Emerging investigators series: Microbial communities in full-scale drinking water distribution systems – A meta-analysis

Bautista-de los Santos, Q. M., Schroeder, J., Sevillano-Rivera, M. C., Sungthong, R. , Ijaz, U. Z. , Sloan, W. T. and Pinto, A. J. (2016) Emerging investigators series: Microbial communities in full-scale drinking water distribution systems – A meta-analysis. Environmental Science: Water Research and Technology, 2(4), pp. 631-644. (doi:10.1039/C6EW00030D)

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Abstract

In this study, we co-analyze all available 16S rRNA gene sequencing studies from bulk drinking water samples in full-scale drinking water distribution systems. Consistent with expectations, we find that Proteobacteria, particularly Alpha- and Betaproteobacteria, dominate drinking water bacterial communities irrespective of origin of study and presence/absence of or disinfectant residual type. We find that microbial communities in disinfectant residual free systems are more diverse than those that maintain a disinfectant residual. Further, we also find positive associations between mean relative abundance and occurrence of bacteria within a disinfectant category group. The relative abundance and occurrence of key bacterial genera (e.g. Legionella, Mycobacterium, Pseudomonas) is influenced by the presence/absence of a disinfectant residual and the type of disinfectant residual used. Similarly, we find widespread distribution of bacterial genera that are of interest from both an ecological and process perspectives (e.g. nitrification, predation). By estimating the contribution of potential contaminating genera to published drinking water datasets, we recommend routine sequencing of negative controls be included in drinking water studies. Finally, we test the utility of predicting metabolic potential of drinking water communities using 16S rRNA gene data and recommend against this practice. Though data heterogeneity across available datasets is a major confounding factor in our meta-analysis, we recommend that efforts to standardize sample processing protocols to address it may not optimal for the drinking water microbial ecology field at this juncture. Rather, we recommend standardizing data and meta-data reporting, starting with making all sequencing data publicly available, and sample sharing as means of supporting future efforts for comparative analyses across drinking water systems/studies.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Pinto, Dr Ameet and Sungthong, Dr Rungroch and Schroeder, Dr Joanna and Sloan, Professor William and Ijaz, Dr Umer Zeeshan
Authors: Bautista-de los Santos, Q. M., Schroeder, J., Sevillano-Rivera, M. C., Sungthong, R., Ijaz, U. Z., Sloan, W. T., and Pinto, A. J.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
Journal Name:Environmental Science: Water Research and Technology
Publisher:Royal Society of Chemistry
ISSN:2053-1400
Published Online:30 March 2016
Copyright Holders:Copyright © 2016 The Royal Society of Chemistry
First Published:First published in Environmental Science: Water Research and Technology 2(4): 631-644
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
621651Developing an Event Prediction and Correction Framework for Microbial Management in Drinking Water Systems.Ameet PintoEngineering & Physical Sciences Research Council (EPSRC)EP/K035886/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR
665801Healthy drinking waterAmeet PintoEngineering & Physical Sciences Research Council (EPSRC)EP/M016811/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR
652771Understanding microbial community through in situ environmental 'omic data synthesisUmer IjazNatural Environment Research Council (NERC)NE/L011956/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR