Evidence map›Paper›PMID 39039555›Full record

ArticleMicrobiome2024

Distributions, interactions, and dynamics of prokaryotes and phages in a hybrid biological wastewater treatment system.

Dou Wang, Lei Liu, Xiaoqing Xu, Chunxiao Wang, Yulin Wang, Yu Deng, Tong Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microbiome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Dou WangEnvironmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China.
Lei LiuEnvironmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China.
Xiaoqing XuEnvironmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China.
Chunxiao WangEnvironmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China.
Yulin WangEnvironmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China.
Yu DengEnvironmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China.
Tong ZhangEnvironmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China. zhangt@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding the interactions and dynamics of microbiotas within biological wastewater treatment systems is essential for ensuring their stability and long-term sustainability. In this study, we developed a systematic framework employing multi-omics and Hi-C sequencing to extensively investigate prokaryotic and phage communities within a hybrid biofilm and activated sludge system.

resultsWe uncovered distinct distribution patterns, metabolic capabilities, and activities of functional prokaryotes through the analysis of 454 reconstructed prokaryotic genomes. Additionally, we reconstructed a phage catalog comprising 18,645 viral operational taxonomic units (vOTUs) with high length and contiguity using hybrid assembly, and a distinct distribution of phages was depicted between activated sludge (AS) and biofilm. Importantly, 1340 host-phage pairs were established using Hi-C and conventional in silico methods, unveiling the host-determined phage prevalence. The majority of predicted hosts were found to be involved in various crucial metabolic processes, highlighting the potential vital roles of phages in influencing substance metabolism within this system. Moreover, auxiliary metabolic genes (AMGs) related to various categories (e.g., carbohydrate degradation, sulfur metabolism, transporter) were predicted. Subsequent activity analysis emphasized their potential ability to mediate host metabolism during infection. We also profiled the temporal dynamics of phages and their associated hosts using 13-month time-series metagenomic data, further demonstrating their tight interactions. Notably, we observed lineage-specific infection patterns, such as potentially host abundance- or phage/host ratio-driven phage population changes.

conclusionsThe insights gained from this research contribute to the growing body of knowledge surrounding interactions and dynamics of host-phage and pave the way for further exploration and potential applications in the field of microbial ecology. Video Abstract.

Indexed as

BacteriaBacteriophagesSewageWastewaterBiofilmsMetagenomicsMicrobiotaWater PurificationSewageWastewaterHi-C sequencingHost-phage interactionsHybrid systemMulti-omicsPhageProkaryote

Identifiers

PMID39039555
PMCPMC11265110

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.