Literature DB >> 33401450

Can Cyanobacterial Diversity in the Source Predict the Diversity in Sludge and the Risk of Toxin Release in a Drinking Water Treatment Plant?

Farhad Jalili1, Hana Trigui1, Juan Francisco Guerra Maldonado1, Sarah Dorner1, Arash Zamyadi2, B Jesse Shapiro3,4,5, Yves Terrat3, Nathalie Fortin6, Sébastien Sauvé7, Michèle Prévost1.   

Abstract

Conventional processes (coagulation, flocculation, sedimentation, and filtration) are widely used in drinking water treatment plants and are considered a good treatment strategy to eliminate cyanobacterial cells and cell-bound cyanotoxins. The diversity of cyanobacteria was investigated using taxonomic cell counts and shotgun metagenomics over two seasons in a drinking water treatment plant before, during, and after the bloom. Changes in the community structure over time at the phylum, genus, and species levels were monitored in samples retrieved from raw water (RW), sludge in the holding tank (ST), and sludge supernatant (SST). Aphanothece clathrata brevis, Microcystis aeruginosa, Dolichospermum spiroides , and Chroococcus minimus were predominant species detected in RW by taxonomic cell counts. Shotgun metagenomics revealed that Proteobacteria was the predominant phylum in RW before and after the cyanobacterial bloom. Taxonomic cell counts and shotgun metagenomic showed that the Dolichospermum bloom occurred inside the plant. Cyanobacteria and Bacteroidetes were the major bacterial phyla during the bloom. Shotgun metagenomics also showed that Synechococcus, Microcystis , and Dolichospermum were the predominant detected cyanobacterial genera in the samples. Conventional treatment removed more than 92% of cyanobacterial cells but led to cell accumulation in the sludge up to 31 times more than in the RW influx. Coagulation/sedimentation selectively removed more than 96% of Microcystis and Dolichospermum. Cyanobacterial community in the sludge varied from raw water to sludge during sludge storage (1-13 days). This variation was due to the selective removal of coagulation/sedimentation as well as the accumulation of captured cells over the period of storage time. However, the prediction of the cyanobacterial community composition in the SST remained a challenge. Among nutrient parameters, orthophosphate availability was related to community profile in RW samples, whereas communities in ST were influenced by total nitrogen, Kjeldahl nitrogen (N- Kjeldahl), total and particulate phosphorous, and total organic carbon (TOC). No trend was observed on the impact of nutrients on SST communities. This study profiled new health-related, environmental, and technical challenges for the production of drinking water due to the complex fate of cyanobacteria in cyanobacteria-laden sludge and supernatant.

Entities:  

Keywords:  cyanobacteria; cyanobacterial community; high-throughput sequencing; microcystins (MCs); shotgun metagenomics; sludge; water treatment

Mesh:

Substances:

Year:  2021        PMID: 33401450      PMCID: PMC7823770          DOI: 10.3390/toxins13010025

Source DB:  PubMed          Journal:  Toxins (Basel)        ISSN: 2072-6651            Impact factor:   4.546


  43 in total

1.  Forward selection of explanatory variables.

Authors:  F Guillaume Blanchet; Pierre Legendre; Daniel Borcard
Journal:  Ecology       Date:  2008-09       Impact factor: 5.499

2.  The effect of water treatment unit processes on cyanobacterial trichome integrity.

Authors:  Carlos J Pestana; José Capelo-Neto; Linda Lawton; Samylla Oliveira; Ismael Carloto; Helísia P Linhares
Journal:  Sci Total Environ       Date:  2018-12-26       Impact factor: 7.963

3.  Cyanobacterial harmful algal blooms are a biological disturbance to Western Lake Erie bacterial communities.

Authors:  Michelle A Berry; Timothy W Davis; Rose M Cory; Melissa B Duhaime; Thomas H Johengen; George W Kling; John A Marino; Paul A Den Uyl; Duane Gossiaux; Gregory J Dick; Vincent J Denef
Journal:  Environ Microbiol       Date:  2017-02-16       Impact factor: 5.491

4.  Revealing the changes of bacterial community from water source to consumers tap: A full-scale investigation in eastern city of China.

