Evidence map›Paper›PMID 19908076›Full record

ArticleJournal of industrial microbiology & biotechnology2010

Variations of bacterial 16S rDNA phylotypes prior to and after chlorination for drinking water production from two surface water treatment plants.

Jean-Baptiste Poitelon, Michel Joyeux, Bénédicte Welté, Jean-Pierre Duguet, Eric Prestel, Michael S DuBow

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Article in Journal of industrial microbiology & biotechnology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jean-Baptiste PoitelonEAU DE PARIS, Paris, France.
Michel Joyeux
Bénédicte Welté
Jean-Pierre Duguet
Eric Prestel
Michael S DuBow

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We examined the variations of bacterial populations in treated drinking water prior to and after the final chlorine disinfection step at two different surface water treatment plants. For this purpose, the bacterial communities present in treated water were sampled after granular activated carbon (GAC) filtration and chlorine disinfection from two drinking water treatment plants supplying the city of Paris (France). Samples were analyzed after genomic DNA extraction, polymerase chain reaction (PCR) amplification, cloning, and sequencing of a number of 16S ribosomal RNA (rRNA) genes. The 16S rDNA sequences were clustered into operational taxonomic units (OTUs) and the OTU abundance patterns were obtained for each sample. The observed differences suggest that the chlorine disinfection step markedly affects the bacterial community structure and composition present in GAC water. Members of the Alphaproteobacteria and Betaproteobacteria were found to be predominant in the GAC water samples after phylogenetic analyses of the OTUs. Following the chlorine disinfection step, numerous changes were observed, including decreased representation of Proteobacteria phylotypes. Our results indicate that the use of molecular methods to investigate changes in the abundance of certain bacterial groups following chlorine-based disinfection will aid in further understanding the bacterial ecology of drinking water treatment plants (DWTPs), particularly the disinfection step, as it constitutes the final barrier before drinking water distribution to the consumer's tap.

Indexed as

Water MicrobiologyWater PurificationWater SupplyBacteriaBiodiversityCharcoalChloridesChlorineDisinfectionDNA, BacterialDNA, RibosomalEcosystemFerric CompoundsFiltrationFresh WaterParisCharcoalChloridesChlorineDNA, BacterialDNA, Ribosomalferric chlorideFerric CompoundsRNA, Ribosomal, 16S

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.