4.7 Article

Chlorination effects on DNA based characterization of water microbiomes and implications for the interpretation of data from disinfected systems

Journal

JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 276, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2020.111319

Keywords

Chlorination; Microbial water quality; Faecal indicator bacteria; 16S rRNA amplicon sequencing

Funding

  1. Engineering and Physical Sciences Research Council [EPSRC] [EP/P028527/1]
  2. UK's Economic and Social Research Council [ES/S008179/1]
  3. EPSRC [EP/P028527/1] Funding Source: UKRI

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Quantitative PCR (qPCR) and next generation sequencing (NGS) are nucleic acid based microbiology techniques that provide new insights into drinking water quality, but considerable uncertainty remains around their correct interpretation. We noticed the presence of bacterial DNA from various putative pathogens, including from faecal indicator bacteria (FIB), in disinfected water, when culturable FIB were absent. To understand these observations better we studied the effect of chlorination on conventional and DNA based microbial water quality assessments. Surface water chlorination reduced plate counts for various FIB by up to >6 log units, intact cell counts by flow cytometry by 3.3 log units, and 16S rRNA gene copies by qPCR by 1.5 and 1.6 log units for total bacteria and total coliforms, respectively. Nanopore sequencing of 16S rRNA amplicons with the portable MinION device revealed the DNA from several families containing putative pathogens appeared to be more resistant than that of other bacteria to degradation by chlorine disinfection. For instance, 16S rRNA genes assigned to the Enterobacteriaceae family, members of which are mostly the target of coliform tests, increased in relative abundance from 0.001 +/- 0.0002% to 0.0036 +/- 0.003% after chlorine treatment. Hence, metagenomic drinking water data needs to be interpreted with caution. Plate counts and flow cytometry in combination with DNA based analysis provide more robust insight than NGS or qPCR alone.

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