ArticleScientific reports2020
A network-based approach to deciphering a dynamic microbiome's response to a subtle perturbation.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Bioenergetically constrained dynamical microbial interactions govern the performance and stability of methane-producing bioreactors.NPJ biofilms and microbiomes · 2025Article
- Variations in the Bacterial, Fungal, and Protist Communities and Their Interactions Within Sediment Affected by the Benthic Organism, SnailMicroorganisms · 2024Article
- Disruption of bacterial interactions and community assembly in Babesia-infected Haemaphysalis longicornis following antibiotic treatment.BMC microbiology · 2024Article
- Deciphering the role of rhizosphere microbiota in modulating disease resistance in cabbage varieties.Microbiome · 2024Article
- Influences of the Integrated Rice-Crayfish Farming System with Different Stocking Densities on the Paddy Soil Microbiomes.International journal of molecular sciences · 2024Article
- Differential microbial assemblages associated with shikonin-producing Borage species in two distinct soil types.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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Abstract
Over the past decades, one main issue that has emerged in ecological and environmental research is how losses in biodiversity influence ecosystem dynamics and functioning, and consequently human society. Although biodiversity is a common indicator of ecosystem functioning, it is difficult to measure biodiversity in microbial communities exposed to subtle or chronic environmental perturbations. Consequently, there is a need for alternative bioindicators to detect, measure, and monitor gradual changes in microbial communities against these slight, chronic, and continuous perturbations. In this study, microbial networks before and after subtle perturbations by adding S. acidaminiphila showed diverse topological niches and 4-node motifs in which microbes with co-occurrence patterns played the central roles in regulating and adjusting the intertwined relationships among microorganisms in response to the subtle environmental changes. This study demonstrates that microbial networks are a good bioindicator for chronic perturbation and should be applied in a variety of ecological investigations.
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Registered trials
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