep learning
- machine learning
- respiratory failure
- diffusion weighted imaging