Bacterial community change through drinking water treatment processes

Liao, Xiaobin; Chen, C.; Wang, Z.; Chang, Chih‐Hsiang; Zhang, X.; Xie, Shuguang

doi:10.1007/s13762-014-0540-0

Cited by 21 publications

(11 citation statements)

References 28 publications

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“…Core taxa within the DWTPs comprised primarily of Actinobacteria ( Sporichthyaceae ) , Acidobacteria ( Halophagaceae ), Alphaproteobacteria, Gammaproteobacteria and Betaproteobacteriales ( Rhizobiales, Phreatobacter ). These groups have previously found to be ubiquitous in DWTPs (Pinto et al ., 2012; Lautenschlager et al ., 2013; Zeng et al ., 2013; Liao et al ., 2015a). In this study, these taxa were observed to be dominant in the source waters and showed continued dominance throughout DWTP samples.…”

Section: Discussionmentioning

confidence: 99%

Reproducible microbial community dynamics of two drinking water systems treating similar source waters

Potgieter

Pinto²,

Havenga

et al. 2019

Preprint

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26In addition to containing higher concentrations of organics and bacterial cells, 27 surface waters are often more vulnerable to pollution and microbial contamination 28 with intensive industrial and agricultural activities frequently occurring in areas 29 surrounding the water source. Therefore, surface waters typically require additional 30 treatment, where the choice of treatment strategy is critical for water quality. Using 31 16S rRNA gene profiling, this study provides a unique opportunity to simultaneously 32 investigate and compare two drinking water treatment plants and their 33 corresponding distribution systems. The two treatment plants treat similar surface 34 waters, from the same river system, with the same sequential treatment strategies. 35 Here, the impact of treatment and distribution on the microbial community within and 36 between each system was compared over an eight-month sampling campaign. 37 Overall, reproducible spatial and temporal dynamics within both DWTPs and their 38 corresponding DWDSs were observed. Although source waters showed some 39 dissimilarity in microbial community structure and composition, pre-disinfection 40 treatments (i.e. coagulation, flocculation, sedimentation and filtration) resulted in 41 highly similar microbial communities between the filter effluent samples. This 42 indicated that the same treatments resulted in the development of similar microbial 43 communities. Conversely, post-disinfection (i.e. chlorination and chloramination) 44 resulted in increased dissimilarity between disinfected samples from the two 45 systems, showing alternative responses of the microbial community to disinfection. 46 Lastly, it was observed that within the distribution system the same dominant taxa 47 were selected where samples increased in similarity with increased residence time. 48 Although, differences were found between the two systems, overall treatment and 49 distribution had a similar impact on the microbial community in each system. This 50 study therefore provides valuable information on the impact of treatment and 51 distribution on the drinking water microbiome. 52 53 Keywords: drinking water treatment; drinking water distribution; disinfection; 54 microbial community dynamics; Illumina MiSeq. 55 56 Highlights 57  Source waters show some dissimilarity in microbial community. 58  Treatment processes increases similarity and selects for the same dominant 59 taxa. 60  Differential response to chlorination causing increased dissimilarity and 61 variation. 62  Stabilisation of DWDS microbial community through selection of same 63 dominant taxa. 64  Microbial community dynamics are reproducible between the two systems. 65 66 Abbreviations 67 DWDS, drinking water distribution system; DWTP, drinking water treatment plant; 68 DADA2, Divisive Amplicon Denoising Algorithm; ASV, amplicon sequence variant; 69 AMOVA, analysis of molecular variance; MRA, mean relative abundance; PCoA, 70 Principal coordinate analysis; ANOVA, One-way analysis of varianc...

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Section: Discussionmentioning

confidence: 99%

Reproducible microbial community dynamics of two drinking water systems treating similar source waters

Potgieter

Pinto²,

Havenga

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…In the past few decades, volatile organic compounds, heavy metal and pathogen contaminations in household pipes were routinely evaluated [ 3 ]. Compared with the numerous reports on bacterial cell concentration and community from drinking water reservoirs [ 4 , 5 ], drinking water treatment processes [ 6 ], and transportation system [ 7 ], the characteristics of water bacterial composition associated with building indoor pipelines remains poorly understood. Recent publications have suggested that drinking water pipeline materials, including metal pipes and polymer pipes [ 8 , 9 ], household stagnation [ 10 ] and temperature [ 3 ] may increase the bacterial regrowth associated with indoor water pipes [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Indoor Heating Drives Water Bacterial Growth and Community Metabolic Profile Changes in Building Tap Pipes during the Winter Season

