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Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance
- Source :
- Nature Communications, Nature Communications, Nature Publishing Group, 2020, 11 (1), ⟨10.1038/s41467-020-19006-2⟩, Nature Communications, Vol 11, Iss 1, Pp 1-14 (2020)
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.<br />Herold et al. present an integrated meta-omics framework to investigate how mixed microbial communities, such as oleaginous bacterial populations in biological wastewater treatment plants, respond with distinct adaptation strategies to disturbances. They show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity.
- Subjects :
- Water microbiology
Proteomics
0301 basic medicine
meta-metabolomics
Microbiologie [F11] [Sciences du vivant]
Time Factors
General Physics and Astronomy
Wastewater
Microbial ecology
Bioreactors
Dynamical systems
activated sludge
Microbiology [F11] [Life sciences]
lcsh:Science
ComputingMilieux_MISCELLANEOUS
[SDV.EE]Life Sciences [q-bio]/Ecology, environment
metatranscriptomics
Multidisciplinary
Microbiota
Community structure
[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]
6. Clean water
metaproteomics
Science
030106 microbiology
Niche
Biology
Article
General Biochemistry, Genetics and Molecular Biology
03 medical and health sciences
[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN]
Metabolomics
ecological niche
wastewater
Ecosystem
Ecological niche
metagenomics
Phenotypic plasticity
Bacteria
Resistance (ecology)
General Chemistry
15. Life on land
030104 developmental biology
13. Climate action
Evolutionary biology
Metagenomics
Metaproteomics
Metagenome
lcsh:Q
lipid accumulating organisms
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
time series
Adaptation
Subjects
Details
- ISSN :
- 20411723
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Nature Communications
- Accession number :
- edsair.doi.dedup.....8a508d5887429a06c8acf64388295318
- Full Text :
- https://doi.org/10.1038/s41467-020-19006-2