title: Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities.
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.
authors.affiliation: Center for Environmental Sensing and Modelling, Singapore-MIT Alliance for Research and Technology Centre Singapore, Singapore.
authors.forename: BoonFei
authors.initials: B
authors.lastname: Tan
authors.affiliation: Department of Civil and Environmental Engineering, National University of Singapore Singapore, Singapore.
authors.forename: Charmaine
authors.initials: C
authors.lastname: Ng
authors.affiliation: Center 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.
authors.forename: Jean Pierre
authors.initials: JP
authors.lastname: Nshimyimana
authors.affiliation: Center 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.
authors.forename: Lay Leng
authors.initials: LL
authors.lastname: Loh
authors.affiliation: Department of Civil and Environmental Engineering, National University of Singapore Singapore, Singapore.
authors.forename: Karina Y-H
authors.initials: KY
authors.lastname: Gin
authors.affiliation: Center 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.
authors.forename: Janelle R
authors.initials: JR
authors.lastname: Thompson
keywords: antibiotic resistance; biodegradation; fecal indicator; harmful algal bloom; next-generation sequencing; sewage; water quality