Microbial niche nexus sustaining biological wastewater treatment

Wu, Guangxue; Yin, Qidong

doi:10.1038/s41545-020-00080-4

Cited by 38 publications

(15 citation statements)

References 36 publications

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“…Activated sludge processes are the most applied wastewater treatment system, involving highly diverse microbial communities. The operational functioning of wastewater treatment plants (WWTPs) promotes a niche differentiation in the system, needed for the simultaneous carbon, nitrogen, and phosphorous removal, among other contaminants 1 , 2 . Thus, it is essential to understand the structure and assembly of these communities to ensure an optimal operation of WWTPs 3 .…”

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confidence: 99%

Niche differentiation drives microbial community assembly and succession in full-scale activated sludge bioreactors

Celis

Duque

Marquina

et al. 2022

npj Biofilms Microbiomes

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Network models and community phylogenetic analyses are applied to assess the composition, structure, and ecological assembly mechanisms of microbial communities. Here we combine both approaches to investigate the temporal dynamics of network properties in individual samples of two activated sludge systems at different adaptation stages. At initial assembly stages, we observed microbial communities adapting to activated sludge, with an increase in network modularity and co-exclusion proportion, and a decrease in network clustering, here interpreted as a consequence of niche specialization. The selective pressure of deterministic factors at wastewater treatment plants produces this trend and maintains the structure of highly functional and specialized communities responding to seasonal environmental changes.

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mentioning

confidence: 99%

Niche differentiation drives microbial community assembly and succession in full-scale activated sludge bioreactors

Celis

Duque

Marquina

et al. 2022

npj Biofilms Microbiomes

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“…The BNRdb database incorporates BNR-associated genes/strains, BNR treatment experimental datasets and metagenomic datasets from BNR engineered systems and diverse environments. Natural environments such as intertidal zones, where the oxic/anoxic conditions vary through time, are valuable microbial sources for discovering novel BNR metabolic pathways and microbial functions [39,40]. Users can thus access the BNR information from natural environments held within the BNRdb to evaluate the real applicability of novel BNR microbial strains in the optimization of BNR treatment systems.…”

Section: Discussionmentioning

confidence: 99%

Biological Nitrogen Removal Database: A Manually Curated Data Resource

2022

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Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and function of BNR microbial communities and optimizing BNR treatment systems to enhance nitrogen removal efficiency. The literature on BNR microbial communities and experimental datasets is not unified across various repositories, while a uniform resource for the collection, annotation, and structuring of these BNR datasets is still unavailable. Herein, we present the Biological Nitrogen Removal Database (BNRdb), an integrated resource containing various manually curated BNR-related data. At present, BNRdb contains 23308 microbial strains, 46 gene families, 24 enzymes, 18 reactions, 301 BNR treatment datasets, 860 BNR-associated next-generation sequencing datasets, and 6 common BNR bioreactor systems. BNRdb provides a user-friendly interface enabling interactive data browsing. To our knowledge, BNRdb is the first BNR data resource that systematically integrates BNR data from archaeal, bacterial, and fungal communities. We believe that BNRdb will contribute to a better understanding of BNR process and nitrogen bioremediation research.

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“…The diagrams of S-, N-, and C-cycle are originated from the study of Wu and Yin. 7 The figures of phylogenic trees, PCoA, and data-driven modeling analysis on functional expression are based on the study of Cheng et al 31 Environmental Science: Water Research & Technology Perspective operational taxonomic unit levels. 154 The genomics-enabled data-driven modeling approach was rigorously cross-validated using three validation strategies.…”

Section: Genomics-enabled Data-driven Modelingmentioning

confidence: 99%