Zhang

Chen

Shang

et al. 2015

IJERPH

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The growth of the bacterial community harbored in indoor drinking water taps is regulated by external environmental factors, such as indoor temperature. However, the effect of indoor heating on bacterial regrowth associated with indoor drinking water taps is poorly understood. In the present work, flow cytometry and community-level sole-carbon-source utilization techniques were combined to explore the effects of indoor heating on water bacterial cell concentrations and community carbon metabolic profiles in building tap pipes during the winter season. The results showed that the temperature of water stagnated overnight (“before”) in the indoor water pipes was 15–17 °C, and the water temperature decreased to 4–6 °C after flushing for 10 min (“flushed”). The highest bacterial cell number was observed in water stagnated overnight, and was 5–11 times higher than that of flushed water. Meanwhile, a significantly higher bacterial community metabolic activity (AWCD590nm) was also found in overnight stagnation water samples. The significant “flushed” and “taps” values indicated that the AWCD590nm, and bacterial cell number varied among the taps within the flushed group (p < 0.01). Heatmap fingerprints and principle component analyses (PCA) revealed a significant discrimination bacterial community functional metabolic profiles in the water stagnated overnight and flushed water. Serine, threonine, glucose-phosphate, ketobutyric acid, phenylethylamine, glycerol, putrescine were significantly used by “before” water samples. The results suggested that water stagnated at higher temperature should be treated before drinking because of bacterial regrowth. The data from this work provides useful information on reasonable utilization of drinking water after stagnation in indoor pipes during indoor heating periods.

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“…Recent work has investigated the bacteria that could reduce some organic matters, and also examined the change in microbial community due to the change in drinking water processes ( Chung et al, 2008 ; Liao et al, 2012 , 2013 , 2014 , 2015b ; Wang et al, 2015 ). However, there is no information on the microbial communities in BAC filters that exposed to phenol, which could contribute to isolating the main indigenous bacteria that has excellent phenol-degrading ability in drinking water biofilters.…”

Section: Discussionmentioning

confidence: 99%

Community Analysis and Recovery of Phenol-degrading Bacteria from Drinking Water Biofilters

Zhang

et al. 2016

Front. Microbiol.

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Phenol is a ubiquitous organic contaminant in drinking water. Biodegradation plays an important role in the elimination of phenol pollution in the environment, but the information about phenol removal by drinking water biofilters is still lacking. Herein, we study an acclimated bacterial community that can degrade over 80% of 300 mg/L phenol within 3 days. PCR detection of genotypes involved in bacterial phenol degradation revealed that the degradation pathways contained the initial oxidative attack by phenol hydroxylase, and subsequent ring fission by catechol 1,2-dioxygenase. Based on the PCR denatured gradient gel electrophoresis (PCR-DGGE) profiles of bacteria from biological activated carbon (BAC), the predominant bacteria in drinking water biofilters including Delftia sp., Achromobacter sp., and Agrobacterium sp., which together comprised up to 50% of the total microorganisms. In addition, a shift in bacterial community structure was observed during phenol biodegradation. Furthermore, the most effective phenol-degrading strain DW-1 that correspond to the main band in denaturing gradient gel electrophoresis (DGGE) profile was isolated and identified as Acinetobacter sp., according to phylogenetic analyses of the 16S ribosomal ribonucleic acid (rRNA) gene sequences. The strain DW-1 also produced the most important enzyme, phenol hydroxylase, and it also exhibited a good ability to degrade phenol when immobilized on granular active carbon (GAC). This study indicates that the enrichment culture has great potential application for treatment of phenolpolluted drinking water sources, and the indigenous phenol-degrading microorganism could recover from drinking water biofilters as an efficient resource for phenol removal. Therefore, the aim of this study is to draw attention to recover native phenol-degrading bacteria from drinking water biofilters, and use these native microorganisms as phenolic water remediation in drinking water sources.

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Bacterial community change through drinking water treatment processes

Cited by 21 publications

References 28 publications

Reproducible microbial community dynamics of two drinking water systems treating similar source waters

Reproducible microbial community dynamics of two drinking water systems treating similar source waters

Indoor Heating Drives Water Bacterial Growth and Community Metabolic Profile Changes in Building Tap Pipes during the Winter Season

Community Analysis and Recovery of Phenol-degrading Bacteria from Drinking Water Biofilters

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