Evidence map›Paper›PMID 26441948›Full record

ReviewFrontiers in microbiology2015

Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities.

BoonFei Tan, Charmaine Ng, Jean Pierre Nshimyimana, Lay Leng Loh, Karina Y-H Gin, Janelle R Thompson

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 1 pooled it
20.5field-weighted citation impact, top 1% 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

81 citing papers in PubMed, 1 synthesis or guideline pooled it, 289 citations in OpenAlex.

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  14. Application of next-generation sequencing for detectingFrontiers in veterinary science · 2025
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21 more citing papers are in PubMed but not listed here.

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

6 authors at 3 institutions in 2 countries.

BoonFei TanCenter for Environmental Sensing and Modelling, Singapore-MIT Alliance for Research and Technology Centre Singapore, Singapore.
Charmaine NgDepartment of Civil and Environmental Engineering, National University of Singapore Singapore, Singapore.
Jean Pierre NshimyimanaCenter for Environmental Sensing and Modelling, Singapore-MIT Alliance for Research and Technology Centre Singapore, Singapore ; Singapore Centre on Environmental Life Sciences Engineering, Nanyang Technological University Singapore, Singapore ; School of Civil and Environmental Engineering, Nanyang Technological University Singapore, Singapore.
Lay Leng LohCenter for Environmental Sensing and Modelling, Singapore-MIT Alliance for Research and Technology Centre Singapore, Singapore ; Department of Civil and Environmental Engineering, National University of Singapore Singapore, Singapore.
Karina Y-H GinDepartment of Civil and Environmental Engineering, National University of Singapore Singapore, Singapore.
Janelle R ThompsonCenter for Environmental Sensing and Modelling, Singapore-MIT Alliance for Research and Technology Centre Singapore, Singapore ; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge MA, USA.
National University of Singapore · SGSingapore-MIT Alliance for Research and Technology · SGNanyang Technological University · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water quality is an emergent property of a complex system comprised of interacting microbial populations and introduced microbial and chemical contaminants. Studies leveraging next-generation sequencing (NGS) technologies are providing new insights into the ecology of microbially mediated processes that influence fresh water quality such as algal blooms, contaminant biodegradation, and pathogen dissemination. In addition, sequencing methods targeting small subunit (SSU) rRNA hypervariable regions have allowed identification of signature microbial species that serve as bioindicators for sewage contamination in these environments. Beyond amplicon sequencing, metagenomic and metatranscriptomic analyses of microbial communities in fresh water environments reveal the genetic capabilities and interplay of waterborne microorganisms, shedding light on the mechanisms for production and biodegradation of toxins and other contaminants. This review discusses the challenges and benefits of applying NGS-based methods to water quality research and assessment. We will consider the suitability and biases inherent in the application of NGS as a screening tool for assessment of biological risks and discuss the potential and limitations for direct quantitative interpretation of NGS data. Secondly, we will examine case studies from recent literature where NGS based methods have been applied to topics in water quality assessment, including development of bioindicators for sewage pollution and microbial source tracking, characterizing the distribution of toxin and antibiotic resistance genes in water samples, and investigating mechanisms of biodegradation of harmful pollutants that threaten water quality. Finally, we provide a short review of emerging NGS platforms and their potential applications to the next generation of water quality assessment tools.

Indexed as

antibiotic resistancebiodegradationfecal indicatorharmful algal bloomnext-generation sequencingsewagewater quality

Identifiers

PMID26441948
PMCPMC4585245
OpenAlexW1951683428

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.