Authors:  Xu Ma; Guiwei Li; Ruya Chen; Ying Yu; Hui Tao; Guangming Zhang; Baoyou Shi
Journal:  J Environ Sci (China)       Date:  2019-07-31       Impact factor: 5.565

Review 5.  Experimental and analytical tools for studying the human microbiome.

Authors:  Justin Kuczynski; Christian L Lauber; William A Walters; Laura Wegener Parfrey; José C Clemente; Dirk Gevers; Rob Knight
Journal:  Nat Rev Genet       Date:  2011-12-16       Impact factor: 53.242

6.  SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data.

Authors:  Murray P Cox; Daniel A Peterson; Patrick J Biggs
Journal:  BMC Bioinformatics       Date:  2010-09-27       Impact factor: 3.169

7.  An Improved Method for High Quality Metagenomics DNA Extraction from Human and Environmental Samples.

Authors:  Satyabrata Bag; Bipasa Saha; Ojasvi Mehta; D Anbumani; Naveen Kumar; Mayanka Dayal; Archana Pant; Pawan Kumar; Shruti Saxena; Kristine H Allin; Torben Hansen; Manimozhiyan Arumugam; Henrik Vestergaard; Oluf Pedersen; Verima Pereira; Philip Abraham; Reva Tripathi; Nitya Wadhwa; Shinjini Bhatnagar; Visvanathan Gnana Prakash; Venkatesan Radha; R M Anjana; V Mohan; Kiyoshi Takeda; Takashi Kurakawa; G Balakrish Nair; Bhabatosh Das
Journal:  Sci Rep       Date:  2016-05-31       Impact factor: 4.379

8.  Microbial Communities Shaped by Treatment Processes in a Drinking Water Treatment Plant and Their Contribution and Threat to Drinking Water Safety.

Authors:  Qi Li; Shuili Yu; Lei Li; Guicai Liu; Zhengyang Gu; Minmin Liu; Zhiyuan Liu; Yubing Ye; Qing Xia; Liumo Ren
Journal:  Front Microbiol       Date:  2017-12-12       Impact factor: 5.640

9.  Nitrogen-phosphorus-associated metabolic activities during the development of a cyanobacterial bloom revealed by metatranscriptomics.

Authors:  Jingrang Lu; Bo Zhu; Ian Struewing; Ning Xu; Shunshan Duan
Journal:  Sci Rep       Date:  2019-02-21       Impact factor: 4.379

10.  CD-HIT: accelerated for clustering the next-generation sequencing data.

Authors:  Limin Fu; Beifang Niu; Zhengwei Zhu; Sitao Wu; Weizhong Li
Journal:  Bioinformatics       Date:  2012-10-11       Impact factor: 6.937

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  3 in total

Review 1.  Evidence-Based Framework to Manage Cyanobacteria and Cyanotoxins in Water and Sludge from Drinking Water Treatment Plants.

Authors:  Farhad Jalili; Saber Moradinejad; Arash Zamyadi; Sarah Dorner; Sébastien Sauvé; Michèle Prévost
Journal:  Toxins (Basel)       Date:  2022-06-15       Impact factor: 5.075

2.  The Effects of Ferric Sulfate (Fe2(SO4)3) on the Removal of Cyanobacteria and Cyanotoxins: A Mesocosm Experiment.

Authors:  Kim Thien Nguyen Le; Eyerusalem Goitom; Hana Trigui; Sébastien Sauvé; Michèle Prévost; Sarah Dorner
Journal:  Toxins (Basel)       Date:  2021-10-23       Impact factor: 4.546

3.  Removal of Cyanobacteria and Cyanotoxins in Waters.

Authors:  Albert Serrà; Laetitia Philippe; Elvira Gómez
Journal:  Toxins (Basel)       Date:  2021-09-09       Impact factor: 4.546

  3 in total

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