Evidence map›Paper›PMID 38423320›Full record

ArticleThe Science of the total environment2024

Impact of harmful algal bloom severity on bacterial communities in a full-scale biological filtration system for drinking water treatment.

Youchul Jeon, Lei Li, Mudit Bhatia, Hodon Ryu, Jorge W Santo Domingo, Jess Brown, Jake Goetz, Youngwoo Seo

Open access · hybridAbstract read
In one paragraph

Article in The Science of the total environment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
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

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Toxins · 2026
    Article
  2. Article
  3. Review
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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

8 authors at 2 institutions in 1 country.

Youchul JeonDepartment of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3006 Nitschke Hall, Toledo, OH 43606, United States of America.
Lei LiDepartment of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3006 Nitschke Hall, Toledo, OH 43606, United States of America.
Mudit BhatiaDepartment of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3006 Nitschke Hall, Toledo, OH 43606, United States of America.
Hodon RyuWater Infrastructure Division, Center for Environmental Solutions and Emergency Response, U.S. Environmental Protection Agency, Cincinnati, OH 45268, United States of America.
Jorge W Santo DomingoWater Infrastructure Division, Center for Environmental Solutions and Emergency Response, U.S. Environmental Protection Agency, Cincinnati, OH 45268, United States of America.
Jess BrownCarollo Engineers' Research and Development Practice, Costa Mesa, CA 92626, United States of America.
Jake GoetzCity of Toledo Colins Park Water Treatment, Toledo, OH 43605, United States of America.
Youngwoo SeoDepartment of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3006 Nitschke Hall, Toledo, OH 43606, United States of America; Department of Chemical and Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall, Toledo, OH 43606, United States of America. Electronic address: Youngwoo.Seo@utoledo.edu.
University of Toledo · USEnvironmental Protection Agency · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

The occurrence of harmful algal blooms (HABs) in freshwater environments has been expanded worldwide with growing frequency and severity. HABs can pose a threat to public water supplies, raising concerns about safety of treated water. Many studies have provided valuable information about the impacts of HABs and management strategies on the early-stage treatment processes (e.g., pre-oxidation and coagulation/flocculation) in conventional drinking water treatment plants (DWTPs). However, the potential effect of HAB-impacted water in the granular media filtration has not been well studied. Biologically-active filters (BAFs), which are used in drinking water treatment and rely largely on bacterial community interactions, have not been examined during HABs in full-scale DWTPs. In this study, we assessed the bacterial community structure of BAFs, functional profiles, assembly processes, and bio-interactions in the community during both severe and mild HABs. Our findings indicate that bacterial diversity in BAFs significantly decreases during severe HABs due to the predominance of bloom-associated bacteria (e.g., Spingopyxis, Porphyrobacter, and Sphingomonas). The excitation-emission matrix combined with parallel factor analysis (EEM-PARAFAC) confirmed that filter influent affected by the severe HAB contained a higher portion of protein-like substances than filter influent samples during a mild bloom. In addition, BAF community functions showed increases in metabolisms associated with intracellular algal organic matter (AOM), such as lipids and amino acids, during severe HABs. Further ecological process and network analyses revealed that severe HAB, accompanied by the abundance of bloom-associated taxa and increased nutrient availability, led to not only strong stochastic processes in the assembly process, but also a bacterial community with lower complexity in BAFs. Overall, this study provides deeper insights into BAF bacterial community structure, function, and assembly in response to HABs.

Indexed as

Drinking WaterFiltrationHarmful Algal BloomWater PurificationBacteriaMicrobiotaWater MicrobiologyDrinking WaterBacterial community structureBiologically-active filtersDrinking water treatment processHarmful algal bloomNetwork analysis

Identifiers

PMID38423320
PMCPMC11333992
OpenAlexW4392195574

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.