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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Tan, BoonFei, Ng, Charmaine, Nshimyimana, Jean Pierre, Loh, Lay Leng, Gin, Karina Y.-H., Thompson, Janelle R.
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2015
Subjects:
Online Access:https://hdl.handle.net/10356/80959
http://hdl.handle.net/10220/39025
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-80959
record_format dspace
spelling sg-ntu-dr.10356-809592022-02-16T16:31:01Z Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities Tan, BoonFei Ng, Charmaine Nshimyimana, Jean Pierre Loh, Lay Leng Gin, Karina Y.-H. Thompson, Janelle R. School of Civil and Environmental Engineering Singapore Centre for Environmental Life Sciences Engineering Next-generationsequencing Waterquality Fecalindicator Antibioticresistance Harmfulalgalbloom Biodegradation Sewage 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. NRF (Natl Research Foundation, S’pore) Published version 2015-12-10T04:35:48Z 2019-12-06T14:18:19Z 2015-12-10T04:35:48Z 2019-12-06T14:18:19Z 2015 Journal Article Tan, B., Ng, C., Nshimyimana, J. P., Loh, L. L., Gin, K. Y. -H., & Thompson, J. R. (2015). Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities. Frontiers in Microbiology, 6, 1027-. 1664-302X https://hdl.handle.net/10356/80959 http://hdl.handle.net/10220/39025 10.3389/fmicb.2015.01027 26441948 en Frontiers in Microbiology © 2015 Tan, Ng, Nshimyimana, Loh, Gin and Thompson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. 20 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Next-generationsequencing
Waterquality
Fecalindicator
Antibioticresistance
Harmfulalgalbloom
Biodegradation
Sewage
spellingShingle Next-generationsequencing
Waterquality
Fecalindicator
Antibioticresistance
Harmfulalgalbloom
Biodegradation
Sewage
Tan, BoonFei
Ng, Charmaine
Nshimyimana, Jean Pierre
Loh, Lay Leng
Gin, Karina Y.-H.
Thompson, Janelle R.
Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities
description 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.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Tan, BoonFei
Ng, Charmaine
Nshimyimana, Jean Pierre
Loh, Lay Leng
Gin, Karina Y.-H.
Thompson, Janelle R.
format Article
author Tan, BoonFei
Ng, Charmaine
Nshimyimana, Jean Pierre
Loh, Lay Leng
Gin, Karina Y.-H.
Thompson, Janelle R.
author_sort Tan, BoonFei
title Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities
title_short Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities
title_full Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities
title_fullStr Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities
title_full_unstemmed Next-generation sequencing (NGS) for assessment of microbial water quality : current progress, challenges, and future opportunities
title_sort next-generation sequencing (ngs) for assessment of microbial water quality : current progress, challenges, and future opportunities
publishDate 2015
url https://hdl.handle.net/10356/80959
http://hdl.handle.net/10220/39025
_version_ 1725985769491791872