Microbiome of drinking water: A full-scale spatio-temporal study to monitor water quality in the Paris distribution system

Water Res. 2019 Feb 1:149:375-385. doi: 10.1016/j.watres.2018.11.013. Epub 2018 Nov 12.

Abstract

The microbiological water quality of drinking water distribution system (DWDS) is of primary importance for human health. High-throughput sequencing has gained more and more attention in the last decade to describe this microbial diversity in water networks. However, there are few studies describing this approach on large drinking water distribution systems and for extended periods of time. To fill this gap and observe the potential subtle variation in microbiota of a water network through time and space, we aimed to apply high-throughput sequencing of the 16S rRNA gene approach to characterize bacterial communities of the Paris' DWDS over a one-year period. In this study, the Paris network, composed of four different DWDSs, was sampled at 31 sites, each month for one year. The sampling campaign was one of the largest described so far (n = 368) and the importance of key spatio-temporal and physico-chemical parameters was investigated. Overall, 1321 taxa were identified within the Paris network, although only fifteen of them were found in high relative abundance (>1%) in all samples. Two genera, Phreatobacter and Hyphomicrobium were dominant. The whole bacterial diversity was not significantly affected between the four DWDSs (spatial parameter) and by physico-chemical parameters. However, the bacterial diversity was slightly modified over the one-year period (temporal parameter) as we were able to observe DWDS microbiome perturbations, presumably linked to a preceding flood event. Comparison of high-throughput sequencing of the 16S rRNA gene amplicons vs. cultivation-based techniques showed that only 1.8% of bacterial diversity was recovered through cultivation. High throughput sequencing has made it possible to monitor DWDS more accurately than conventional methods by describing the whole diversity and detecting slight fluctuations in bacterial communities. This method would be further used to supervise drinking water networks, to follow any perturbations due to internals events (such as treatments) or external events (such as flooding).

Keywords: 16S; Bacteria; Drinking water; Ecology; Microbiome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Drinking Water*
  • Microbiota*
  • Paris
  • RNA, Ribosomal, 16S
  • Water Quality

Substances

  • Drinking Water
  • RNA, Ribosomal, 16S