Literature DB >> 34347524

Direct Evidence for Deterministic Assembly of Bacterial Communities in Full-Scale Municipal Wastewater Treatment Facilities.

Taegyu Kim1, Sebastian Behrens1,2, Timothy M LaPara1,2.   

Abstract

In this study, we investigated whether bacterial community composition in full-scale wastewater treatment bioreactors can be better explained by niche- or neutral-based theory (deterministic or stochastic) and whether bioreactor design (continuous flow versus fill and draw) affected community assembly. Four wastewater treatment facilities (one with quadruplicated continuous-flow bioreactors, two with one continuous-flow bioreactor each, and one with triplicate fill-and-draw bioreactors) were investigated. Bioreactor community composition was characterized by sequencing of PCR-amplified 16S rRNA gene fragments. Replicate bioreactors at the same wastewater treatment facility had largely reproducible (i.e., deterministic) bacterial community composition, although bacterial community composition in continuous-flow bioreactors was significantly more reproducible (P < 0.001) than in fill-and-draw bioreactors (Bray-Curtis dissimilarity, μ = 0.48 ± 0.06 versus 0.58 ± 0.08). Next, we compared our results to previously used indirect methods for distinguishing between deterministic and stochastic community assembly mechanisms. Synchronicity was observed in the bacterial community composition among bioreactors within the same metropolitan region, consistent with deterministic community assembly. Similarly, a null model-based analysis also indicated that all wastewater bioreactor communities were controlled by deterministic factors and that continuous-flow bioreactors were significantly more deterministic (P < 0.001) than fill-and-draw bioreactors (nearest-taxon index, μ = 3.8 ± 0.6 versus 2.7 ± 0.8). Our results indicate that bacterial community composition in wastewater treatment bioreactors is better explained by deterministic community assembly theory; simultaneously, our results validate previously used but indirect methods to quantify whether microbial communities were assembled via deterministic or stochastic mechanisms. IMPORTANCE Understanding the mechanisms of bacterial community assembly is one of the grand challenges of microbial ecology. In environmental systems, this challenge is exacerbated because replicate experiments are typically impossible; that is, microbial ecologists cannot fabricate multiple field-scale experiments of identical, natural ecosystems. Our results directly demonstrate that deterministic mechanisms are more prominent than stochastic mechanisms in the assembly of wastewater treatment bioreactor communities. Our results also suggest that wastewater treatment bioreactor design is pertinent, such that the imposition of feast-famine conditions (i.e., fill-and-draw bioreactors) nudge bacterial community assembly more toward stochastic mechanisms than the imposition of stringent nutrient limitation (i.e., continuous-flow bioreactors). Our research also validates the previously used indirect methods (synchronous community dynamics and an application of a null model) for characterizing the relative importance of deterministic versus stochastic mechanisms of community assembly.

Entities:  

Keywords:  deterministic community assembly; microbiome; municipal wastewater treatment; nearest-taxon index (NTI); synchrony

Mesh:

Substances:

Year:  2021        PMID: 34347524      PMCID: PMC8478442          DOI: 10.1128/AEM.01086-21

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  38 in total

1.  Stochastic and deterministic assembly processes in subsurface microbial communities.

Authors:  James C Stegen; Xueju Lin; Allan E Konopka; James K Fredrickson
Journal:  ISME J       Date:  2012-03-29       Impact factor: 10.302

2.  Synchrony in aquatic microbial community dynamics.

Authors:  Angela D Kent; Anthony C Yannarell; James A Rusak; Eric W Triplett; Katherine D McMahon
Journal:  ISME J       Date:  2007-05       Impact factor: 10.302

3.  Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

Authors:  Qiong Wang; George M Garrity; James M Tiedje; James R Cole
Journal:  Appl Environ Microbiol       Date:  2007-06-22       Impact factor: 4.792

4.  Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

Authors:  James J Kozich; Sarah L Westcott; Nielson T Baxter; Sarah K Highlander; Patrick D Schloss
Journal:  Appl Environ Microbiol       Date:  2013-06-21       Impact factor: 4.792

5.  Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests.

Authors:  Steven W Kembel
Journal:  Ecol Lett       Date:  2009-09       Impact factor: 9.492

6.  Nonrandom assembly of bacterial populations in activated sludge flocs.

Authors:  Joaquín M Ayarza; Leandro D Guerrero; Leonardo Erijman
Journal:  Microb Ecol       Date:  2009-09-16       Impact factor: 4.552

7.  Regional synchrony in full-scale activated sludge bioreactors due to deterministic microbial community assembly.

Authors:  James S Griffin; George F Wells
Journal:  ISME J       Date:  2016-12-20       Impact factor: 10.302

8.  Bacterial assembly and temporal dynamics in activated sludge of a full-scale municipal wastewater treatment plant.

Authors:  Feng Ju; Tong Zhang
Journal:  ISME J       Date:  2014-09-02       Impact factor: 10.302

9.  OptiClust, an Improved Method for Assigning Amplicon-Based Sequence Data to Operational Taxonomic Units.

Authors:  Sarah L Westcott; Patrick D Schloss
Journal:  mSphere       Date:  2017-03-08       Impact factor: 4.389

10.  Bacterial community assembly in activated sludge: mapping beta diversity across environmental variables.

Authors:  Siavash Isazadeh; Shameem Jauffur; Dominic Frigon
Journal:  Microbiologyopen       Date:  2016-10-19       Impact factor: 3.139

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  1 in total

1.  Microbial Community Composition in Municipal Wastewater Treatment Bioreactors Follows a Distance Decay Pattern Primarily Controlled by Environmental Heterogeneity.

Authors:  Taegyu Kim; Sebastian Behrens; Timothy M LaPara
Journal:  mSphere       Date:  2021-10-20       Impact factor: 4.389

  1 in total

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